GIS Technical Annexes for DRR CCA by Kyan Pbio

manual for mainstreaming disaster risk reduction and climate change adaptation in provincial development and physical framework plans

Manual for Mainstreaming Disaster Risk Reduction and Climate Change Adaptation in Provincial Development and Physical Framework Plans ISBN 978-971-XXXX-XX-X Copyright 2011 National Economic and Development Authority United Nations Development Programme Australian Agency for International Development Millennium Development Goal Achievement Fund 1656 All rights reserved. Any part of this book may be used or reproduced provided proper acknowledgement is made. Published by the National Economic and Development Authority, United Nations Development Programme, Australian Agency for International Development, Millennium Development Goal Achievement Fund 1656 For inquiries, please contact: Director Susan Rachel G. Jose Regional Development Coordination Staff National Economic and Development Authority Tel. Nos. (+63-2) 631 3743 / 631 3708 Email: rdcsmailbox@neda.gov.ph, sgjose@neda.gov.ph Cover design and layout by xxxxxxx, Printed in the Philippines by xxxxxxxxxxxx, Inc.

Volume 7

technical annexes

Contents

Annex A: Cartography guidelines for standardized DRR-CCA format maps!

Annex B: Historical seismicity assessment !

Annex C: Generating ground shaking iteration maps!

Generate presentation format ground shaking maps! Generate raster to vector format ground shaking maps! Generate GRD format ground shaking iteration maps!

Annex D: Generating Liquefaction Iteration Maps! Generate presentation format liquefaction iteration maps! Generate raster to vector format liquefaction iteration maps! Generate GRD format iteration maps for vector conversion!

Annex E: Generating Earthquake induced landslide Iteration Maps!

19 20 22

25 25 26 27

Generate presentation format earthquake induced landslide iteration maps! Generate raster to vector format earthquake induced landslide iteration maps! Generate GRD format earthquake induced landslide iteration maps!

31 32 33

Annex F: Raster to vector conversion of REDAS generated iteration maps!

Conversion using the RGB profile! Conversion using the GRD to vector method!

Annex G: Risk to population estimation! Risk to Property for individual areas! Prepare a barangay administrative map with the required attribute field! Prepare the hazard exposure map! Compute for the affected areas per hazard occurrence! Compute for the affected population per hazard occurrence! Input the factor of fatality per hazard occurrence! Estimate the consequence of fatality per hazard occurrence! Fatality Risk Computation!

Compute for the municipal level risk! Compute for the barangay level weighted risk to fatality! Compute for the municipal level risk to fatality!

Municipal Risk to Fatality Prioritization!

Annex H: Risk to property estimation! Risk estimation for Built-up and AFF areas! Prepare a Property Inventory Exposure Map! Prepare a Municipal Administrative Map! Prepare the municipal aggregated exposure map! Prepare the hazard exposure map! Compute for the affected areas for each hazard occurrence! Input the factor of damage for each hazard occurrence! Compute for consequence in terms of property damage! Risk computation for built-up and AFF areas!

Estimate risk to critical point facilities! Prepare a critical point utilities exposure dataset! Prepare a critical point facilities hazard exposure dataset!

37 43

51 51 51 51 53 54 55 55 56

60 60 60

67 67 67 69 69 71 72 74 75 76

84 84 86

Compute for the consequence and risk! Aggregate critical point facilities risk estimates to the municipal level!

Estimate risk to lifeline facilities! Prepare a lifeline utilities exposure dataset! Determine the total value of the lifeline assets and risk threshold values! Prepare the hazard exposure lifeline dataset! Aggregate lifeline utilities risk estimates to the municipal level!

Municipal risk to property prioritization!

86 87

88 88 89 90 93

Annex I: Composite Risk Prioritization and Evaluation!

103

Annex J: Consequence in terms of fatality!

107

Fatality Consequence Estimation! Prepare the Barangay Administrative exposure map with the necessary attribute field! Prepare the hazard exposure map! Consequence estimation for individual areas!

Annex K: Consequence in terms of property! Property damage consequence estimation for AFF and Built-up areas! Prepare the Property Inventory Maps! Prepare the hazard exposure map! Consequence estimation for individual areas! Municipal level consequence estimate for AFF and Built-up areas!

Estimate consequence for critical point facilities! Critical point consequence estimation for individual areas! Municipal level consequence estimation for critical point facilities!

Estimate consequence for lifeline utilities! Municipal level consequence estimation for lifeline utilities!

Municipal aggregated consequence for AFF and urban assets! Table joining for municipal level consequence estimation for AFF and urban assets! Calculate the urban consequence!

107 107 107 109

113 113 113 113 113 116

117 117 118

119 120

121 121 122

iii

ANNEX A

Cartography guidelines for standardized DRR-CCA format maps

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Annex A: Cartography guidelines for standardized DRR-CCA format maps The following standard format shall be used in preparing the various map elements for large format hazard maps. All maps shall use the Universal Transverse Mercator Zone 51 Luzon Datum map projection at 1:50,000 scale. Prepare several 1:50,000 scale quadrangle maps to fully cover the boundaries of the Province.

1. Paper size

data frame below the regional title, and placed at the background.

Dimensions shall have a maximum width and height of 40 inches.

5. Scale text

2. Map Title The main map title shall be all capital letters, bold, with font size 26 with a font type Helvetica Neue LT 55. Should be aligned on the top middle portion of the main map data frame.

Scale text should be in absolute scale with a font size of 20, color black, font type of Tw Cen Condensed and aligned in the lower middle portion of the main map data frame below the regional title and on top of the north arrow. 6. Scale Bar

3. Province and Region map title. The Provincial title shall be all capital letters, bold, with font size 24 with a font type Helvetica Neue LT 55. Shall be aligned on the lower middle portion of the main map data frame. The Regional sub title shall be all capital letters, bold, with font size 14, with a font type Helvetica Neue LT 55.Shall be aligned on the lower middle portion of the main map data frame below the Provincial title.

Scale bar type should be the double alternating with black and white color, and using meters as the unit. There should be three major divisions with 4,000 meters as the division value. It should have a ten minor subdivisions. Scale bar should also show one major division before zero. Major division and minor subdivision tick marks should be 20 and 10 pt. respectively and should be indicated below the scale bar.

4. North Arrow North arrow type should be ESRI North 7 or any similar type, with a dimension of 3.6 square inches, with an RGB color profile of 225/225/225. Aligned in the lower middle portion of the main map

Number scale shall be placed below the scale bar with a font size of 14, color black, with font type Tw Cen Condensed. Map division unit shall be placed above the scale bar.

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It shall be aligned in the lower middle portion of the main map data frame below the scale text and on top of the north arrow.

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inches. It shall be placed directly under the iteration map thumbnail maps. Font shall be in Tw Cen Condensed, black, single space, with a font size of 12.

7. Map Projection Information Final processed map should conform with the Clarke 1866 Spheroid, Universal Transverse Mercator (UTM) projection, Mean Sea Level as the Vertical Datum, and Luzon 1911 as the Horizontal Datum.

Content of the technical notes shall contain a summary of the earthquake scenarios used. It should outline the magnitude, depth, and epicenters in longitude and latitude.

It should be in all capital letters, 15, color black, with font type Tw Cen Condensed.

It should also mention the REDAS modeling parameters used such as soil type and soil amplification attenuation used.

It shall be aligned in the lower middle portion of the main map data frame below the scale bar and on top of the north arrow.

It should also mention the software used to process the REDAS iteration maps. 10. Map sources and preparer

8. Main Map Data Frame Dimension shall have a maximum width and height of 31.5 inches. It should indicate geographic coordinates using the Degrees, Minutes and Seconds format. Geographic coordinate labels should be placed on all sides of the data frame with side labels in ver tical orientation. The geographic coordinate should have a five minute interval. Label should use a 15 font size, color black, with font type Helvetica Neue LT 55. Graticule tick mark labels along the bounding box should be black in color, tick height size of 5.0 pt, and 1.0 pt thickness. Graticule intersection marks inside the map data frame should be black and size 8.00. 9. Technical Notes Technical notes shall be aligned to the right of the map bounds. Maximum width of the text box should not exceed 6.4

It should list down all input maps used in the preparation of the hazard map and should be listed down using the bibliography type format. It should include the map title, source/agency, and year of publication. It shall be placed directly under the technical notes aligned at the right side of the map. \Font shall be in Tw Cen Condensed, black, single space, with a font size of 12. The map preparer whether individual, agency of office should be mentioned. 11. Base data legend Base data legend header title shall be all capital letters, bold, with font size 16, and font type of Helvetica Neue LT 55. All legend text labels should have a font size 14, and font type of Helvetica Neue LT 55. All items should a legend patch width and height dimension of 30 and 15 pt respectively. Refer to the Table A-1 on the specific legend color and annotation format per layer.

16°15'0"N

ua al

Riv

Infanta 279

Base data legend

428

Ba as it er

315

459

396

ZAMBALES

Riv

Sual

lit eB

s Ri ver

499

569

457

691

188

Bugallon

305

Aguilar

448

1212

314 329

Urbiztondo

REGION 1- ILOCOS

285

San Carlos City

Basista

Bayambang

Santa Barbara

852

Mangatarem

Calasiao

PANGASINAN

Malasiqui

VERTICAL DATUM............................................. MEAN SEA LEVEL HORIZONTAL DATUM........................................... LUZON DATUM

SPHEROID............................................................. CLARKE 1866 PROJECTION.........................UNIVERSAL TRANSVERSE MERCATOR

Kilometers

1:150,000

lan River

Manaoag

Bautista

a Mitur

Laoac

Alcala

Pozorrubio

120°30'0"E

TARLAC

Sinoca

Mapandan

San Jacinto

PROVINCE OF PANGASINAN

120°15'0"E

Lingayen

Mangaldan

Sison

Santo Tomas

Villasis

Urdaneta

Riv

North arrow, scale text, Scale bar, map projection information

557

Labrador 568

Binmaley

Dagupan

San Fabian

Binalonan

549

382

Balungao

Santa Maria

mon

ve Ri

120°45'0"E

Tayug

San Nicolas

376

Riv

NUEVA ECIJA

Umingan

isia al Cab

San Quintin

Natividad

789

NUEVA VIZCAYA

Integrating Disaster Risk Reduction and Climate Change Adaptation (DRR-CCA) in Local Development and Decision-making Processes

Project:

Provincial Government of Pangasinan in coordination with the National Economic and Development Authority-Region 1 (NEDA-R1)

Composite Map prepared by:

Jarvis A., H.I. Reuter, A. Nelson, E. Guevara, 2008, Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture (CIAT), available from http://srtm.csi.cgiar.org.

Administrative Boundaries, National Roads and Rivers - National Mapping and Resource Information Authority

Rapid Earthquake Damage Assessment System (REDAS) Philippine Institute of Volcanology and Seismology, 2011

Map Sources:

Raster Maps generated in REDAS was further processed using ARCGIS 9.3

Earthquake Modelling conducted by the Provncial Government of Pangasinan using the Rapid EarthquakeDamage Assessment System Software of the Philippine Institute of Volcanology and Seismology (REDAS-PHIVOLCS)

Indicated ground shaking intensity is the highest observed PEIS intensity emanating from the three scenrio earthquakes.

120.5 Longitude and 16.1 Latitude 120.22 Longitude and 15.87 Latitude 120.0 Longitude and 16.00 Latitude

Composite ground shaking map is based from a hypothetical 7.8, magnitude scenario earthuakes at a depth of 26 kilometers at the following epicenters:

Technical Notes:

Main Data Frame

Province and Region Map Title

Rosales

Asingan

San Manuel

BENGUET

120°45'0"E

16°15'0"N

Figure A-1. Map elements of Standardized DRR/CCA large format maps

Susceptibility Legend

PEIS - PHIVOLCS Earthquake Intensity Scale

120°0'0"E

317

267

ino

Poro Island, Sual

Cabalitian Island, Sual

Camas Island, Sual

PEIS Intensity VIII PEIS Intensity VII PEIS Intensity VI PEIS Intensity lower than VI

147

Mabini

Alam

Hundred Islands, Alaminos

Agno River

Map Title

Ambayabang River

River

Burgos

Rive r

Island Alo Island, Alaminos

Punacalan Island

Low Frequency

at Riv

Dasol

lin cagu in

Alaminos

Anda

LA UNION

120°30'0"E

dag

SUSCEPTIBILITY

Tambac Island, Bolinao

Islet, Anda

Island, Bolinao

Tanduyong Island, Anda

120°15'0"E

GROUND SHAKING HAZARD MAP

Agency Logos

Inset Maps

Map Sources and Preparer

Technical Notes

Iteration Maps

Provincial Boundaries City/Municipal Boundaries National Roads Spot Elevation Rivers Contour Elevation (100 meters)

Dasol

Agno

Bani

Bolinao

Narra Island, Anda

Island, Anda

Siapar Island, Anda Cangaluyan Island, Anda

Islet, Bolinano

Santiago Island, Bolinao Tagaporo Island, Bolinao

Dewey Island, Bolinao

Dos Hermanos Islands, Bolinao

Silaqui Island, Bolinao

120°0'0"E

Aro

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BASE DATA LEGEND

119°45'0"E

Figure A-1 Sample DRR-CCA standardized map

AND

16°0'0"N

P ROVINCIAL D EVELOPMENT

15°45'0"N

River

gan

Ineran

er Riv Bued

ve r y Ri g Ri ve

sa linaa inat en

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16°0'0"N

FOR

15°45'0"N

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Line Line

Road Network

Polygon

Not Susceptible

Polygon Polygon

Prone

Not Prone

Tsunami

Polygon Polygon

None

255/0/0

None

10% Simple Hatch (2.0 pt. separation)

None

190/255/232

None

0.5

Times New Roman (Capital and Lower Case)

None

0/0/255

168/112/0

Along the line

Right relative to point

Middle alignment relative to Polygon

Placement

AND

Low

None None

Times New Roman (Capital and Lower Case)

No Annotation

168/112/0

0/0/0

Color (RGB)

P ROVINCIAL D EVELOPMENT

Accumulation Zone

255/255/0

255/0/0 197/0/255

Polygon Polygon

High

Moderate

None None

1.0

0.5

Times New Roman (Capital and Lower Case)

No Annotation

Annotation

Earthquake Induced Landslide Susceptibility Map

Low

Not Susceptible

None None

0.5 1.5

Times New Roman

Size

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None

255/255/0

Polygon Polygon

Moderate

255/0/0 197/0/255

Polygon Polygon

High

Liquefaction Susceptibility Map

197/0/255

Polygon Polygon

PEIS Intensity VI

PEIS Intensity lower than VI

None

64/101/235

0/112/255

156/156/156

3.4

0.75

1.25

Times New Roman

Swiss721BT Roman (All Caps)

Font Type

FOR

255/255/0

255/181/189

Polygon Polygon

PEIS Intensity VIII and Above

Solid line

Dashed 2:1 (ESRI Preset)

Solid line

Dashed 2:1 (ESRI Preset)

255/55/55

230/152/0

1.5

Size (pt.)

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PEIS Intensity VII

Ground Shaking Hazard Map

Earthquake Related Hazards

Hazard Map Symbology

255/0/0

151/219/242

Line

Inland water bodies

N/A

Polygon/Line

Intermittent Rivers

0/112/255

Perennial Rivers

N/A

Freeway (ESRI Preset)

Cart trails

Dashed 2:1 (ESRI Preset)

N/A

Line

Depression

Dashed 2:1 (ESRI Preset)

Solid line

0/0/0

Cross

ESRI ERS Infrastructures S1, Unicode 102 (ESRI Preset)

0/0/0 0/0/0

Dashed 2:1 (ESRI Preset)

N/A

N/A N/A

Line Line

Contour Elevation Lines (20 meter contour interval)

N/A

Line

Contour Elevation Lines (100 meter contour interval)

Contour Supplementary (5 and 10 meter intervals)

N/A

Point

Spot Elevation

N/A

Point

None

Dashed 2:1 (ESRI Preset)

Color (R/G/B)

255/255/255

Outline/Line/Point

Feature Symbology Line/Symbol Type

Fill Color (R/G/B)

Bridges

Polygon Polygon/Line

Municipal Boundaries of the Province

Feature Type

Provincial Boundaries of the Philippines

Base Map Layers

Layer and Order

Table A-1. Standard layer symbologyies and annotation format

8 P HYSICAL F RAMEWORK P LANS

Polygon Polygon

Moderate

Low

Polygon Polygon Polygon

Low

Accumulation Zone

Polygon Polygon Polygon

Inundations of 1m. surges

Prone (If only one susceptibility class is provided

Polygon Polygon Polygon

Moderate

Low

Prone (If only one susceptibility class is provided

255/0/0

Prone (If only one susceptibility class is provided

Within 6-Km Danger Zone Polygon

Polygon

Low

Six-kilometer Danger Zone

None None

255/255/0

Polygon

Moderate

255/0/0

None

None None

Polygon

Placement

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255/0/0

None None

255/0/0 197/0/255

Polygon

High

Lava Flows

None

Polygon

Low

None

255/255/0

Polygon

Moderate

0.5

None

190/255/232

None

255/0/0

None

197/0/255

10% Simple Hatch (2.0 pt. separation)

0.5

Polygon

None

190/255/232

None

Polygon

255/0/0

255/255/0

197/0/255

10% Simple Hatch (20 pt. separation)

None

Color (RGB)

Annotation

High

Pyroclastic Flows and surges

Polygon

High

Lahar

255/0/0

255/255/0

197/0/255

255/0/0

None

255/255/0

None

Size (pt.)

Size

AND

Volcanic Related Hazards

Polygon

Inundations of >1 to 4m. surges

255/0/0 197/0/255

None

Color (R/G/B)

Font Type

P ROVINCIAL D EVELOPMENT

Inundations of >4m to 12m surges

Storm Surge

Polygon

Line/Symbol Type

Outline/Line/Point

Feature Symbology

Moderate

255/255/0

197/0/255

255/0/0

Color (R/G/B)

Fill

M AINSTREAMING DRR/CCA

High

Rain Induced Landslide

Polygon

High

Flood

Feature Type

FOR

Hydrometeorologic Hazards

Layer and Order

Table A-1. (Continued) Standard layer symbologyies and annotation format

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12. Susceptibility Susceptibility legend header title shall be all capital letters, bold, with font size 16, and font type of Helvetica Neue LT 55. All legend text labels should have a font size 14, and font type of Helvetica Neue LT 55.

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should have a maximum width and height of 3.6 and 3.5 inches. Both data frame background color shall be (190/232/255) with a frame outline of (0/0/0) and 1 pt. line thickness. It shall be placed in the lower right portion of the map above the agency logos. 14. Agency Logos

All items should a legend patch width and height dimension of 30 and 15 pt respectively. Refer to the Table A-1 on the standard symbology for susceptibility layer per hazard type. 13. Inset Maps The first inset map indicates the location of the Province relative to the country, The data frame should have a maximum width and height of 2.65 and 3.5 inches. The second inset map indicates the location of the Province relative to the adjacent provinces, The data frame

All logos shall have a minimum height of one inch. All provinces covered by the technical assistance should include the agency logos of the National Economic Development Authority (NEDA), United N a t i o n s D e v e l o p m e n t P ro g r a m m e (UNDP), Australian Agency for International Development (AusAID), and the Millennium Development Goal Achievement Fund (MDGF).

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Historical seismicity assessment

ANNEX B

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Annex B: Historical seismicity assessment This process is a pre-requisite for generating the various iteration maps needed for earthquake related hazards. The assessment is undertaken to define several earthquake scenarios that will serve as the basis for REDAS based seismic hazard simulation for the generation of hazard iteration maps. An earthquake scenario is described using four (4) parameters: the magnitude, the epicenter, depth and fault azimuth. A minimum of five scenarios will be generated for each seismic hazard. The assessment will based on the DOST-PHIVOLCS REDAS built-in seismic catalog of past earthquakes. 1. Generate the seismic catalog using the Seismicity Assessment tool of REDAS. 2. Plot the provincial boundaries in REDAS. Zoom in and out and pan to the approximate location of your province and determine the farthest north, south, east and west bounds (in latitude and longitude) and write down the map extents. Add 1.80 degree (approximately 200 kilometers) in the northern and eastern map extents and deduct 1.80 degree in the southern and western map extents, this will include all possible historical earthquakes considered to significantly affect the province based on the epicentral distance Use the built in XY tool and query points tool and refer to the long-lat indicator in the REDAS map interface. 3. Open the seismic assessment tool. Input the coordinate range in the coordinate range input menu you derived in the previous step. This shall be your selection criteria in

terms of epicentral distance relative to your provincial boundaries. 4. Still in the Seismic Assessment calibration window, set the date range as 16000101 and 20111231 (this date is interpreted as Year 1600 Month 01 and Day 01 to Year 2011 Month 12 Day 31), select the SOEPD- PHIVOLCS as the catalog input database, change the depth to 0 to 300 filter all shallow to intermediate depth earthquakes, input the magnitude as 5-9 to select all moderate to high magnitude earthquake events. 5. In the Earthquake classification select all the listed possible earthquake types and maintain the default values for the other parameters. Click the sort button and view the seismic catalog. 6. Save the seismic catalog into the REDAS default format. Convert the REDAS exported catalog into a Microsoft Excel document (or any similar spreadsheet softwares). 7. Plot the seismicity map based on the selection parameters.

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8. Create another seismicity map plotting the NEIC-USGS database using the same selection parameters in steps b-e. Save a seismic catalog into the REDAS default format and plot a seismicity map using the results of the NEIC-USGS database. 9. Refer to the PHIVOLCS regional active faults maps covering the Province. List down all the possible faults generators that fall within the map extent. You should identify active faults, fault traces and trenches. Input the unique fault names or segments in column 2. These will serve as a master list of faults representing possible earthquake generators that may affect the province. When segments do not have unique names, document the longitudinal and latitudinal location of start and end points of the fault. 10.Document the estimated length (in kilometers) of each fault segment. The estimated length can be used to determine a hypothetical magnitude when the historical seismic catalog did not yield any large magnitude earthquakes for simulation purposes. 11.Determine the highest observed magnitudes emanating from the fault source using the SOEPD database and the NEIC-USGS database which includes a compilation of historical earthquakes (Dr. B. Bautista and Dr. L. Bautista). Only select high magnitude events adjacent or along the fault source. Document the date, epicenter (longitude and latitude), magnitude and depth. This will serve as a list of historical earthquakes that likely emanated from the specific fault source. Users are expected to consult with PHIVOLCS to verify the earthquake events emanating from a particular fault,

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trench or fault segment. Document your findings in columns 10 to 15. 12.To facilitate the identification of epicenters, plot the epicenters in GIS. In GIS, create a point feature shapefile by plotting the longitude and latitude points of the encoded catalog using the Make XY Event Layer (Data Management) tool. Load/add the data epicenter table in GIS containing the longitude and latitude values, specify the X field as the longitude and Y field as the latitude, and name the temporary feature shapefile as epicenters. Right click the temporary shapefile in the table of contents and export the file as REDAS epicenters. 13.One scenario should be generated per possible fault generator. Place one epicenter along the fault, preferably at a point nearest to the major urban center of the Province. List the hypothetical longitude and latitude of the epicenter for each fault in columns 4 and 5. 14.A d o p t t h e h i g h e s t o b s e r v e d magnitude per fault source based on the list of historical events. Input the simulation magnitude per fault in column 6. Consult PHIVOLCS to determine a suitable magnitude for fault segments where the magnitudes can not be identified based on available historical seismicity data. 15.Use a 1 km. depth for scenario earthquakes for faults and fault traces and use a 35 km. depth for ear thquakes emanating from trenches. This will replicate a hypothetical high magnitude earthquake occurring at a shallow depth. Input the depth in column 7.

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Table B-1 Sample Earthquake Simulation Parameters, Province of Tarlac1

REDAS Simulation Parameters4 Scenario

Fault Source/

Name2

East Zambales Fault

Iba Fault

PFZ Digdig Fault

Estimated Fault length (km)

110

28.14

115

Epicenter Longitude

Latitude

120.453

120.189

120.987

15.427

15.241

15.890

Past Earthquake Events along the fault3

Depth

Fault Azimuth1

Fault Azimuth2

Year

Month

Day

1987 1877

7.6

6.9

7.9

330.5109

299.505

339.829

153.2249

124.426

153.924

West Boundary Fault

120

119.812

15.624

7.5

1.1235

171.972

Manila Trench

255

119.188

15.502

7.6

356.7293

180.7347

San Manuel Fault

38.7

120.768

15.966

6.9

311.4235

129.867

San Jose Fault

67.5

129.867

16.013

5.5

331.26

149.743

PFZ Infanta Fault

Tubao Fault

125

150

121.252

120.465

15.519

16.293

Epicenter

Magnitude

7.6

6.6

317.06

327.528

138.813

149.349

Abra River Fault

117

120.686

16.957

6.9

342.837

156.037

Casiguran Fault

200

121.571

15.737

7.5

46.684

227.602

Phil. Trench East Luzon Trough

1214

122.655

15.659

8.1

24.211

196.144

West Valley Fault

121.2256

15.0805

6.5

4.7638

196.6994

Longitude

Latitude

Magnitude (Ms)

Depth

120.301

16.066

7.4

107

120.45

15.55

5.8

1963

120.1

15.7

7.6

1959

120,5

15,5

6.6

150

1986

119.88

15.22

6.9

1969

120.064

14.968

6.1

1933

120

15.5

6.5

120

1645

121.2

15.6

7.9

1990

121.172

15.679

7.8

1990

121.04

16.6

6.3

1934

119

17.5

7.6

1924

119

6.9

1872

119.45

15.8

6.8

1796

120.5

16,1

6.9

1884

120.95

15.75

5.2

1886

120.65

16.35

5.3

1883

120.75

16.3

5.5

1880

121.55

14.9

7.6

1937

121.5

14.5

7,3

1824

121.9

14.2

7.4

1927

120.5

16.5

6.2

140

1990

120.412

16.385

6.1

1892

120.4

16.4

6.6

1839

120.65

16.95

6.9

1968

122.1

16.3

7.3

1970

122.201

16.522

7.3

1688

122.2

16.95

7.5

1970

121.71

15.78

8.1

1658

121.1

14.65

5.7

1863

120.9

14.55

6.5

1Earthquake

simulation parameters, with the exception of the Iba, San Manuel, San Jose, Tubao, and Abra river Faults, were based from the Metro Manila Earthquake Reduction Study Fault Model Parameters of Scenario Earthquakes for Hazard Estimation and was used as basis for the earthquake scenarios for the Province of Tarlac. 2Refer

to the PHIVOLCS Regional Active Faults Map for the name of the faults.

3Refer

to the REDAS Seismicity Assessment using the SOEPD and NEIC-USGS databases. Only select a maximum of highest observed magnitude events occurring within the vicinity of the fault. Some earthquake events may not necessarily be generated by the specified fault but such scenarios can be documented and further verified with PHIVOLCS. 4Provinces

are advised to consult with PHIVOLCS regarding suitable earthquake simulation parameters applicable for their area. To facilitate the consultation process, it is recommended that provinces prepare an initial summary matrix of earthquake scenarios.

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16.Determine the fault azimuth per earthquake scenario. Find the fault where the epicenter is located. Click the Assign Fault Azimuth at the left side of the REDAS map interface. Left click and right click on two points of the fault with the epicenter located between the points. This will calibrate the angle of propagation from the fault/epicenter. Changes in the Azimuth will be viewable upon o p e n i n g t h e S e i s m i c H a z a rd Assessment Window. List down the Fault Azimuth in Table 5, columns (7) and (8). Repeat the steps to determine the fault azimuths per earthquake scenario. 17.Create an initial ground shaking simulation map for all identified scenarios. Model all earthquake events identified in Table B-1 in REDAS. You can use a low grid

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resolution to minimize processing time. Make sure that the PEIS contour lines are displayed to determine the approximate distribution of PEIS levels per event. Take note of the spatial location of high intensity levels (PEIS intensity 7 and above) 18.Observe and compare the ground shaking levels of all scenarios. Select a minimum of five scenarios with high ground shaking intensities affecting the province. The five scenarios and the modeling parameters will be used for the seismic hazard assessment portion in REDAS. 19.Summarize the five scenarios and consult with PHIVOLCS for an experts judgement on the identified scenarios.

Important Note: Users are expected to consult PHIVOLCS for an experts judgement on the earthquake scenarios and ground shaking simulation parameters applicable to the Province. This will ensure that all significant fault generators will be covered and the potential earthquake parameters are valid. Once the simulation parameters have been verified, user can proceed with the generation of provincial level high resolution iteration maps using the REDAS seismic hazard assessment covering ground shaking, liquefaction and earthquake induced landslide.

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Figure 2.1. Sample low resolution ground shaking iteration maps, Province of Tarlac

Scenario 1 East Zambales Fault

Scenario 5 Manila Trench

Scenario 9 Tubao

Scenario 2 Iba Fault

Scenario 6 San Manuel

Scenario 10 Abra River Fault

Scenario 3 PFZ Digdig Fault

Scenario 4 West Boundary Fault

Scenario 7 San Jose

Scenario 8 PFZ Infanta

Scenario 11 Casiguran

Scenario 12 East Luzon Through

PEIS Intensity Scale Color Legend

(1) Compile all the low resolution iteration maps and select a minimum of five (5) scenarios with the highest observed ground shaking intensities affecting the province which will be further processed. (2) In this example, scenarios 1, 2, 3, 4 and 5 were selected as the five scenarios which will be further processed for high resolution mapping.

Scenario 13 West Valley Fault

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Generating ground shaking iteration maps

ANNEX C

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Annex C: Generating ground shaking iteration maps The ground shaking iteration maps are prepared based on the selected scenario earthquakes using the parameters as listed down in Table B-1. The iterations maps will be used to create high resolution provincial level ground shaking hazard maps using REDAS. The ground shaking map will be a vital input in simulating the other earthquake related hazards. Generate presentation format ground shaking maps Presentation format maps are generated in REDAS for users who intend to digitize the maps through map isoline tracing. 1. In REDAS, select the Seismic Hazard Assessment Menu. In the new window display, select Ground Shaking. Create the first selected iteration using the earthquake parameters for Scenario 1 as indicated in Table 5. 2. In the Hypocentral input pane, place the longitude and latitude and input the magnitude and depth. Also input the derived fault azimuths. 3. Plot the PEIS shaded map, use 4/10/1 as the minimum-maximum values, and interval. Enable the PIES contour map (this will indicate a line separating PEIS values that can be used for manual digitization) then set the initial resolution of the grid to 50-70 (test the modeling before creating the 300 grid resolution maps).

4. Enable the Apply Amplification option using the Vs30 Amplification. Resulting intensity levels may depend on the soil type (hard, medium and soft). Take note of all the parameters used specifically, the hypocentral, fault data and the attenuation equation used. This will form part of the technical notes in the resulting map. In REDAS, click the start calculation and plot the map in the GMT parameters window. 5. In the REDAS GMT interface, set the proper longitude-latitude map extent. The map extent for the iteration maps should be limited to the extent of the provincial boundaries. Add 0.1 degree to the north and east bounds of the provincial boundaries then deduct 0.1 of a degree to the south and west bounds. Use A3 type paper and set the map size to 10 inches. Plot the Earthquake Generators in the Axis Proper ties, set the annotation, tick mark and frame spacing to 1, and click the Plot Map button. Use Geographic (WGS84) as the map projection. 6. Take note of the map extent used in the previous step. The North, South, East and West bounds can be used

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in the proper georeferencing of your maps. You can adopt the same map extent for other hazard iteration maps so all the maps will have identical map extents. 7. You will notice a ground shaking map is generated. Take note of the legend directly below the map. This shows the differences in the estimated PEIS values based on your input parameters. In general, areas close to the epicenter have higher ground shaking intensities. Ground shaking intensities dissipates farther away from the epicenter. Also, check if the map extent covers the whole bounds of the Province and that the map grids fit the paper size you used. You can make certain adjustments to the paper and map size dimensions to ensure that georeference points, and the total bounds of the province is properly displayed in the final iteration map. 8. Once everything is final, create a high resolution map by using a 150 grid resolution for the presentation type iteration maps. The presentation map should display the PEIS contour lines, the PEIS shaded color map, and the plot the epicenter. 9. Save your map file as a REDAS native map format for future retrieval. Save it in a DRR CCA folder and l a b e l i t a c c o rd i n g l y ( s a m p l e : pangasinan_GSmap_pres_PEIS Iteration1.map). 10.To save a presentation type raster for mat file, save your file as yourprovince_GSmap_pres_PEIS_ite ration1 in tiff format. Refer to Figure 1 for sample ground shaking iteration maps using three epicenters (using the highest

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observed magnitude and average depth).

Generate raster to vector format ground shaking maps Raster to vector format maps are generated in REDAS for users who intend to convert raster based REDAS format maps using the red, green and blue color profiles into ground shaking intensities based on the color legend scale profile. 1. In creating a REDAS generated map for the purposes of raster to vector conversion, rerun the ground shaking assessment, Retain the earthquake parameters (longitude, latitude, magnitude, and depth). Tick the shaded maps plot PEIS option and change the grid resolution to 300. Note that the higher grid resolution may result in longer processing time. Tick the Apply Amplification option and select the Vs30 Amplification. Retain the Azimuth values you used. (Refer to Figures 2 and 3 for the sample presentation map and the map intended for raster to vector conversion) 2. Disable the Plot PIES contoured map option and the Plot Epicenter option. Also make sure that the provincial boundaries are not indicated (plotted).This is to ensure that only the plotted PEIS map is indicated in the final map. Start calculation and proceed to the GMT map parameters. 3. In the GMT window, untick the plot drainage / rivers, untick the Plot Earthquake Generators option, untick the plot lakes. In the Axis properties, type 1 in the Annotation Spacing, type 0 in the Tick Mark Spacing and Frame Spacing. Do

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not enable the map type display options such as coastline data, DEM, SRTM, Bathymetry, etc. The resulting map should only display the ground shaking values, the outer bounds of map coverage and annotations (for georeferencing purposes), and the coastline. Use the Geographic (WGS84) map projection. 4. Change the map coverage and scale. As a rule of thumb, try to limit the map extent relative to the extent of your provincial boundaries. You can adopt the map extent used in Step g. Set the proper longitudelatitude map extent, add at least half a degree on the north, south, east and west longitude and latitude

bounds of the provincial boundaries. Use A3 type paper and set the map size to 10 inches. 5. S t i l l i n t h e G M T p a r a m e t e r s interface, change the Coastline resolution to high, directly under the use 30x30 sec DEM (from NDGC) option, change the color of the ocean to white. Since the ground shaking map will be further processed and digitized, this step ensures that axis lines will not create black lines in the generated map covering the ground shaking values, the blue ocean will not be classified as ground shaking values. Plot the map and view the processed map in the REDAS main map display window.

Figure C-1. Sample high resolution presentation and raster to vector format ground shaking iteration maps, Province of Pangasinan

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(1) Sample presentation format ground shaking iteration map generated using REDAS. Map indicates the PEIS contour lines which can be used for the map digitization. (2) Sample ground shaking iteration map intended for raster to vector conversion, pixel reclassification will be based on the intensity color legend scale. Color combinations for each ground intensity level can be derived by sampling the range of red, green and blue band and creating a color profile. Notice that the fault and inner grid lines are excluded in the final image.

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6. To save a raster format file, click the Edit and Print Map button in the REDAS map window interface, you will notice a map is opened in Windows Paintbrush. In Windows Paintbrush, Save the file as TIFF then specify the filename as yourprovince_GSmap_digitz_PEIS_it eration1 in a specified folder. 7. Repeat these steps in the generation of ground shaking maps for the other earthquake scenarios. 8. To minimize processing time in generating other seismic hazards (i.e. liquefaction and earthquake induced landslide) it is recommended that you create the other iteration maps for the other hazards before proceeding to the next ground shaking iterations. REDAS uses the ground shaking calculations as inputs to the other seismic hazard assessments. Refer to the generation of liquefaction susceptibility iteration maps in the succeeding chapter. 9. Repeat the process until all the iteration maps have been generated. The number of iteration is dependent on the number of fault and epicenters used to cover the whole province. Important Note:

It is important to note that the necessary GRD file changes every time you simulate a certain hazard. Make sure to copy the specified GRD file every time you finish a the seismic hazard simulation of a particular hazard.

Generate GRD format ground shaking iteration maps

The GRD format is a temporary raster based REDAS format map that can be converted to vector using third party GIS. However, special conversion licenses are required to employ the conversion procedures. 1. Users can repeat the steps in generating the iteration maps using

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the raster to vector conversion or presentation format maps. 2. To get a copy of the GRD format map, navigate to C:REDAS\temp folder and sort the files according to the Date modified date/time. 3. Take note of the files with a *.GRD extension. Some are input raster files that are used in simulating earthquake hazards and some are the output raster format maps used in the final out map when you plot the map in REDAS. 4. Right click and copy the intens.grd file. This is the output *.grd file of the PEIS intensity map. (The values in the intens.grd will depend on the intensity unit you used (either PEIS or MMI) in measuring ground shaking. Paste the file in your desktop and rename the file as PEIS_1 (PEIS map for scenario 1). 5. Now simulate the ground shaking map using the PGA values. Plot the contoured PGA values and create a Tiff file of the PGA ground shaking map. 6. Navigate to C:REDAS\temp folder and sort the files according to the Date Modified date/time. You can enable the Date modified sorting header by right clicking the field spaces then select â&#x20AC;&#x153;Date Modifiedâ&#x20AC;?. 7. Right click and copy the pga.grd file. This is the output *.grd file of the PGA values map based on your simulation parameters. Paste the file in your desktop and rename the file as PGA_1 (PGA map for scenario 1). 8. The intens.grd and pga.grd files can be exported to vector format using third party GIS equipped with a d d i t i o n a l s o f t w a re e x t e n s i o n license/s.

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Figure C-2. Sample high resolution ground shaking iteration maps, Province of Tarlac

Scenario 1 East Zambales Fault

Scenario 2 Iba Fault

Scenario 4 West Boundary Fault

Scenario 3 PFZ Digdig Fault

Scenario 5 Manila Trench

PEIS Intensity Scale Color Legend

(1) The above images are the high resolution REDAS generated iteration maps in raster format with a provincial map extent. (2) These maps shall be converted to vector format using other GIS based softwares either through digitizing using manual tracing (tracing along isopleths) or raster to vector conversion using the RGB color profile of the REDAS legend scale as a basis for classifying pixel RGBvalues into PEIS values.

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Generating liquefaction iteration maps

ANNEX D

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Annex D: Generating liquefaction iteration maps The liquefaction hazard iteration maps are prepared based on the selected scenario earthquakes using the parameters as listed down in Table B-1. Similarly, the iterations maps will be used to create a liquefaction hazard map. As a general rule, two maps per iteration are prepared. One for presentation purposes (low grid resolution, where epicenters and fault sources are indicated) which will be included as inset maps in the large format Provincial hazard map and another for intended for raster to vector conversion.

Generate presentation format liquefaction iteration maps 1. In REDAS, re-run the ground shaking hazard assessment using the same parameters for the first earthquake scenario. Use the exact modeling parameters for the generation of the iteration maps. It should be noted that REDAS uses the ground shaking calculations as inputs to the other seismic hazard assessments. 2. Note: To minimize map processing time, it is recommended that the user proceed with the other seismic hazard assessment (liquefaction and earthquake induced landslide) after the generation of one ground shaking map iteration. 3. For the generation of presentation type REDAS maps, use a low resolution of 150 inputed during the ground shaking assessment. 4. Proceed to the liquefaction hazard assessment. Plot Shaded

Liquefaction Potential Map. Set the minimum/maximum/interval values as -0.9/0/0.05. Retain the recommended minimum/maximum/ interval values in order to apply the color profile table in classifying RGB colors into susceptibility levels. Changing the minimum/maximum/ interval values may result in a modification of the color profile table. 5. Use the Wet Season condition and Apply Site Amplification option. Calculate the exceedance values and plot the map. 6. Note: The REDAS software shall compare actual acceleration values with critical acceleration values. The exceedance between the two values (actual acceleration exceeding the critical acceleration) is used as an indicator whether liquefaction is possible. The higher the exceedance of actual acceleration from critical acceleration, the higher the possibility that liquefaction might occur. Critical acceleration is based

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on site conditions such as slope, geomorphology, geology and soil. 7. In the REDAS GMT interface, set the proper longitude-latitude map extent. The map extent for the iteration maps should be limited to the extent of the provincial boundaries. Add 0.1 degree to the north and east bounds of the provincial boundaries then deduct 0.1 of a degree to the south and west bounds. Use A3 type paper and set the map size to 10 inches. Plot the Earthquake Generators in the Axis Proper ties, set the annotation, tick mark and frame spacing to 0.5 click the Plot Map button. Use Geographic (WGS84) as the map projection. 8. Save the map file as TIFF (*.tif, *.tiff) then specify the filename as yourprovince_lique_pres _iteration1 in a specified folder.

Generate raster to vector format liquefaction iteration maps Raster to vector format maps are generated in REDAS for users who intend to convert raster based REDAS format maps using the red, green and blue color profiles into exceedance values based on the color legend scale profile. The liquefaction GRD file will be based on the input ground shaking simulation and will change depending on the ground shaking map generated. 1. In creating a REDAS generated map for the purposes of raster to vector conversion, rerun the ground shaking assessment, retain the earthquake parameters (longitude, latitude, magnitude, and depth) Tick the shaded maps plot PEIS option and change the grid resolution to

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300. Note that the higher grid resolution may result in longer processing time. Use the Apply Amplification option and select the Vs30 Amplification. Retain the Azimuth values you used. (Refer to Figure D-1 for the sample presentation map and the map intended for raster to vector conversion.) 2. Figure D-1. Sample liquefaction hazard iteration map using REDAS. 3. Disable the Plot PEIS contoured map option and the Plot Epicenter option. This is to ensure that only the liquefaction exceedance values are indicated in the final map. Start calculation and proceed to the GMT map parameters. 4. P r o c e e d t o L i q u e f a c t i o n Assessment. Use the same parameters in the liquefaction assessment (shaded legend minimum, maximum and interval values, soil amplification and wet season assumption) when the presentation type map was prepared. 5. In the GMT window, untick the plot drainage / rivers, untick the Plot Earthquake Generators option, untick the plot lakes. In the Axis properties, type 1 in the Annotation Spacing, type 0 in the Tick Mark Spacing and Frame Spacing, do not enable the map type display options such as coastline data, DEM, SRTM, Bathymetry, etc. The resulting map should only display the exceedance values, the outer bounds of map coverage and annotations (for georeferencing purposes), and the coastline. Use the Geographic (WGS84) map projection. 6. You can use the same map extent parameters used in the generation of

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ground shaking iteration maps. This will make georeferencing easier where the saved georeferencing text file can be loaded and applied to the raster map. 7. S t i l l i n t h e G M T p a r a m e t e r s interface, change the Coastline resolution to high, directly under the use 30x30 sec DEM (from NDGC) option, change the color of the ocean to white. Plot and generate the liquefaction hazard map. 8. Save the file as TIFF (*.tif, *.tiff) then specify the filename as yourprovince_lique_R2V_PEIS_iterati on1 in a specified folder.

9. Repeat the process until all the iteration maps have been generated.

Generate GRD format iteration maps for vector conversion

The GRD format is a temporary raster based REDAS format map that can be converted to vector using third party GIS. However, special conversion licenses are required to employ the conversion procedures. 10.Users can repeat the steps in generating the iteration maps using

Figure D-1. Sample high resolution presentation and raster to vector format liquefaction iteration maps, Province of Pangasinan

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(1) Sample presentation format liquefaction iteration map generated using REDAS. Legend indicates areas where the critical acceleration has been exceeded by the actual acceleration at varying g values. (2) Sample liquefaction iteration map intended for raster to vector conversion, pixel reclassification will be based on the exceedance color legend scale. Red, green and blue band (RGB) color combinations for each exceedance interval will be sampled to create a color range profile per interval. The range of RGB colors will be used for raster to vector conversion using third party GIS. Notice that the fault and inner grid lines are excluded (black pixel colors) in the final image.

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the raster to vector conversion or presentation format maps. 11.Simulate the liquefaction scenario, using the seismic hazard assessment in REDAS. Make sure to click calculate and plot the map. 12.Create a tiff format map of the liquefaction hazard map. 13.Navigate to C:REDAS\temp folder and sort the files according to the Date modified date/time. 14.The pga2.grd file in the temp folder changes every time you simulate a certain hazard. The pga2.grd file you are copying now contains the exceedance values for liquefaction. Prior to simulation, it contained the

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PGA ground shaking values as a result of the ground shaking simulation. When the you calculated for the liquefaction potential map, REDAS changed the values from PGA ground shaking to Liquefaction potential exceedance values. 15.Right click and copy the pga2.grd file. This is the output *.grd file of the exceedance values map based on your liquefaction simulation parameters. Paste the file in your desktop and rename the file as lique_1 (liquefaction map for scenario 1). Move the lique_1.grd file to the folder you created in step 3.

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Figure D-2. Sample high resolution liquefaction iteration maps, Province of Tarlac

Scenario 1 East Zambales Fault

Scenario 2 Iba Fault

Scenario 4 West Boundary Fault

Scenario 3 PFZ Digdig Fault

Scenario 5 Manila Trench

Exceedance value (g)

(1) The above images are the high resolution REDAS generated iteration maps in raster format with a provincial map extent. Color legend is expressed as event specific exceedance values derived from the difference between the critical acceleration and the actual acceleration. (2) These maps shall be converted to vector format using other GIS based softwares either through digitizing employing manual tracing or raster to vector conversion using the RGB color profile of the REDAS legend scale as basis for reclassifying pixel RGB values into exceedance values.

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Generating earthquake induced landslide Iteration maps

ANNEX E

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Annex E: Generating earthquake induced landslide Iteration maps The EIL iteration maps are prepared based on the selected scenario earthquakes using the parameters as listed down in Table B-1. Similarly, the iterations maps will be used to create an earthquake induced landslide hazard map. As a general rule, two maps per iteration are prepared. One for presentation purposes (low grid resolution, where epicenters and fault sources are indicated) which will be included as inset maps in the large format Provincial hazard map and another for intended for raster to vector conversion

Generate presentation format earthquake induced landslide iteration maps 1. In REDAS, re-run the ground shaking hazard assessment using the same parameters for the first earthquake scenario. Use the exact modeling parameters for the generation of the iteration maps. It should be noted that REDAS uses the ground shaking calculations as inputs to the other seismic hazard assessments. 2. Note: To minimize map processing time, it is recommended that the user proceed with the other seismic hazard assessment (liquefaction and earthquake induced landslide) after the generation of one ground shaking map iteration. 3. For the generation of presentation type REDAS maps, use a low resolution of 150 inputed during the ground shaking assessment.

4. Proceed to the earthquake induced landslide hazard assessment and plot the Landslide Potential Map. Set the minimum/maximum/interval values as -0.9/0/0.05. Note: Retaining the above mentioned parameters will allow the user to use the same color table profile in Annex 2 to classify the exceedance values into susceptibility categories during the raster to vector conversion. 5. Use the Wet Season condition and Apply Site Amplification option. Calculate the exceedance values and plot the map. 6. In the REDAS GMT interface, set the proper longitude-latitude map extent. The map extent for the iteration maps should be limited to the extent of the provincial boundaries. Add 0.1 degree to the north and east bounds of the provincial boundaries then deduct 0.1 of a degree to the south and west bounds. Use A3 type paper and set the map size to 10 inches.

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Plot the Earthquake Generators in the Axis Proper ties, set the annotation, tick mark and frame spacing to 0.5 click the Plot Map button. Use Geographic (WGS84) as the map projection. 7. Save the map file as TIFF (*.tif, *.tiff) then specify the filename as yourprovince_EIL_pres_iteration1 in a specified folder.

Generate raster to vector format earthquake induced landslide iteration maps Raster to vector format maps are generated in REDAS for users who intend to convert raster based REDAS format maps using the red, green and blue color profiles into exceedance values based on the color legend scale profile. The ear thquake induced landslide GRD file will be based on the input ground shaking simulation and will change depending on the ground shaking map generated. 8. In creating a REDAS generated map for the purposes of raster to vector conversion, rerun the ground shaking assessment, retain the earthquake parameters (longitude, latitude, magnitude, and depth) Tick the shaded maps plot PEIS option and change the grid resolution to 300. Note that the higher grid resolution may result in longer processing time. Use the Apply Amplification option and select the Vs30 Amplification. Retain the Azimuth values you used (Refer to Figure E-1 for the sample presentation map and the map intended for raster to vector conversion). 9. Disable the Plot PIES contoured map option and the Plot Epicenter option.

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This is to ensure that only the liquefaction exceedance values are indicated in the final map. Start calculation and proceed to the GMT map parameters. 10.P r o c e e d w i t h t h e L a n d s l i d e assessment. Use the wet season assumption, and apply the site amplification option. Calculate the exceedance values and plot the map. 11.In the GMT window, untick the plot drainage / rivers, untick the Plot Earthquake Generators option, untick the plot lakes. In the Axis properties, type 1 in the Annotation Spacing, type 0 in the Tick Mark Spacing and Frame Spacing > do not enable the map type display options such as coastline data, DEM, SRTM, Bathymetry, etc. The resulting map should only display the exceedance values, the outer bounds of map coverage and annotations (for georeferencing purposes), and the coastline. Use the Geographic (WGS84) map projection. 12.You can use the same map extent parameters used in the generation of ground shaking iteration maps. This will make georeferencing easier where the saved georeferencing text file can be loaded and applied to the raster map. 13.S t i l l i n t h e G M T p a r a m e t e r s interface, change the Coastline resolution to high, directly under the use 30x30 sec DEM (from NDGC) option, change the color of the ocean to white. Plot and generate the liquefaction hazard map. 14.Save the file as TIFF (*.tif, *.tiff) then specify the filename as yourprovince_EIL_R2V_iteration1 in a specified folder.

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Figure E-1. Sample high resolution presentation and raster to vector format earthquake induced landslide iteration maps, Province of Pangasinan

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(1) Sample presentation format liquefaction iteration map generated using REDAS. Legend indicates areas where the critical acceleration has been exceeded by the actual acceleration at varying g values. (2) Sample earthquake induced landslide iteration map intended for raster to vector conversion, pixel reclassification will be based on the exceedance color legend scale. Red, green and blue band (RGB) color combinations for each exceedance interval will be sampled to create a color range profile per interval. The range of RGB colors will be used for raster to vector conversion using third party GIS. Notice that the fault and inner grid lines are excluded (black pixel colors) in the final image.

15.Repeat the process until all the iteration maps have been generated.

Generate GRD format earthquake induced landslide iteration maps

16.Simulate the earthquake induced landslide hazard, using the seismic hazard assessment in REDAS. 17.Create a tiff format map of the ear thquake induced landslide hazard map. 18.Navigate to C:REDAS\temp folder and sort the files according to the Date modified date/time. 19.The pga2.grd file in the temp folder changes every time you simulate a certain hazard. The pga2.grd file you are copying now contains the

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exceedance values for earthquake induced landslide. Prior to simulation, it contained the exceedance values of the liquefaction potential map. When the you calculated for the earthquake induced landslide potential map, REDAS changed the values from Liquefaction potential exceedance values to Earthquake Induced Landslide exceedance values. 20.Right click and copy the pga.grd file. This is the output *.grd file of the exceedance values map based on

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your earthquake induced landslide simulation parameters. Paste the file in your desktop and rename the file as EIL_1 (earthquake induced landslide map for scenario 1). Move the EIL_1.grd file to the folder you created in step 3. 21.Now save the REDAS native map file for future retrieval. (When saving the map files, do not place spaces in the filename. Use the underscore character for example EQScenario_1.map)

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Figure E-2. Sample high resolution earthquake induced landslide iteration maps, Province of Tarlac

Scenario 2 Iba Fault

Scenario 1 East Zambales Fault

Scenario 4

Scenario 3 PFZ Digdig Fault

Scenario 5

Exceedance value (g)

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Raster to vector conversion of REDAS generated iteration maps

ANNEX F

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Annex F: Raster to vector conversion of REDAS generated iteration maps There are several ways of converting raster format REDAS maps into vector format to be used in vector overlaying in GIS. One is through digitizing presentation maps where tracing along ground shaking isolines is employed, the other is by way of raster to vector conversion where the red, green and blue bands are used to differentiate the ground shaking intensities based on the ground shaking color scale profiles, and lastly is through the conversion of the temporary GRD file to vector. Conversion using the RGB profile

make a color map table to determine the RGB color range for each intensity or exceedance level interval.

Raster to vector conversion is a different approach to the digitization of raster maps. It utilizes the Red-BlueGreen (RGB) raster bands stored in the raster image which can be used to reclassify and group pixels into categories, in this case PEIS levels and exceedance values (intervals).

Starting with the iteration maps, the conversion process generally involves three major steps namely:

Each raster band (Red, Green Blue) will contain a value ranging from 0-255. A combination of any three of the available bands in a multi-band raster dataset can be used to create RGB composites which is what you see when you load a tiff format image. For raster to vector conversion of REDAS maps, we will convert each RGB color band to a vector polygon which will retain the pixel values (0-255) per band then combine all three vector bands to get a composite RGB attribute table which will contain all the RGB values making up a color profiles. We shall use the select attributes tool to select combinations of RGB values based on the shaded color legend. We will also

1. A t t a c h i n g t h e p ro p e r s p a t i a l reference and georeferencing the REDAS generated iteration map/s; 2. Map reprojection of REDAS maps from WGS84 to Universal Transverse Mecator Projection, Luzon Datum; and 3. Vector conversion of REDAS iteration raster format maps in GIS. Note: To minimize map processing time, it is recommended that the user proceed with the other seismic hazard assessment (liquefaction and earthquake induced landslide) after the generation of one ground shaking map iteration.

Attach the proper spatial reference and georeference the iteration maps

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Figure F-1. Red, Green and Blue bands creating a RGB composite map

The succeeding procedures for raster to vector conversion using the RGB profiles is only applicable using ArcGIS 9.3. Special procedures may be required for other third party GIS softwares. 1. Define the proper spatial reference of the raster dataset maps. Use either arcCatalog or the define projection tool in ArcMap. 2. When defining the projection in arcCatalog, Open arcCatalog and navigate to the folder where the ground shaking iteration maps are located at the left side pane of the ArcCatalog window. At the right side of the ArcCatalog Interface, select and right click the GSmap_digitz_PEIS_iteration1 map.tif (or the name of the appropriate iteration map) file then click Properties. You shall be prompted to the Raster Dataset Properties. Navigate to the Spatial Reference and click the edit button. You will notice the spatial reference Properties window.

3. In the Spatial Reference Properties click Select then click the Geographic Coordinates folder, then W o r l d f o l d e r, t h e n s e l e c t WGS1984.prj, then click Add. This will assign the WGS 84 coordinate system to your raster dataset (which was the map projection used when you generated the REDAS maps). Now notice your Raster Reference Properties, it now has a defined spatial reference of WGS84. Click Apply to make the changes permanent. Do this for the other hazard iteration raster maps. 4. Georeference the REDAS map. Open ArcMap and enable the G e o re f e re n c e t o o l b a r. I n t h e georeference toolbar, select the iteration map as the target layer. Use the annotation tick marks as the control points during georeferencing. As a rule of thumb, the RMS error should not exceed 0.000045 degrees. Also take into consideration the relative error of your final output map. In our case we would like to use our raster

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image at 1:50,000 with a maximum error of five meters. Use at least four control points outside of the provincial boundaries. 5. Save a text file of the georeference information by clicking the save button in the link table window. You can apply the same georeferencing points to other iteration maps (assuming the same page size and resolution was used). 6. Make the changes permanent by updating the Georeferencing points. This will apply the georeference points to the map image so that when you load the map image in the future, it will display the map in the proper longitude-latitude location.

M i n d a n a o ) a n d L u z o n _ 1 9 1 1 _ To _ W G S _ 1 9 8 4 _ 2 ( M i n d a n a o ) . U s e t h e n e a re s t neighbor as the resampling technique and retain the output cell size (current pixel resolution of the raster map). 10.Repeat the process for all the iteration maps. 11.Before proceeding to raster to vector conversion, check and verify if all iteration maps are georeferenced properly. You can load all the scenario maps and check for the alignment of the maps.

Convert from raster to vector

7. W h e n g e o r e f e r e n c i n g t h e succeeding iteration maps using the saved text file, load the map image, select the target layer in the georeferencing toolbar. Open the link table and open the georeferencing text file you saved in step (e). Apply the changes permanently.

12.Select an iteration map. In ArcMap, navigate to the iteration map and display the three bands namely Band_1, Band_2, Band_3. Band_1 contains the Red values. Highlight and select all three layers. (Note: Make sure you have georeferenced and reprojected your raster data to UTM, Luzon Datum before proceeding)

Re-project maps from WGS84 t o U n i v e r s a l Tr a n s v e r s e Mecator Projection, Luzon Datum

Note: For the ground shaking maps, the bands represent the various PEIS values. For the liquefaction and the EIL maps, the bands correspond to the exceedance values.

8. In ArcMap, enable the project raster (Management) tool.

13.Use the raster to polygon conversion tool in ArcMap to convert Band_1 into a polygon feature shapefile. The resulting shapefile should have an attribute table that stores the red color values (0-255). Do the same with Band_2 and Band_3, the resulting shapefile and attribute table will contain the green and blue values respectively.

9. In the project calibration window, select the first iteration raster map, you will notice that the input spatial reference is WGS84. Reproject the data to UTM Zone 51N, Luzon Datum as the output coordinate system. Only the areas of Palawan shall use UTM Zone 50N. Note: when assigning the proper geographic transformation, select L u z o n _ 1 9 1 1 _ To _ W G S _ 1 9 8 4 _ 1 (Areas in the Philippines except

14.Union the red and green shapefiles. The resulting shapefile and attribute table will contain columns where the

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red and green (Gridcode and Gridecode_1) values are stored.

shaking iteration map as the sample case:

15.Union the red-green with the blue shapefile. The resulting shapefile and attribute table will contain columns where the red, green and blue values are stored (Gridcode , Gridecode_1, and Gridecode_2).

18.Zoom and pan to one of the polygons belonging to highest PEIS class (or exceedance value for liquefaction or EIL) in the REDAS legend scale. Select one polygon along the color legend. Take note of the values in the RGB gridcodes of your selected polygon.

16.Dissolve the dataset based on the field headings Gridcode, Gridecode_1, and Gridecode_2. This will minimize the number of records in the shapefile layer. 17.Before we reclassify/group polygons into intensity or exceedance levels, first determine the color profiles making up an Intensity level. This process is called color profile mapping. Open both of the raster for mat presentation and high resolution maps. Arrange the layers where the polygon feature is on top, then the high resolution map, then the presentation map. For illustration purposes, the succeeding steps use the ground

19.Now verify the RGB of the raster file and compare it with the union polygon. Click a raster inspector tool to determine the RGB profile of the raster image. Now cross reference this with the values of RGB gridcodes in your attribute table. You will notice that the Red, Green and Blue values raster are the same as the value in the Gridcode (attribute table). 20.Prepare a color map table. The color map table is a guide containing the range values of Red, Green and Blue for each PEIS intensity class (or exceedance value for liquefaction or EIL). The range values will be used

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so we can select a group of polygons via select by attributes tools. Refer to the color map table. 21.Now let us first create a color map for PEIS 9-10. Zoom to the high end of the shaded REDAS color legend scale. Use the identify button and click to the higher limit of the class. Notice that the Red value is 255, Green is 1, then the blue value is zero. Since the upper limit of the scale divide is not a valid scale color because it was “blackened”, you can include R255 G0 and B0 as the upper limit RGB color for PEIS class 9-10. Write down 255 in Red, 0 in Green and 0 in Blue in you upper

limit color map table. (Note the RGB profile sample is based on a ground shaking map generated using REDAS with a minimum/maximum/ interval of 4/10/1, actual color p ro f i l e s m a y d i ff e r a n d v a r y depending on your range-interval values used when you generated your REDAS ground shaking map, proceed with utmost care and use the RGB profiles you see in your raster dataset.) 22.Now zoom/pan to the lower limit of the PEIS 9-10 class in the raster image, you will notice that the Red is 255, Green is 211 and the Blue is still zero. You will also notice that the

Table F-1. Color Map Profile Table for Ground Shaking1 PEIS Intensity Scale

Upper Limit

Red PEIS>=9

8 to <9

7 to <8

6 to <7

255

Lower limit

Attribute Field

Selection Parameters

Red

255

GRIDCODE

= 255

213

GRIDCODE_1

<=213 =0

Green

Blue

GRIDCODE_2

Red

255

Red

GRIDCODE

>=82

Green

214

Green

255

GRIDCODE_1

>=214 =0

Blue

GRIDCODE_2

Red

GRIDCODE

<=81

Green

255

Green

255

GRIDCODE_1

= 255

GRIDCODE_2

<= 127

Blue

127

Red

GRIDCODE

Green

255

Green

170

GRIDCODE_1

>=170

Blue

128

Blue

255

GRIDCODE_2

>=128

Red

255

GRIDCODE

Green

169

Green

Blue

255

Blue

>=0

GRIDCODE_1

<=169

255

GRIDCODE_2

=255

Selection Syntax

"GRIDCODE"=255 AND "GRIDCODE_1" <=213 AND "GRIDCODE_2" =0

"GRIDCODE" >=84 AND "GRIDCODE_1" >=214 AND "GRIDCODE_2" =0

"GRIDCODE" <=83 AND "GRIDCODE_1" =255 AND "GRIDCODE_2" <=127 "GRIDCODE" =0 AND "GRIDCODE_1" >=170 AND "GRIDCODE_2" >=128

"GRIDCODE" >=0 AND "GRIDCODE_1" <=169 AND "GRIDCODE_2" =255

Color profile applicable to a six class with one PEIS intensity per class interval using the default REDAS shaded color scale scheme. Can also be used with a different maximum and minimum PEIS values if a six classes and one interval is used. 1

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Table F-2. Color Map Profile Table for Earthquake Induced Landslide and Liquefaction1 Exceedance Value Range

Upper Limit Red

0 to -0.15 (Low Exceedance)

<-0.15 to -0.25 (Moderate Exceedance)

255

Lower limit

Attribute Field

Selection Parameters

Red

255

GRIDCODE

= 255

213

GRIDCODE_1

<=213

GRIDCODE_2

Green

Blue

Red

255

Red

156

GRIDCODE

>=156

Green

214

Green

255

GRIDCODE_1

>=214 =0

Blue

GRIDCODE_2

Red

155

Red

GRIDCODE

<=155

255

Green

255

GRIDCODE_1

= 255

Blue

199

GRIDCODE_2

<=199

Red

GRIDCODE

255

Green

GRIDCODE_1

>= 28

200

Blue

255

GRIDCODE_2

>=200

Red

255

GRIDCODE

>=0

Green

GRIDCODE_1

<=27

255

Blue

255

GRIDCODE_2

=255

<-0.25 to -0.50 (High Green Exceedance) 2 Blue Red <-0.50 - 0.70 (High Green Exceedance) 2 Blue Red <-0.70 - 0.90 (High Green Exceedance) 2 Blue

Selection Syntax

"GRIDCODE"=255 AND "GRIDCODE_1" <=213 AND "GRIDCODE_2" =0

"GRIDCODE" >=156 AND "GRIDCODE_1" >=214 AND "GRIDCODE_2" =0

"GRIDCODE" <=155 AND "GRIDCODE_1" =255 AND "GRIDCODE_2" <=199

=0 "GRIDCODE" =0 AND "GRIDCODE_1" >=28 AND "GRIDCODE_2" >=200

"GRIDCODE" >=0 AND "GRIDCODE_1" <=27 AND "GRIDCODE_2" = 255

Color profile applicable to an 18 class with 0.05 per class exceedance value interval using the default REDAS shaded color scale scheme. Can also be used with a different maximum and minimum exceedance values if an 18 class interval is retained 2 You can use the selection syntax that combines all three high susceptibility selection syntaxes by using ("GRIDCODE" <=155 AND "GRIDCODE_1" =255 AND "GRIDCODE_2" <=199) OR ("GRIDCODE" =0 AND "GRIDCODE_1" >=28 AND "GRIDCODE_2" >=200) OR ("GRIDCODE" >=0 AND "GRIDCODE_1" <=27 AND "GRIDCODE_2" = 255) 1

marginal scale divide indicating the class breaks is not a valid color as basis for the color map range so we need to determine the colors under the marginal scale to be included in the 9-10 interval. To determine this, you need to sample the upper limit of PEIS 8-9 (or exceedance value for liquefaction or EIL) and see the changes in the RGB values. 23.Now click on the upper limit of the PEIS 8-9 scale. It shows a RGB value of 255/214/0 comparing this with the lower limit RGB value of

255/211/0 there seems to be two colors that are not accounted namely 255/212/0 and 255/13/0. In this case we will adopt the 255/213/0 as the lower limit of the PEIS 9-10. In the color map table, in the lower limit of PEIS 9-10, write down 255 in the Red Column, 213 in Green and 0 in Blue. Then the upper limit of the PEIS scale 8-9 write down RGB as 255, 214, and 0. 24.Repeat the previous steps to determine the upper and lower limit range for each PEIS interval (or

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exceedance value for liquefaction or EIL). 25.Now convert the upper and lower limit RGB range values as a selection expression. Refer to Tables F-1 and F-2 for the color map table. Analyze how upper and lower limit values are transformed into a selection expression syntax. 26.Add another field in the RGB shapefile that will contain the PEIS labels (or exceedance value for liquefaction or EIL). Use the select by attributes tool in the attribute table options and input the selection expression syntax (refer to sample selection expression syntax in Tables B-1 and B-2) for every PEIS intensity (or exceedance value for liquefaction or EIL) to select all polygons. Input the text PEIS intensity labels for each interval. 27.Now select the polygons were not selected (polygons not included in the PEIS color profile interval) and label it as null. 28.Dissolve the dataset based on the reclassified PEIS field (or exceedance value for liquefaction or EIL). 29.Intersect the dissolved iteration map w i t h t h e P ro v i n c i a l B o u n d a r y polygon feature data. Only the polygons within the provincial b o u n d a r i e s w i l l b e re t a i n e d . Scrutinize the attribute table and ensure that the PEIS data is stored in the dataset. 30.User will encounter polygons without PEIS intensities especially in areas near the coastlines. This is due to the coastal outline that have color profiles (mostly black areas) that can not be classified as PEIS intensities. In such cases, user should use other geoprocessing tools like multipart to

single part tool, polygon cut and merge then editing the attribute table to assign the proper PEIS intensities. 31.Repeat the process for all the iteration maps.

Conversion using the GRD to vector method Another method of converting REDAS iteration maps is through the GRD to vector conversion. Create a raster layer in ArcGIS for Ground Shaking PEIS map 1. In ArcGIS, open the Arctoolbox > Multidimension Tools > Double click MakeNetCDF Raster Layer, you will notice a NetCDF input calibration window. 2. In the MakeNetCDF Raster Layer calibration window, in the Input netCDF File drop down menu, click the folder button and navigate to the folder you created in step 5, you will notice an Open file window. In the files of type drop down menu, select File (*.*) this will make all the files in the folder viewable. 3. First create a raster file of the Scenario 1 Ground Shaking Hazard. Select the PEIS_1.grd file). Retain the Variables, X and Y dimension values > change the output raster layer name to PEIS_temp (this data will only be temporary file) > Click Ok. You will notice that a new raster file is displayed in your table of contents. 4. Scrutinize the PEIS_temp map. Notice the high and low values of the PEIS map. This pertains to the PEIS values for each unit pixel. These pixel values can be grouped and

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Select input file

X and Y refers to the longitude and latitude data and the z variable refers to the PEIS values and exceedance values for the liquefaction and landslide *.grd files

Change the output layer name to PEIS_Temp

Click ok to import the *.grd file in ArcMap

reclassified based on your preferred interval scale.

click the PEIS_temp layer > Data > Export Data.

5. Now export the data as a IMAGINE image format file in preparation for raster values reclassification. Right

6. In the export raster data window, change the raster format to imagine image > change the filename to

Right click layer > Data > Export data

Change format to IMAGINE image and rename file as PEIS_1.img

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Old default range values

New unique value per range of values

Classify calibration button

Actoolbox > index tab > Reclassify (3d) PEIS_1.img > change the location scenario 1 folder > click save. You will notice that a new raster layer is added in the table of contents. You can now remove the PEIS_temp.

Input one as the interval size

7. Turn you attention to the PEIS_1.img map. You will notice that the range values per pixel in the symbology. These are the range of values per pixel and it need to be reclassified

Select defined interval in the method drop down menu

Click ok

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New range

Minimum range value

based on the whole number PEIS scale. Let us now reclassify the values by going to arctoolbox > index tab > type in reclassify (3d). You will notice a reclassification calibration window. 8. In the reclassification window, select the PEIS_1.img as the input raster file > change the reclass field to Value. You will notice that there is a window displaying the old and new values. The old values pertain to the raw values of the PEIS map (with decimal numbers) that are expressed as a range of values. The new values will be reclassified unique values assigned to the old range values. We need to assign the old range values 7-8 as a unique value 7 meaning all values within the 7-8 range will be classified as PEIS 7. 9. Now classify your range values and assign the new unique value. Click classify, you will notice that a reclassification calibration window appears. In the calibration window, select defined interval in the method drop down menu > change the interval size to 1 > click ok. 10.Notice that the old range of values were changed based on your

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New unique assigned values

Maximum range value

calibration. Now specify the new values for every range. In the new value column change the values by manually inputing the minimum range value (ex. for 4-5 old values, change the new value to 4). Just assign a No data value for null values. 11.Once you have made the necessary value changes, assign a filename (PEIS_1reclass) and save the file in the scenario 1 folder > click ok. You will notice that a new map is added where the range values are represented as a unique reclassified value. 12.Now convert the reclassified raster based on the unique value. Go to actoolbox > index tab > type in raster to polygon. In the raster to polygon window, select the reclass raster in the input raster drop down menu > unclick the simplify polygon > and specify a shapefile name (PEIS_1.shp) > click Ok. You will notice that you have converted a REDAS *.grd file to a shapefile format. You can dissolve based on the Gridcode to minimize the records of your final ground shaking scenario map.

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Specify value as the field

Input raster to be converted

Untick the simplify polygon option

13.You can dissolve your dataset, create a new field (text with 50 characters) and manually type the PEIS text description for future reference. Create a raster layer in ArcGIS for liquefaction and earthquake induced landslide map Similar to the PEIS map, the liquefaction and earthquake induced landslide map can also be converted to vector but differs in the reclassification of pixel values. The succeeding steps are applicable for converting liquefaction and earthquake induced landslide exceedance values to a polygon shapefile format. 1. The conversion of grd format REDAS maps for liquefaction and Ear thquake induced landslide exceedance values follow a similar procedure. The difference will be that unique exceedance values will be retained. First impor t the lique_1.grd or EIL_1.grd file using the MakeNetCDF Raster Layer.

specify filename and location

2. Convert the raw raster file to an imagine image raster (use lique1.img and EIL_1.img). 3. Change the symbology of the *.img file by going to the table of contents > right click the layer (lique1.img or EIL_1.img) > properties > symbology tab. 4. In the symbology tab,click classified > change the number of classes to four (4) > click classify. You will notice a classification calibration window. 5. In the Method drop down menu, select Manual > navigate to the break values window pane > highlight and select the first value > type in -0.25 (this will create a group with values less than or equal to -0.25 representing the high exceedance value range)> highlight the second value > type in -0.15 (this will create a group with values more than -0.25 but less than -0.15 representing the moderate exceedance value range) > highlight the third value and type in

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Change classes to four (for the high, moderate, low and no exceedance range values) classify

-0.0000001 (this will create a group with values more than -0.15 but less than zero representing the low exceedance value range) > then retain the highest value at the last break value > click Ok > change the color ramp to a high contrast color scheme > click apply. You will notice that your values are grouped into four classes depending on the range break values you made. 6. Now reclassify the values using the reclassify (3d) tool, go to arctoolbox > index > type in reclassify (3d). You will notice a reclassify calibration window. 7. In the reclassify window, notice that the old values column is similar to the break values (range values) you made in step 7. You will also notice that the new value for higher exceedance range (<= -0.25) is

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Use the manual method

Manually highlight/select and type the recommended break values. use -0.25, -0.15,-0.0000001 and retain the highest observed value as the last break value.

currently 1, while -0.25 to -0.15 is classified as 2, -0.15 to -0.0000001 is classified as 3 and the 0 to the highest positive value is 0. 8. Scrutinize your new reclassified raster file. You will notice that your old range value classes were assigned a new unique value (0, 1, 2, 3,). You will also notice a unique value of zero (0). These are the zero to positive values or areas where the hazard (EIL or Liquefaction) did not occur because the actual acceleration is not strong enough to overcome the critical acceleration. 9. Now you can convert your raster file to polygon based on the new reclassified values (3-High exceedance, 2-moderate exceedance, 1-low exceedance, 0No Exceedance). Go to arctoolbox > type in raster to polygon > select the

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New Value column. Manually input the new values as a nominal

Reverse the default new values raster file you created in step 10 > select Value in the field > untick the simplify polygon > specify an output name and location (Lique_1.shp) > click OK. You will notice that a new shapefile was added in the table of contents. 10.Open the attribute table and look at the gridcode values. The gridcode values represent the exceedance value range expressed as a nominal unique value you grouped in step 9.

Specify filename and location 11.You can dissolve your dataset based in the GRIDCODE value. Name your file as Lique_1_dissolved.shp. 12.In the dissolved dataset, create two new fields (text with 50 characters). Start the editing session and edit the attribute table. Manually type the exceedance range values and text label (refer to table F-3 for the Gridcode and the corresponding exceedance range values (old values) and exceedance category (text label) for future reference.

Table F-3. Recommended Exceedance Value Reclassification for liquefaction and earthquake induced landslide Old Values

New Value (GRIDCODE)

Text Label

Lowest observed value- -0.25

High Exceedance

-0.25- -0.15

Moderate Exceedance

-0.15- -0.000001

Low Exceedance

0-(Highest observed positive value)

No Exceedance

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Risk to population estimation

ANNEX G

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Annex G: Risk to population estimation The risk to population seeks to determine the expected impacts of the hazard to the population. This quantitative probabilistic approach expresses the risk as the number of fatalities per year. The results of the risk estimation hopes to provide key decision points to guide and supplement local disaster risk reduction at the local level either through spatial framework, development and investment planning. Risk to Property for individual areas Prepare a barangay administrative map with the required attribute field

1. Prepare a province wide barangay aggregated population density Map. The Barangay aggregated map should have the required minimum attribute information (refer to Table G-1). 2. Encode the necessary values for the PSGC and reference name of the various administrative levels. The standard codes can be derived from the official NSCB 3. Encode the barangay population and average household size. 4. Compute for the Municipal Area in hectares. Select the MunArea field header and use the calculate geometry tool in the attribute table options. Note: Municipal areas should be reflected in all barangay records. This field will be used for the computation of the weighted risk per barangay. 5. Compute for the barangay area in hectares. Select the BrgyArea field header and use the calculate

geometry tool in the attribute table options. 6. Compute for the population density by dividing the BrgyPopn with the BrgyArea. The unit should be the persons per hectare. Note: User can choose to use other units in computing for the area (i.e. square kilometers, square meters, etc) for as long as the proper unit conversion is applied in the succeeding steps Prepare the hazard exposure map 7. Open your hazard map and create a new field for the reclassified hazard susceptibility code. Add a field HazCode (Text, length 10) and reclassify the raw susceptibility levels. Dissolve the dataset based on the HazCode and the raw susceptibility levels (refer to table G-2). The hazard dataset should also indicate areas that are not susceptible to hazards. Ideally, the hazard map should have the same geometry as your administrative map. In general, high susceptible areas will be assigned a HazCode of HSA, moderate susceptible areas shall be assigned a HazCode of MSA, the low susceptible areas shall be assigned a value of LSA and those without hazard shall be assigned as None. There will only be

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Table G-1. Minimum data requirements for population density exposure map for risk to fatality estimation

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Regional Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

RegPSGC

TEXT, Length 50

Region Name

Name of the Region

RegName

TEXT, Length 50

Provincial Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

ProvPSGC

TEXT, Length 50

Province Name

Name of the Province

ProvName

TEXT, Length 50

Municipal/City Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

MunPSGC

TEXT, Length 50

Municipal/City Name

Name of the City or Municipality

MunName

TEXT, Length 50

Municipal Area

The computed area based on the GIS geometry expressed in sq. kilometers or hectares.

MunArea

Float, Precision 20, Scale 8,

Municipal/City Population

Latest Population Count per Municipality or City

MunPopn

Long Integer, Precision 0

Barangay Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

BrgyPSGC

TEXT, Length 50

Barangay Name

Name of the Barangay

BrgyName

TEXT, Length 50

Barangay Area

Computed area of the barangay based on the GIS dataset geometry expressed as square kilometers

BrgyArea

Float, Precision 20, Scale 8,

Barangay Population

Latest Population Count per Barangay

BrgyPopn

Long Integer, Precision 0

Barangay Population Density

Computed population density expressed as population count per square kilometer or hectares. This field will be used to compute the estimated affected population based on the area extent of the hazard affected area.

PopDen

Float, Precision 10, Scale 4,

Barangay Average Household Size

Official statistics on the household size expressed as persons per household. Values can be derived by dividing population count per barangay and the total number of households

AveHHSize

Float, Precision 10, Scale 4,

M ANUAL

FOR

M AINSTREAMING DRR/CCA

P ROVINCIAL D EVELOPMENT

AND

P HYSICAL F RAMEWORK P LANS

Table G-2. Minimum data requirements for hazard map with necessary attribute table data fields

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Hazard Code per susceptibility level in text format

This field will contain the reclassified hazard code in text format (HSA, MSA, LSA, None) based on the raw susceptibility codes of the hazard map.

HazCode

Text, Length 50

Hazard Code per susceptibility level in numerical formal

This field will contain the reclassified hazard numerical code (0, 1, 2 , 3) based on the raw susceptibility codes of the hazard map.

HazCodeNum

Short Integer, Precision 0

a maximum of four unique HazCodes. Note: The HazCode will

Compute for the affected areas per hazard occurrence

depend on the raw indicated susceptibility levels of your hazard map and the type of hazard map that is being used (since there are different map legends that are being used to describe susceptibility for each hazard type). Refer to the various susceptibility levels and the corresponding HazCode values per type of hazard and type of map (READY and Non-READY/Other maps).

9. Open the attribute table of the exposure dataset and add three additional fields to contain the estimated area affected per susceptibility level (refer to table G-3).

8. Union the barangay administrative map with the reclassified hazard map. The resulting dataset should include all the barangay administrative base fields and the additional hazard susceptibility and HazCode fields. Name your union dataset as Exposure_Fatality_(type of hazard)_(yourprovince).

10.Select records falling within the frequent events. In the attribute table option, use the select by attributes and enter the proper selection syntax. Refer to the HazCode field and determine the proper s u s c e p t i b i l i t y l e v e l s t h a t a re considered frequent events (refer to table G-4)

Table G-3. Attribute table data fields for affected area estimation FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Affected areas for frequent events

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in square kilometers

AfAreaFreq

Float, Precision 20, Scale 8,

Affected areas for likely events

This field will contain the affected area for classified likely events computed using the calculate geometry tool. Value is expressed in square kilometers. Area calculation of Likely events shall also include areas falling under the frequent event.

AfAreaLike

Float, Precision 20, Scale 8,

Affected areas for likely events

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in square kilometers. The rare events shall also include areas falling under the frequent and likely events,

AfAreaRare

Float, Precision 20, Scale 8,

M ANUAL

FOR

M AINSTREAMING DRR/CCA

P ROVINCIAL D EVELOPMENT

AND

P HYSICAL F RAMEWORK P LANS

Table G-4. Syntaxes to select the various hazard occurrences. Hazard Occurrence

Selection Syntax (HazCode)

Compute Area for AfArea Field

Frequent Events

"HazCode" = 'HSA'

[AfAreaFreq]

Likely Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA'

[AfAreaLike]

Rare Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA'

[AfAreaRare]

11.Compute for the estimated area affected by frequent events. In the attributes table, select the AfAreaFreq, use the calculate geometry to estimate the area in sq. kilometers or hectares of all selected records. 12.Select all records falling within the likely events. Likely events shall cover both HSA and MSA. Select the [AfAreaLike] field, and compute for the estimated area in sq. kilometers or hectares. 13.Select all records falling within the rare events. Rare events shall also include all affected areas HSA, MSA, and LSA. [AfAreaRare] field and compute for the estimated area in sq. kilometers or hectares.

Compute for the affected population per hazard occurrence 14.Open the attribute table of the exposure dataset and add three additional fields to contain the estimated area affected per hazard occurrence (refer to table G-5). 15.Select the records falling within the various hazard occurrences. Compute for the estimated number of affected population by multiplying the area affected and the population density. 16.Open the attribute table and use the select by attributes tool. Input the proper selection syntax for frequent events "HazCode" = 'HSA'.

Table G-5. Attribute table data fields for affected population estimation FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Affected population for frequent events

This shall contain values of the estimated affected population arising from a frequent event, expressed as number of persons per area.

AffPopFreq

Float, Precision 20, Scale 8,

Affected population for likely events

This shall contain values of the estimated affected population arising from a likely event, expressed as number of persons per area.

AffPopLike

Float, Precision 20, Scale 8,

Affected population for likely events

This shall contain values of the estimated affected population arising from a rare event, expressed as number of persons per area.

AffPopRare

Float, Precision 20, Scale 8,

M ANUAL

FOR

M AINSTREAMING DRR/CCA

P ROVINCIAL D EVELOPMENT

AND

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Table G-6. Selection and field calculator syntax for the various hazard occurrences Hazard Occurrence

Selection Syntax (HazCode)

Field Label

Field Calculator Syntax

Frequent Events

"HazCode" = 'HSA'

AffPopFreq

[PopDen]* [AfAreaFreq]

Likely Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA'

AffPopLike

[PopDen]* [AfAreaLike]

Rare Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA'

AfPopRare

[PopDen]* [AfAreaRare]

17.Select the AffPopFreq field, use the field calculator tool and input the string [PopDen]* [AfAreaFreq]. This will compute the estimated affected population based on the affected area for likely events and the population density. Refer to the selection and field calculation syntaxes for each hazard occurrence and the field calculator computation syntax (refer to table G-6). Input the factor of fatality per hazard occurrence 18.Create three fields that will contain the factor of fatality for the various hazard occurrence. This fields will be used to compute for the estimated fatality per hazard

occurrence. Refer to the table for the standard field heading labels and value formats. 19.Input the corresponding factors in the designated fields. Do a batch table edit by selecting all the records, select the specified hazard occurrence field for factor of fatality, use the field calculator to input the corresponding factors per hazard occurrence. Note: All records will have the same factor of fatality field values for the three hazard occurrences. Estimate the consequence of fatality per hazard occurrence 20.Add three additional fields that will contain the estimated consequence

Table G-7. Attribute table data fields for factor of fatality for each hazard occurrence FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Factor of Fatality for frequent events

Factor indicating the number of ratio of deaths to affected persons for frequent events based on historical records.

FFFreq

Float, Precision 20, Scale 10,

Factor of Fatality for likely events

Factor indicating the number of ratio of deaths to affected persons for likely events based on historical records.

FFLike

Float, Precision 20, Scale 10,

Factor of Fatality for rare events

Factor indicating the number of ratio of deaths to affected persons for rare events based on historical records.

FFRare

Float, Precision 20, Scale 10,

M ANUAL

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M AINSTREAMING DRR/CCA

P ROVINCIAL D EVELOPMENT

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Table G-8. Attribute table data fields for consequence estimation for the various hazard occurrences. FIELD

FIELD HEADER LABEL

Description

TYPE AND FORMAT

Estimated consequence of fatality for frequent events

Estimated number of deaths resulting from a frequent event based on the number of affected persons and a factor of fatality for frequent events.

ConsqFreq

Float, Precision 20, Scale 10,

Estimated consequence of fatality for likely events

Estimated number of deaths resulting from a likely event based on the number of affected persons and a factor of fatality for likely events.

ConsqLike

Float, Precision 20, Scale 10,

Estimated consequence of fatality for rare events

Estimated number of deaths resulting from a rare event based on the number of affected persons and a factor of fatality for rare events.

ConsqRare

Float, Precision 20, Scale 10,

of fatality per hazard occurrence (refer to table G-8 for the recommended field label and value type and format). 21.Compute for the consequence of fatality for frequent events. Select all records falling within the frequent event. Use the select by attributes tool and input the selection syntax for frequent events. Select the ConsqFreq field, use the field calculator tool and input the calculation syntax [AffPopFreq]* [FFFreq]. Refer to table G-9 for the filed calculator syntaxes for the rest of the hazard occurrences. Note that no selection syntax was employed, this procedure will be a simple multiplication of the affected area

field and the factor of fatality for each hazard occurrence. 22.R e p e a t t h e s t e p s f o r t h e computation of consequence for the likely and rare events 23.T h e c o m p u t e d v a l u e s i s t h e estimated number of deaths per area if the event occurs. Fatality Risk Computation 24.Create three additional fields to contain the return periods for the various hazard occurrences. The return periods are the result of the frequency analysis of the hazard being assessed. Use the recommended field labels and value type and format. Refer to the return periods per hazard occurrence for

Table G-9. Syntaxes to select the various hazard occurrences. Hazard Occurrence

Field Label

Field Calculator Syntax

Frequent Events

ConsqFreq

[AffPopFreq]* [FFFreq]

Likely Events

ConsqLike

[AffPopLike]* [FFLike]

Rare Events

ConsqRare

[AffPopRare]* [FFRare]

M ANUAL

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P ROVINCIAL D EVELOPMENT

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Table G-10. Attribute table data fields for risk estimation for the various hazard occurrences. FIELD

FIELD HEADER LABEL

Description

TYPE AND FORMAT

Return period of a frequent event

Return period expressed as the recurrence interval in number of years of a single frequent event. Frequent events are generally low in magnitude with a shorter recurrence interval compared to likely and rare events

RPFreq

Float, Precision 7, scale 4

Return period of a likely event

Return period expressed as the recurrence interval in number of years of a single likely event. Likely events have a longer recurrence interval between events but are of higher magnitude compared to frequent events.

RPLike

Float, Precision 7, scale 4

Return period of a rare event

Return period expressed as the recurrence interval in number of years of a single rare event. Rare events are large magnitude affecting large areas. Rare events have very long recurrence intervals between events but compared to frequent and likely events.

RPRare

Float, Precision 7, scale 4

Incremental risk of frequent and likely events

The incremental risk of the computed likely consequence multiplied by the difference between the reciprocal of return periods of frequent and likely hazard events)

IncRiskFL

Float, Precision 20, scale 10

Incremental risk of likely and rare events

The incremental risk of the computed rare consequence multiplied by the difference between the reciprocal of return periods of likely and rare hazard events)

IncRiskLR

Float, Precision 20, scale 10

Total Incremental Risk

The total risk from the sum of two incremental risks

FatTotRisk

Float, Precision 20, scale 10

the various hazards (refer to table G-10). 25.Create three additional fields that will contain the incremental risks for the frequent-likely event and the likelyrare events. Add the total computed risk which will contain the estimated annualized risk per individual area (refer to table G-10).

26.Populate all records with the corresponding return period value for each hazard occurrence fields. All records will have the same return period value for the the frequent, likely and rare return periods. 27.R e f e r t o t a b l e G - 1 1 f o r t h e incremental risk and total risk estimation computation syntaxes.

Table G-11. Computation of incremental and total annualized risk. Risk Estimation Field

Field Label

Field Calculator Syntax

Incremental risk of frequent and likely events

IncRiskFL

[ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

Incremental risk of likely and rare events

IncRiskLR

[ConsqRare]*((1/ [RpLike])-(1/ [RpRare]))

Total Incremental Risk

FatTotRisk

[IncRiskFL]+ [IncRiskLR]

M ANUAL

FOR

M AINSTREAMING DRR/CCA

Compute for the incremental risk of the frequent and likely events in the IncRiskFL field. Multiply the values in the [ConsqLike] with the difference of the reciprocals of the frequent and likely event return periods using the calculation syntax: [ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

28.Compute for the incremental risk of the likely and rare events in the IncRiskLR field. Multiply the values in the [ConsqRare] with the difference of the reciprocals of the

P ROVINCIAL D EVELOPMENT

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P HYSICAL F RAMEWORK P LANS

likely and rare event return periods using the calculation syntax: [ConsqRare]*((1/ [RpLike])-(1/ [RpRare]))

29.Compute for the total risk in the FatTotRisk field by deriving the sum of the two incremental risks. The calculation syntax is as follows: [IncRiskFL]+ [IncRiskLR]

30.Prepare a risk to population map for individual areas using the recommended symbologies Refer to table G-12).

Table G-12. Recommended symbologies for risk to fatality estimates for individual areas. Level

Range Values

Label

Symbology (RGB)

No Data

No risk to fatality or no hazard data available

255/255/255

> 0.0 to 0.00001

Less than 1 fatality in 100,000 persons per year

255/255/190

0.00001 to 0.0001

1 to 10 fatalities in 100,000 persons per year

255/255/0

0.0001 to 0.001

1 to 10 fatalities in 10,000 persons per year

255/181/189

0.001 to 0.01

1 to 10 fatalities in 1,000 persons per year

197/0/255

0.01 to <highest observed value>

1 to <max> fatalities in 100 persons per year

255/0/0

Malimono

745

San Francisco

982

939

1052

701

Tubod

Socorro

Caye Island

114

Alegria

Mahaba Island

457

945

AGUSAN DEL NORTE 1128

975

366

209 Bonga Island

Masapelid Island, Placer

Bacuag

Dinago Island

Opong Island

346 Hinatuan Island

Gigaquit

Lapinigan Island

Island, Gigaquit

Cabgan Island

Nagubat Island

Talavera Island 185

548

334

Ondona Island Masapelid Island, Tagana-an

Maanoc Island

Bayagnan Island

Sugbu Island

Nonoc Island

196

1187

854

1168

1170

Aling Island

Claver

Halian Island

360

405

SURIGAO DEL SUR

Amaga Island

180

271

Poneas Island

259

159

245 282

225

Bucas Grande Island

137

242

274

207

183

Casulian Island

183East Bucas Island, Socorro

Pilar

225

San Isidro

Burgos

Bancuyo Island

Abanay Island

Dapa

San Benito 204

Middle Bucas Island 291

Tona Island, Del Carmen

Laonan Island

Poneas Island, Del Carmen 303

Kangbangyo Island

Cawhagan Island Megancub Island

Poneas Island, San Benito

Kangun Island

199

Sta. Monica

Date Published: Month 2011

Mamon Island Antokon Island

Lajanosa Island

Daco Island

Anajauan Island

Gen. Luna

Island, Pilar

Provincial Boundaries Road Network Spot Elevation Rivers

Provincial Government of Surigao del Norte in coordination with the National Economic and Development Authority-Region 1 (NEDA-R1) under the Integrating Disaster Risk Reduction and Climate Change Adaptation (DRR-

Map prepared by:

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale

Map Sources:

Less than 1 fatality in 100,000 persons per year 1 to 10 fatalities in 100,000 persons per year 1 to 10 fatalities in 10,000 persons per year 1 to 10 fatalities in 1,000 persons per year 1 to 13 fatalities in 100 persons per year

RISK TO POPULATION

µ 0

SPHEROID............................................................. CLARKE 1866 PROJECTION.........................UNIVERSAL TRANSVERSE MERCATOR VERTICAL DATUM............................................. MEAN SEA LEVEL HORIZONTAL DATUM........................................... LUZON DATUM

BASE DATA LEGEND

Kilometers

1:315,000

REGION 13- CARAGA

PROVINCE OF SURIGAO DEL NORTE

P HYSICAL F RAMEWORK P LANS

661

423

335

Santa Monica

Awasan Island

333

Lamagon Island Island

Rasa Island

Taganaan

313

Load Island

172

Hanigad Island

SURIGAO DEL NORTE

694

134 Sibale Island Island

Kabo Island

Placer

Mangrove Island

Surigao City

Mainit

Sison

303

West Cabalian Island

Dinagat

Cagdianao

490

IN INDIVIDUAL AREA S

RISK TO POPULATION FROM RAIN INDUCED LANDSLIDES

AND

395

Lingig

Capaquian Island

Hikdop Island

Danaon Island

Sibanac Island

San Jose

126°0'0"E

P ROVINCIAL D EVELOPMENT

139

170

631

540

Unib Island

303

M AINSTREAMING DRR/CCA

Sumilon Island

276

Basilisa (Rizal)

125°30'0"E

Kotkot Island, Basilisa

Figure G-1 Sample risk to population from rain induced landslide map for individual areas, Province of Surigao del Norte, CARAGA Region.

10°0'0"N

FOR

9°30'0"N

M ANUAL

FOR

M AINSTREAMING DRR/CCA

Compute for the municipal level risk Compute for the barangay level weighted risk to fatality 31.Dissolve your dataset down to the barangay level using the dissolve tool. Dissolve based on the RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName, MunArea,, MunPopn, BrgyPSGC, BrgyName, BrgyArea, BrgyPopn, PopDen, and AveHHSize as the dissolve fields. Create statistical fields by getting the sum of the AfAreaFreq, AfAreaLike, AfAreaRare, AffPopFreq, AffPopLike, AffPopRare. The minimum value for the FFFreq, FFLike, FFRare, RpFreq, RpLike, RpRare fields. Sum of the ConsqFreq, ConsqLike, ConsqRare, IncRiskFL, IncRiskLR, and FatTotRisk fields (refer to table G-13). Save your dataset as Brgy_RiskFatality_(hazard type)_ (your province). 32.Create a weighted barangay risk (WRisk, float, precision=20 and scale=10) 33.Compute for the weighted risk per barangay by multiplying the total risk field with the barangay land area. The computation syntax for the WRisk field is as follows: [SUM_FatTot]* [BrgyArea]

P ROVINCIAL D EVELOPMENT

AND

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Compute for the municipal level risk to fatality 34.Further dissolve the dataset to the municipal level. Only retain the RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName, and MunArea fields. Include a statistical field on sum of the Wrisk. Make sure that the municipal land area is selected as a dissolve field. This will be used in the computation of the municipal risk. Save your file as Municipal_RiskFatality_(hazard type)_(your province) 35.Open the dissolved dataset. Create a field to contain the computed municipal risk (MunRisk, float, precision=20 and scale=10). 36.Compute for the municipal risk by dividing the municipal aggregated weighted risk with the total municipal area. The computation for the MunRisk is as follows: [SUM_WRisk]/ [MunArea] 37.C r e a t e a M u n i c i p a l L e v e l aggregated risk to fatality map using the recommended symbologies (refer to table G-14 and figure G-2). The map generated is a municipal aggregated risk to fatality estimate where the weighted risk are summed and divided by the municipal land area. The values represent the total annualized risk to fatality per municipality within a province. The municipal level risk will be used for the purposes of risk prioritization.

M ANUAL

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Table G-13. Dissolve and statistical dissolve fields for municipal level data aggregation. Field

Field Description

Statistical dissolve type

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

MunArea

The computed area based on the GIS geometry expressed in sq. kilometers or hectares.

Dissolve Field

MunPopn

Latest Population Count per Municipality or City

Dissolve Field

BrgyPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

BrgyName

Name of the Barangay

Dissolve Field

BrgyArea

Computed area of the barangay based on the GIS dataset geometry expressed as square kilometers

Dissolve Field

BrgyPopn

Latest Population Count per Barangay

Dissolve Field

PopDen

Dissolve Field

AveHHSize

Official statistics on the household size expressed as persons per household. Values can be derived by dividing population count per barangay and the total number of households

Dissolve Field

AfAreaFreq

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in square kilometers

Sum

AfAreaLike

Sum

AfAreaRare

Sum

AffPopFreq

This shall contain values of the estimated affected population arising from a frequent event, expressed as number of persons per area unit.

Sum

AffPopLike

This shall contain values of the estimated affected population arising from a likely event, expressed as number of persons per area unit.

Sum

AffPopRare

This shall contain values of the estimated affected population arising from a rare event, expressed as number of persons per area unit.

Sum

FFFreq

Factor indicating the number of ratio of deaths to affected persons for frequent events based on historical records.

Min

FFLike

Factor indicating the number of ratio of deaths to affected persons for likely events based on historical records.

Min

FFRare

Factor indicating the number of ratio of deaths to affected persons for rare events based on historical records.

Min

ConsqFreq

Estimated number of deaths resulting from a frequent event based on the number of affected persons and a factor of fatality for frequent events.

Sum

ConsqLike

Estimated number of deaths resulting from a likely event based on the number of affected persons and a factor of fatality for likely events.

Sum

ConsqRare

Estimated number of deaths resulting from a rare event based on the number of affected persons and a factor of fatality for rare events.

Sum

RpFreq

Min

RpLike

Min

RpRare

Min

IncRiskFL

The incremental risk of the computed likely consequence multiplied by the difference between the reciprocal of return periods of frequent and likely hazard events)

Sum

IncRiskLR

The incremental risk of the computed rare consequence multiplied by the difference between the reciprocal of return periods of likely and rare hazard events)

Sum

FatTotRisk

The total risk from the sum of two incremental risks

Sum

M ANUAL

FOR

M AINSTREAMING DRR/CCA

P ROVINCIAL D EVELOPMENT

AND

P HYSICAL F RAMEWORK P LANS

Table G-14. Recommended symbologies for risk to fatality estimates for municipal aggregated areas. Level

Range Values

Label

Symbology (RGB)

No Data

No risk to fatality or no hazard data available

255/255/255

> 0.0 to 0.00001

Less than 1 fatality in 100,000 persons per year

255/255/190

0.00001 to 0.0001

1 to 10 fatalities in 100,000 persons per year

0.0001 to 0.001

1 to 10 fatalities in 10,000 persons per year

255/181/189

0.001 to 0.01

1 to 10 fatalities in 1,000 persons per year

197/0/255

0.01 to <highest observed value>

1 to <max> fatalities in 100 persons per year

255/255/0

255/0/0

Malimono

745

San Francisco

982

939

1052

701

Tubod

Socorro

Caye Island

Mahaba Island

114

Alegria

975

366

945

AGUSAN DEL NORTE 1128

Bacuag

457

209 Bonga Island

Dinago Island Masapelid Island, Placer

Opong Island

346 Hinatuan Island

Gigaquit

Lapinigan Island

Island, Gigaquit

Cabgan Island

Nagubat Island

Talavera Island 185

548

334

Ondona Island Masapelid Island, Tagana-an

Maanoc Island

Bayagnan Island

Sugbu Island

Nonoc Island

196

1187

854

1168

1170

Aling Island

Claver

Halian Island

360

405

SURIGAO DEL SUR

Amaga Island

180

271

Poneas Island

259

159

245 282

225

Bucas Grande Island

137

242

274

207

183

Casulian Island

183East Bucas Island, Socorro

Pilar

225

San Isidro

Burgos

Bancuyo Island

Abanay Island

Dapa

San Benito 204

Middle Bucas Island 291

Tona Island, Del Carmen

Laonan Island

Poneas Island, Del Carmen 303

Kangbangyo Island

Cawhagan Island Megancub Island

Poneas Island, San Benito

Kangun Island

199

Sta. Monica

Date Published: Month 2011

Mamon Island Antokon Island

Lajanosa Island

Daco Island

Anajauan Island

Gen. Luna

Island, Pilar

Provincial Boundaries Road Network Spot Elevation Rivers

Map prepared by:

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale

Map Sources:

RISK TO POPULATION

µ 0

BASE DATA LEGEND

Kilometers

1:315,000

REGION 13- CARAGA

PROVINCE OF SURIGAO DEL NORTE

P HYSICAL F RAMEWORK P LANS

661

423

335

Santa Monica

Awasan Island

333

Lamagon Island Island

Rasa Island

Taganaan

313

Load Island

172

Hanigad Island

SURIGAO DEL NORTE

694

134 Sibale Island Island

Kabo Island

Placer

Mangrove Island

Surigao City

Mainit

Sison

303

West Cabalian Island

Dinagat

Cagdianao

490

AGGREGATED TO MUNICIPAL/CITY LEVEL

RISK TO POPULATION FROM RAIN INDUCED LANDSLIDES

AND

395

Lingig

Capaquian Island

Hikdop Island

Danaon Island

Sibanac Island

San Jose

126°0'0"E

P ROVINCIAL D EVELOPMENT

139

170

631

540

Unib Island

303

M AINSTREAMING DRR/CCA

Sumilon Island

276

Basilisa (Rizal)

125°30'0"E

Kotkot Island, Basilisa

Figure G-1 Sample municipal level risk to population from rain induced landslide map, Province of Surigao del Norte, CARAGA Region.

10°0'0"N

FOR

9°30'0"N

M ANUAL

FOR

M AINSTREAMING DRR/CCA

Municipal Risk to Fatality Prioritization

P ROVINCIAL D EVELOPMENT

AND

P HYSICAL F RAMEWORK P LANS

Precision 0) RPrioFaTex (Text, length 50)

Depending on the municipal aggregated risk estimates, each municipality will be categorized as either priority, high priority or urgent in ter ms of risk mitigation where intervention measures should be implemented. 38.Add two fields that will contain the risk prioritization categories. Label the field RPrioFaNum, (Short Integer,

39.In the select by attributes tool, select the value ranges in MunRisk field using the selection syntax. For the selected records per value range, type the corresponding risk prioritization index. 40.Create a municipal risk to fatality prioritization index map for your hazard using the prescribed map symbologies.

Table G-15. Recommended symbologies for risk prioritization. Risk Levels Descriptio n

High risk to Very High risk

Moderate risk

Municipal Risk

GIS Selection Syntax

One or more in 100 persons per year

"MunRisk" >= 0.01

less than 1 in 100 to 1 in 100,000 persons per year

"MunRisk" < 0.01 AND "MunRisk" >= 0.00001

Prioritization Index Field RiskPrio

Symbology (RGB)

Acceptability and action needed

RiskText

Urgent

255/0/0

Highly intolerable. Extensive detailed investigation needed and implementation of options essential to reduce risk to acceptable levels; may be too expensive and not practicable. Moderately intolerable. Detailed investigation, planning and implementation of options required to reduce risk to tolerable levels.

Very Low risk to Low risk

Less than 1 in 100,000 persons per year

"MunRisk" < 0.00001 AND "MunRisk" >0

No hazard data available

n/a

"MunRisk" =0

High Priority

Low Priority

197/0/255

Intolerable. Further investigation, planning and implementation of options required to reduce risk to acceptable levels.

Tolerable, provided plan is implemented to maintain or reduce risks. May require investigation and planning of options.

255/255/0 Usually accepted. Treatment requirements and responsibility to be defined to maintain or reduce risk.

No Data

255/255/255

Unsurveyed areas in terms of hazard susceptibility or hazard is not present in the areas.

Malimono

745

San Francisco

982

939

1052

701

Socorro

Caye Island

Opong Island

Mahaba Island

114

Alegria

975

366

945

AGUSAN DEL NORTE 1128

Bacuag

457

209 Bonga Island

Dinago Island Masapelid Island, Placer

346 Hinatuan Island

Gigaquit

Lapinigan Island

Island, Gigaquit

Cabgan Island

Nagubat Island

Talavera Island 185

548

334

Ondona Island Masapelid Island, Tagana-an

Maanoc Island

Bayagnan Island

Sugbu Island

Nonoc Island

196

1187

854

1168

1170

Aling Island

Claver

Halian Island

360

405

SURIGAO DEL SUR

Amaga Island

180

271

Poneas Island

259

159

245 282

225

Bucas Grande Island

137

242

274

207

183

Casulian Island

183East Bucas Island, Socorro

Pilar

225

San Isidro

Burgos

Bancuyo Island

Abanay Island

Dapa

San Benito 204

Middle Bucas Island 291

Tona Island, Del Carmen

Laonan Island

Poneas Island, Del Carmen 303

Kangbangyo Island

Cawhagan Island Megancub Island

Poneas Island, San Benito

Kangun Island

199

Sta. Monica

Date Published: Month 2011

Mamon Island Antokon Island

Lajanosa Island

Daco Island

Anajauan Island

Gen. Luna

Island, Pilar

10°0'0"N

Provincial Boundaries Road Network Spot Elevation Rivers

Map prepared by:

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale

Map Sources:

No Data Low Priority High Priority Urgent

PRIORITY RANKING

µ 0

BASE DATA LEGEND

Kilometers

1:315,000

REGION 13- CARAGA

PROVINCE OF SURIGAO DEL NORTE

P HYSICAL F RAMEWORK P LANS

661

Tubod

335

Santa Monica

Awasan Island

333

Lamagon Island Island

Rasa Island

SURIGAO DEL NORTE

694

423

172

Hanigad Island

Taganaan

313

Load Island

Kabo Island

Placer

Mangrove Island

Surigao City

Mainit

Sison

303

134

Sibale Island Island

West Cabalian Island

Dinagat

Cagdianao

490

AGGREGATED TO MUNICIPAL/CITY LEVEL

RISK TO POPULATION FROM RAIN INDUCED LANDSLIDES

AND

395

Lingig

Capaquian Island

Hikdop Island

Danaon Island

Sibanac Island

San Jose

126°0'0"E

P ROVINCIAL D EVELOPMENT

139

170

631

540

Unib Island

303

M AINSTREAMING DRR/CCA

Sumilon Island

276

Basilisa (Rizal)

125°30'0"E

Kotkot Island, Basilisa

Figure G-1 Sample municipal level risk to population from rain induced landslide map, Province of Surigao del Norte, CARAGA Region.

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Risk to property estimation

ANNEX H

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Annex H: Risk to property estimation The risk to property estimation seeks to determine the annualized risk to agriculture, fisheries and forestry (AFF) and urban assets of the municipality and province. While AFF assets are represented as a polygon feature, urban assets are made up of built-up areas, critical point facilities and lifeline infrastructure and are represented as polygon, point and line feature types respectively. Prioritization will depend on the ratio of the total assets and the estimated risk. Two estimates will be derived namely, risk to AFF and urban assets. Risk estimation for Built-up and AFF areas This covers the risk estimation for builtup and AFF areas using a polygon based feature type map. The estimates for built-up areas will be combined to the estimates derived from the critical point facilities and lifeline utilities to determine the total urban risk. Prepare a Property Inventory Exposure Map Gather map data pertaining to land cover, built-up area, agriculture/crop production zones, and forest zones. These can be gathered from national agencies such as NAMRIA, DENR-FMB, and the Department of Agriculture. These can also be sourced from regional and provincial sources. The property inventory map will serve as the exposure map to deter mine the elements at risk in terms of risk to property. 1. A good source good source of map data identifying the extent of built-up areas are NAMRIA land cover maps.

These maps, however, may not n e c e s s a r i l y re f l e c t t h e l a t e s t information pertaining to the extent of the built-up zones. In such cases local additional field surveys can be conducted to supplement out-dated data. 2. Similarly, agricultural production lands can also be derived from land cover maps. The classification of agricultural lands are limited to cultivated perennial, cultivated annual crop lands and fish ponds areas. Areas indicated as crop production areas do not indicate the type of crop planted. In such cases, additional input maps can be used to delineate agricultural areas by type of crop which is important in assessing provincial/municipal level risk. 3. Forest production and protection areas can be derived from the Department of Environment and Natural Resources-Forest Management Bureau (DENR-FMB). Forest production areas cover Community Based Forest Management (CBFM) areas, those

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Table H-1. Minimum data requirements for property exposure dataset.

FIELD

FIELD HEADER LABEL

DESCRIPTION

TYPE AND FORMAT

Reclassified land cover categories

This field will contain the reclassified land use categories which will be used for the selection syntaxes.

Prop_type

TEXT, Length 50

Crop type for agriculture and forestry production areas

This field will contain the type of crop (i.e. rice, corn, coconut, etc)

Crop_Type

TEXT, Length 50

Unit Cost

This field shall contain the replacement cost per property type expressed as unit cost per hectare

UnitCost

Float, Precision 20, Scale 2,

covered by Active Timber Licenses, Integrated Forest Management Agreement/Industrial Tree Plantation Lease Agreement (IFMA/ITPLA), Tree Farm and Agro-Forestry Farm Leases, Socialized Industrial Forest Management Agreements, Private Forest Development Agreements, Forest Land Grazing Lease Agreements and Permits and other forest utilization agreements. These are mostly documented with clearly defined boundaries which can be used to subdivide the forest production zones of a particular province. Valuing protected forests, protected sanctuaries, or watersheds is difficult. Nonetheless, putting a value to protected areas emphasizes the need to protect and to restore them into their original state after a disaster. 4. There will be instances that several maps should be combined to generate a property inventory map which will serve as elements at risk to property damage. It has to be noted that planners need to delineate areas where the cost of replacement can be indicated per type of land use. 5. G i v e n t h e a b o v e m e n t i o n e d considerations, prepare a property

inventory map delineating the various categories of actual resource use of land in the province. Ideally, all land use categories should have a corresponding cost of replacement. For the purposes of risk estimation, at the minimum, include land use categories delineating the built-up areas (regardless of type of use), production areas such as crop production areas by type of crop, fish pond areas. Forest production and protection areas can also be included assuming that replacement costs can be assigned. 6. Consult the mandated agencies when determining the unit costs per type of crop or forest production zones (DA, DENR-FMB). Built up area unit cost are based on the total cumulative floor area and assessed value based on the municipal aggregated inventory data of NSO. 7. Add two additional fields that will contain the revised property type codes, type of crop (for agricultural lands) and the replacement cost. Unit cost should be expressed as replacement cost per hectare (Refer to table H-1)

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Table H-2. Sample property exposure attribute table. Land_Use

Prop_type

Unit_Cost per Hectare (Php)

Crop_Type

Agricultural (Area 1)

AFF

Rice

30,486

Agricultural (Area 2)

AFF

Corn

17,112

Agricultural (Area 3)

AFF

Coffee

25,228

Agricultural (Area 4)

AFF

Mango

60,038

Protection Forest

AFF

Protection Forest

33,267

Production Forest

AFF

Production Forest

43,146

Fisheries

AFF

Milk Fish

32,843

Built-up

Built up areas

Not applicable

77,050,000

Other Land Uses1

Unclassified

Not applicable

1Assign

other land use categories as unclassified with a replacement cost of zero if such land uses do not have a pre-defined replacement cost.

8. A sample property exposure and unit cost attribute table is presented below limited to agricultural and forest lands by type of crop or forest type and built-up areas (refer to table H-2). 9. In assigning Prop_type, label all indicated built up zones as “Built-up areas”. Label all indicated agricultural, fisheries (inland), and forest areas as ”AFF”. Label all other land uses where the unit cost can not be established as ”Other land uses” Prepare a Municipal Administrative Map 10.Prepare a municipal administrative boundary map. The Municipal Boundary map should have the following minimum attribute information (refer to table H-3).

11.The municipal administrative map will contain key data for estimating risk including the total floor area, and total residential floor area. The risk to built up areas will be based on the total floor area and will be used in estimating the ratio between the documented total floor area estimates and the mapped out builtup areas. The TFA to built-up ratio will be discussed the succeeding steps. Prepare the municipal aggregated exposure map 12.First do a union of the municipal administrative map, property map. Save your file as Muni_Prop1. 13.Dissolve the dataset based on RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName, M u n A re a , T FA , P ro p _ t y p e ,

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Table H-3. Minimum data requirements for municipal administrative map.

FIELD

FIELD HEADER LABEL

DESCRIPTION

TYPE AND FORMAT

Regional Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

RegPSGC

Long Integer, Precision 0

Region Name

Name of the Region

RegName

TEXT, Length 50

Provincial Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

ProvPSGC

Long Integer, Precision 0

Province Name

Name of the Province

ProvName

TEXT, Length 50

Municipal/City Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

MunPSGC

Long Integer, Precision 0

Municipal/City Name

Name of the City or Municipality

MunName

TEXT, Length 50

Municipal Area

The computed area based on the GIS geometry expressed in hectares

MunArea

Float, Precision 20, Scale 2,

Total Floor Area

Total floor area per municipality expressed as square meters

TFA

Float, Precision 20, Scale 2,

Crop_type Unit Cost and save the file as Muni_prop_2.

area per land use at the municipal level (refer to table H-4).

14.Add two fields that will contain the total estimated floor area per built up zone and the initial statistics on the

15.Derive the area per land use category in the LUArea field using the calculate geometry tool.

Table H-4. Attribute table data fields for municipal aggregated land use and TFA to built-up estimates.

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Area per land use per municipality

Initial updated statistics on the area per land use per municipality in terms of hectares.

LUArea

Float, Precision 20, Scale 5,

Ratio of total floor area to total built-up land area

Estimated total floor area in hectares to every hectare of built up area. This will serve as a multiplier to determine the total cost affected given the derived affected built up area.

TFAtoBU

Float, Precision 20, Scale 5,

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16.Compute for the ratio between the total floor area and the estimated area extent of the built up area. This will serve as a multiplier when computing for the actual floor area (converted to hectares) affected by hazards when the area of the builtup zones are derived in the succeeding steps. First select all built-up areas in the Prop_type field using the selection syntax: "Prop_Type" <> 'Built-up areas' 17.In the TFAtoBU field, calculate for the ratio by using the following computation syntax: (([TFA2007]/10000))/[LUArea]

18.You can use this map as your municipal level base layer property exposure map which can be used to various hazard risk estimation. Prepare the hazard exposure map 19.Open your hazard map and create a new field for the reclassified hazard susceptibility codes. Add a field HazCode (Text, length 10) and reclassify the raw susceptibility levels. Dissolve the dataset based on the HazCode and the raw susceptibility levels (refer to table G-2). The hazard dataset should also indicate areas that are not susceptible to hazards. Ideally, the

Important Note:

The GIS derived area of built up zones based on map extent is not the same as the tabular floor area estimates. TFA to built-up ratio is expressed as the total floor area for every unit of mapped out built-up area. In general mapped out built-up areas include open spaces, roads, and parks and open vacant lots. For illustration purposes, a certain municipality has a total document total floor area of 1,500,000 square meters or 150 hectares, and based on the map, it has a total built-up area of 100 hectares. This means that for every hectare of mapped out built up area, there are 15,000 square meters or 1.5 hectares of actual floor area. When deriving the affected area per hazard occurrence, area affected are based on the size of the built-up. Multiplying the affected area with the TFA to built-up ensures that only the actual floor area will be accounted during the consequence estimation and excludes the area of open spaces, roads and vacant lots included in the mapped out builtup area. Furthermore, there will be certain municipalities where the built up to TFA ratio will return null values, this is because there were no mapped built up zones for that particular municipality. It is important that users reflect the updated built-up zones for each municipality. This operation is not applicable for agriculture or forest land estimation.

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Table H-5. Attribute table data fields for hazard maps

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Hazard Code per susceptibility level in text format

This field will contain the reclassified hazard code in text format (HSA, MSA, LSA, None) based on the raw susceptibility codes of the hazard map.

HazCode

Text, Length 50

Hazard Code per susceptibility level in numerical formal

This field will contain the reclassified hazard numerical code (0, 1, 2 , 3) based on the raw susceptibility codes of the hazard map.

HazCodeNum

Short Integer, Precision 0

hazard map should have the same geometry as your administrative map. In general, high susceptible areas will be assigned a HazCode of HSA, moderate susceptible areas shall be assigned a HazCode of MSA, the low susceptible areas shall be assigned a value of LSA and those without hazard shall be assigned as None. There will only be a maximum of four unique HazCodes (refer to table H-5). Note: The HazCode will depend on the raw indicated susceptibility levels of your hazard map and the type of hazard map that is being used (since there are different map legends that are being used to describe susceptibility for each hazard type). Refer to the various susceptibility levels and the corresponding HazCode values per type of hazard and type of map (READY and Non-READY/Other maps).

20.Union the municipal base layer with the hazard map to create the hazard exposure dataset. Save your file a Exposure_Property_(Hazard Type)_ (your province). Compute for the affected areas for each hazard occurrence Calculation of the affected areas for non-built up areas (agriculture, forest) will be based on the derived areas in GIS. For built up areas, it will be based

on the derived areas multiplied by the built-up area to Total Floor Area Ratio. 21.Open the attribute table of the exposure dataset and add four additional fields to determine the estimated area of the polygon record and the estimated area affected per susceptibility level. 22.Compute the for the area per polygon (all records) by selecting the CompuArea field, use the calculate geometry to derive the estimated area in hectares. 23.Populate the area affected fields. The computation of the affected area is different for AFF and built-up. AFF affected area will be based on the computed mapped out area in GIS while the built-up will be based on the computed area in GIS multiplied by the TFAtoBU ratio. 24.Select records falling within the frequent events (HSA) and with property that is not built-up area in type. In the attribute table option, use the select by attributes and enter the proper selection syntax (Refer to the HazCode field and determine the proper susceptibility levels that are considered frequent events).Your selection syntax should be as follows:

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Table H-5. Attribute table data fields for hazard maps

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Computed Area

The total extent of the area affected based on the land cover map.

CompuArea

Float, Precision 20, Scale 5,

Affected areas for frequent events

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in hectares

AfAreaFreq

Float, Precision 20, Scale 5,

Affected areas for likely events

This field will contain the affected area for classified likely events computed using the calculate geometry tool. Value is expressed in hectares. Area calculation of Likely events shall also include areas falling under the frequent event.

AfAreaLike

Float, Precision 20, Scale 5,

Affected areas for rare events

This field will contain the affected area for classified rare events computed using the calculate geometry tool. Value is expressed in hectares. The rare events shall also include areas falling under the frequent and likely events,

AfAreaRare

Float, Precision 20, Scale 5,

"Prop_Type" <> 'Built-up areas' AND "HazCode" = 'HSA'

25.Compute for the estimated area affected by frequent events for nonbuilt up areas. In the attributes table, select the AfAreaFreq, copy the values in the CompuArea field. 26.Select all records falling within the likely events for non-built up areas. Likely events shall cover both HSA and MSA. Select the [AfAreaLike] field, and copy the values in the CompuArea field. Your selection syntax should be as follows: "Prop_Type" <> 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA')

27.Select all records falling within the likely events for non-built up areas. Likely events shall cover both HSA and MSA. Select the [AfAreaLike] field, and copy the values in the CompuArea field. Your selection syntax should be as follows:

"Prop_Type" <> 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA' )

28.Compute for the affected areas for built-up areas. First select the frequent events affecting built up areas. Input the selection syntax to select the proper records. Your syntax should be as follows: "Prop_Type" = 'Built-up areas' AND "HazCode" = 'HSA'

29.Compute for the frequent events affecting built up areas. Computing the affected area is based from the GIS derived map extent of the built up per polygon and the total floor area to built-up ratio. The addition of the TFAtoBU string is used to determine the affected floor area based on the derived area of built up areas per record. Go to the AfAreaFreq field and input the calculation syntax: [CompuArea]*[TFAtoBU]

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Table H-6. Selection and calculation syntaxes for the computation of area affected for built-up and non built-up areas. Hazard Occurrence

Compute Area for AfArea Field

Selection Syntax (HazCode)

Field Calculator Syntax

Non-Built up Areas Frequent Events

"Prop_Type" <> 'Built-up areas' AND "HazCode" = 'HSA'

[AfAreaFreq]

[CompuArea]

Likely Events

"Prop_Type" <> 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA')

[AfAreaLike]

[CompuArea]

Rare Events

"Prop_Type" <> 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA' )

[AfAreaRare]

[CompuArea]

Frequent Events

"Prop_Type" = 'Built-up areas' AND "HazCode" = 'HSA'

[AfAreaFreq]

[CompuArea]* [TFAtoBU]

Likely Events

"Prop_Type" = 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA')

[AfAreaLike]

[CompuArea]* [TFAtoBU]

Rare Events

"Prop_Type" = 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA' )

[AfAreaRare]

[CompuArea]* [TFAtoBU]

Built-up Areas

30.Select the likely events affecting built up areas. Input the selection syntax to select the proper records. Your syntax should be as follows: "Prop_Type" = 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA')

31.Go to the AfAreaLike field input the calculation syntax: [CompuArea]* [TFAtoBU]

32.Select the rare events affecting built up areas. Input the selection syntax to select the proper records. Your syntax should be as follows: "Prop_Type" = 'Built-up areas' AND ("HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA' )

33.Go to the AfAreaRare field input the calculation syntax:

[CompuArea]* [TFAtoBU]

34.Values in the three fields represent the estimated affected area per record. This field will be multiplied by estimated unit cost and factor of damage to derive the consequence per hazard occurrence. Input the factor of damage for each hazard occurrence 35.Add three additional fields that will contain the factor of damage per hazard occurrence (refer to table H-7). Note that the factors of damage will be different for built-up areas and non-built up areas (AFF). 36.First input the factor of damage for built-up areas. Use the select by attributes tool, and input the selection syntax:

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Table H-7. Attribute table data fields for factor of damage for each hazard occurrence FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Factor for property damage for frequent events

Factor indicating the damage ratio to property for frequent events based on historical records.

FDFreq

Float, Precision 20, Scale 10,

Factor for property damage for likely events

Factor indicating the damage ratio to property for likely events based on historical records.

FDLike

Float, Precision 20, Scale 10,

Factor for property damage for likely events

Factor indicating the damage ratio to property for rare events based on historical records.

FDRare

Float, Precision 20, Scale 10,

Selection syntax for Built-up areas: "Prop_Type" = 'Built-up areas'

Selection syntax for Built-up areas: "Prop_Type" <> 'Built-up areas'

37.Use the field calculator tool and make a batch edit to populate the factor of damage fields for frequent, likely and rare events.

39.Use the field calculator tool and make a batch edit to populate the factor of damage fields for frequent, likely and rare events.

38.Now input the factor of damage for non built-up areas. Use the select by attributes tool, and input the selection syntax:

Compute for consequence in terms of property damage 40.Add three additional fields that will contain the factor of damage per

Table H-8. Attribute table data fields for consequence estimation for each hazard occurrence FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Estimated consequence of property damage for frequent events

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for frequent events.

ConsqFreq

Float, Precision 20, Scale 2,

Estimated consequence of property damage for likely events

Estimated property damage resulting from a likely event based on the extent of affected area and the factor of property damage for likely events.

ConsqLike

Float, Precision 20, Scale 2,

Estimated consequence of property damage for rare events

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for rare events.

ConsqRare

Float, Precision 20, Scale 2,

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Table H-8. Attribute table data fields for consequence estimation for each hazard occurrence Consequence

Field

Field computation syntax

Estimated consequence to property damage for frequent events

ConsqFreq

[UnitCost]* [AfAreaFreq]* [FDFreq]

Estimated consequence to property damage for likely events

ConsqLike

[UnitCost]* [AfAreaLike]* [FDLike]

Estimated consequence to property damage for rare events

ConsqRare

[UnitCost]* [AfAreaRare]* [FDRare]

hazard occurrence. (Refer to table H-8). 41.Compute for the consequence in terms of property damage for frequent events. Select the ConsqFreq field, use the field calculator tool and input the calculation syntax: [UnitCost]*[AfAreaFreq]*[FDFreq] Note: No selection syntax was employed, this procedure will be a simple multiplication of the affected area field and the factor of fatality for each hazard occurrence. 42.S i m i l a r l y, c o m p u t e f o r t h e consequence in terms property damage for likely events by selecting the ConsqLike field, in the field calculator, input the calculation syntax: [UnitCost]*[AfAreaLike]* [FDLike]. 43.C o m p u t e t h e r a r e e v e n t consequence by selecting the ConsqLRare field and inputing the syntax : [UnitCost]*[AfAreaLRare]*[FDRare] 44.By this this you have computed the consequence in terms of the cost to p ro p e r t y d a m a g e p e r h a z a rd occurrence (refer to table H-9 for the

calculation syntaxes for each hazard occurrence). Risk computation for built-up and AFF areas 45.Create the following additional fields to contain the return periods for the various hazard occurrences, incremental risks, total property risk, and the separate risk for AFF and built-up areas. . Use the recommended field labels and value type and format. Refer to the return periods per hazard occurrence for the various hazards (refer to table H-9). 46.Populate all records using the field calculator with the corresponding return period value for each hazard occurrence fields. All records will have the same return period value for the the frequent, likely and rare return period fields. 47.Compute for the incremental risk of the frequent and likely events in the IncRiskFL field. Multiply the values in the [ConsqLike] with the difference of the reciprocals of the frequent and likely event return periods using the calculation syntax: [ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

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Table H-9. Attribute table data fields for risk estimation for the various hazard occurrences. FIELD

FIELD HEADER LABEL

Description

TYPE AND FORMAT

Return period of a frequent event

RPFreq

Float, Precision 7 scale 4

Return period of a likely event

RPLike

Float, Precision 7 scale 4

Return period of a rare event

RPRare

Float, Precision 7 scale 4

Incremental risk of frequent and likely events

The incremental risk of the computed likely consequence multiplied by the difference between the reciprocal of return periods of frequent and likely hazard events)

IncRiskFL

Float, Precision 20, Scale 2

Incremental risk of likely and rare events

The incremental risk of the computed rare consequence multiplied by the difference between the reciprocal of return periods of likely and rare hazard events)

IncRiskLR

Float, Precision 20, Scale 2

Total Risk

The total risk for both agriculture, fisheries forest and built-up land uses. These will only be used for the preparation of the risk to property map.

TotRisk

Float, Precision 20, Scale 2

Total Risk for agriculture, fisheries and forest land uses

The total risk from the sum of two incremental risks for agriculture, fisheries and forest land uses

AFFTotRisk

Float, Precision 20, Scale 2

Total Risk for Urban areas

The total risk from the sum of two incremental risks for built-up areas

BUTotRisk

Float, Precision 20, Scale 2

48.Compute for the incremental risk of the likely and rare events in the IncRiskLR field. Multiply the values in the [ConsqRare] field with the difference of the reciprocals of the

likely and rare event return periods using the calculation syntax: [ConsqRare]*((1/ [RpLike])-(1/ [RpRare]))

Table H-10. Incremental risk computation Consequence

Field

Field computation syntax

Incremental risk of frequent and likely events

IncRiskFL

[ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

Incremental risk of likely and rare events

IncRiskLR

[ConsqRare] *((1/ [RpLike] )-(1/ [RpRare]))

TotRisk

[IncRiskFL]+[IncRiskLR]

Total estimated annualized risk

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Table H-11. Incremental risk computation Risk Field Description

Selection Syntax

Total estimated risk

All records

Sub-total risk for agriculture, fisheries and forest land uses

"Prop_Type" <> 'Built-up areas'

Sub-total risk for built-up areas

"Prop_Type" = 'Built-up areas'

Field

Computation Syntax

TotRisk

[IncRiskFL]+ [IncRiskLR]

AFFTotRisk

[TotRisk]

UrTotRisk

[TotRisk]

49.Compute for the total risk in the TotRisk field by adding the two incremental risk estimates (refer to table H-10 for the computation syntaxes for the incremental and total risk).

the total risk values in the respective fields. The separate sub total risk fields will allow statistical dissolve per municipality by type of property risk (AFF and built-up) in the succeeding steps.

50.Separate fields shall contain the estimated risk for agriculture, fisheries and forest land uses and total risk for built-up areas (refer to table H-11). Use the selection syntaxes to filter records and copy

51.Prepare a Risk to property map using the recommended symbologies. Use the TotRisk Field as the value field when symbolizing the magnitude of the risk in terms annual losses (refer to table H-12).

Table H-12. Recommended symbologies for risk to property estimates for individual areas.

Level

No Data

Range Values

Label

Symbology (RGB)

No Data Available

255/255/255

300,000

Php 300,000 and Below

255/255/190

300,000 - 600,000

Php 300,000 to Php 600,000

600,000 - 900,000

Php 600,000 to Php 900,000

255/181/189

900,000 - 1,200,000

Php 900,000 to Php 1,200,000

197/0/255

1,200,000 to <maximum observed value)

Php 1,200,000 and Above

255/255/0

255/0/0

Malimono

745

San Francisco

982

939

1052

701

Tubod

SURIGAO DEL NORTE

694

Placer

423

Taganaan

313

Load Island

Socorro

Caye Island

Bayagnan Island

Mahaba Island

114

Alegria

975

366

945

AGUSAN DEL NORTE 1128

Bacuag

457

209 Bonga Island

Dinago Island Masapelid Island, Placer

Opong Island

346 Hinatuan Island

Gigaquit

Lapinigan Island

Island, Gigaquit

Cabgan Island

Nagubat Island

Talavera Island 185

548

334

Ondona Island Masapelid Island, Tagana-an

Maanoc Island

196

Sugbu Island

Nonoc Island

Lamagon Island Island

335

Santa Monica

Awasan Island

333

1187

854

1168

1170

Aling Island

Claver

Halian Island

360

405

SURIGAO DEL SUR

Amaga Island

180

271

Poneas Island

259

159

245 282

225

Bucas Grande Island

137

242

274

207

183

Casulian Island

183East Bucas Island, Socorro

Pilar

225

San Isidro

Burgos

Bancuyo Island

Abanay Island

Dapa

San Benito 204

Middle Bucas Island 291

Tona Island, Del Carmen

Laonan Island

Poneas Island, Del Carmen 303

Kangbangyo Island

Cawhagan Island Megancub Island

Poneas Island, San Benito

Kangun Island

199

Sta. Monica

Date Published: Month 2011

Mamon Island Antokon Island

Lajanosa Island

Daco Island

Anajauan Island

Gen. Luna

Island, Pilar

10°0'0"N

Provincial Boundaries Road Network Spot Elevation Rivers City/Municipal Boundaries

Map prepared by:

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale

Map Sources:

TotIncRisk Php 300,000 and Below Php 300,000 to Php 600,000 Php 600,000 to Php 900,000 Php 900,000 to Php 1,200,000 Php 1,200,000 and Above

Exposusre_property_RIL_SDN

RISK TO PROPERTY

µ 0

BASE DATA LEGEND

Kilometers

1:315,000

REGION 13- CARAGA

PROVINCE OF SURIGAO DEL NORTE

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661

Mainit

Sison

Surigao City

Mangrove Island

Kabo Island

Rasa Island

Hanigad Island

172

Dinagat

Cagdianao

490

INDIVIDUAL AREAS

PROPERTY RISK FROM RAIN INDUCED LANDSLIDES

AND

395

303

134 Sibale Island Island

West Cabalian Island

Hikdop Island

Danaon Island

Lingig

Capaquian Island

San Jose

126°0'0"E

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139

170

Unib Island

631

540

Sibanac Island

303

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Sumilon Island

276

Basilisa (Rizal)

125°30'0"E

Kotkot Island, Basilisa

Figure H-1 Sample risk map in terms of property from rain induced landslide map, Province of Surigao del Norte, CARAGA Region.

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9°30'0"N

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Determine built-up and AFF asset base This involves the computation of the built-up and AFF asset base which will be used to the determine risk threshold values for the purposes risk prioritization. The computed built-up asset base, including the 20% threshold, will be added to the road asset base to come up with the total urban asset base. 52.Dissolve the property built up and agriculture polygon risk estimate dataset down to municipal level using the dissolve tool. Dissolve based on the RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName, MunArea, TRA, TFA, Prop_Type, Crop_Type, UnitCost, LUArea, TFAtoBU. Create statistical fields by getting the sum of the C o m p u t e d A re a , A f A re a F re q , AfAreaLike, AfAreaRare. The minimum value for the FDFreq, FDLike, FDRare, RpFreq, RpLike, RpRare fields. Sum of the

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ConsqFreq, ConsqLike, ConsqRare, IncRiskFL, IncRiskLR, TotRisk, AFFTotRisk and BuTotRisk fields (refer to table H-14). Save your dataset as Municipal_ RiskProper ty_LandUse_(hazard type)_(your province). 53.Add the necessary fields. Refer to the field labels and field value type and format (refer to table H-13). 54.Compute for the agricultural, fisheries, and forest values. First select all non-built up areas using the select by attributes tool, select the AFFValue field, use the field calculator and input the calculation syntax that will compute for the product of the total land area devoted to agriculture (by type of crop) and the unit cost per hectare. Calculation syntax is as follows: Selection Syntax - "Prop_Type" = 'AFF' Field Calculator Syntax: [UnitCost]* [SUM_CompuA]

Table H-13. Attribute table data fields for AFF and built-up asset base computation

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Total Agricultural, Fisheries and Forestry Value

Total Value of agricultural lands derived from the total agricultural land by type of crop and the corresponding replacement cost unit value expressed in Philippine Pesos

AFFValue

Float, Precision 20, Scale 2,

40% of Agricultural, Fisheries and Forestry Value Values

40% of the total value of agricultural lands derived from the total agricultural land by type of crop and the corresponding replacement cost unit value expressed in Philippine Pesos. 40% refers to the threshold value loss in agriculture for declaring a state of calamity

40perAFFVa

Float, Precision 20, Scale 2,

Total Built up value

Total built up value derived by multiplying the total floor area with the unit cost. Then adding the estimated value of the road infrastructure.

BUValue

Float, Precision 20, Scale 2,

20% of Built up area values

20% of the total value of affected urban area (total provincial assets) expressed in Philippine Pesos. Derived by multiplying 20% to the total monetary value of total assets (sum of the total floor area and critical infrastructure). 20% refers to the threshold value loss (20% of the total provincial asset have been destroyed) for declaring a state of calamity

20perBUVal

Float, Precision 20, Scale 2,

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Table H-14. Dissolve and statistical fields for municipal level aggregation Field

Field Description

Statistical dissolve type

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

MunArea

The computed area based on the GIS geometry expressed in hectares

Dissolve Field

TFA

Total floor area per municipality expressed as square meters

Dissolve Field

Prop_type

This field will contain the reclassified land use categories which will be used for the selection syntaxes.

Dissolve Field

Crop_Type

This field will contain the type of crop (i.e. rice, corn, coconut, production and protection forest, etc)

Dissolve Field

UnitCost

This field shall contain the replacement cost per property type expressed as unit cost per hectare

Dissolve Field

LUArea

Initial updated statistics on the area per land use per municipality in terms of hectares.

Dissolve Field

TFAtoBU

Estimated total floor area in hectares to every hectare of built up area. This will serve as a multiplier to determine the total cost affected given the derived affected built up area.

Dissolve Field

CompuArea

The total extent of the area affected based on the land cover map.

Sum

AfAreaFreq

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in hectares

Sum

AfAreaLike

Sum

AfAreaRare

Sum

FDFreq

Factor indicating the damage ratio to property for frequent events based on historical records.

Minimum

FDLike

Factor indicating the damage ratio to property for likely events based on historical records.

Minimum

FDRare

Factor indicating the damage ratio to property for rare events based on historical records.

Minimum

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for frequent events.

Sum

Estimated property damage resulting from a likely event based on the extent of affected area and the factor of property damage for likely events.

Sum

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for rare events.

Sum

RPFreq

Return period of a frequent event

Minimum

RPLike

Return period of a likely event

Minimum

RPRare

Return period of a rare event

Minimum

IncRiskFL

Incremental risk of frequent and likely events

Sum

Incremental risk of likely and rare events

Sum

TotRisk

Total Risk

Sum

AFFTotRisk

Total Risk for agriculture, fisheries and forest land areas

Sum

BUTotRisk

Total Risk for built-up areas

Sum

ConsqFreq

ConsqLike

ConsqRare

IncRiskLR

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55.With the selection still active, select the 40perAFFVa field and compute for the 40% of the agricultural value by multiplying a factor of 0.4 to the AFFValue. Calculation syntax is as follows: [AFFValue]*0.4

56.The AFFValue and 40perAFFVa fields will contain the sub-total asset base and risk threshold values of AFF areas at the municipal level but subdivided into type of crops. This will be further dissolved in the succeeding steps so all AFF assets can be added to give the total AFF asset base of the municipality for all crop and forest types. 57.Compute for the built-up area value. Select all built up areas using the select by attributes tool. Calculate the values of the BUValue by multiplying the total floor area per

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municipality and the average replacement unit cost per hectare. For clarification of the computation syntax, TFA values are expressed in square meters while the unit cost is expressed as value for every hectare. The TFA values must be forst converted to hectares before applying the unit cost. Your selection and field calculator syntax are as follows: Selection Syntax - "Prop_Type" = 'Built-up areas' Field Calculator Syntax: ([TFA]/10000)* [UnitCost]

58.With the selection still active, derive the twenty percent (20%) of the total Built up area value. Select the 20perBUVal field and use the following calculation syntax: [BUValue]*0.2

Table H-15. Dissolve and statistical fields for municipal level aggregation Field

Field Description

Statistical dissolve type

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

SUM_TotRis

Sum of the total risk for AFF and Built-up areas

Sum

SUM_AFFtot

Sub-total of the AFF computed risk

Sum

SUM_BUtot

Sub-total of the built-up computed risk

Sum

AFFValue

Sub-total AFF asset base per type of crop

Sum

40perAFFVal

Sub-total 40 percent risk threshold value for AFF areas per type of crop

Sum

BUValue

Computed built-up areas asset base

Maximum

20perBUVal

Computed 20 percent risk threshold for built-up areas

Maximum

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59.Values expressed in the BUValue and 20perBUVal fields indicate the subtotal of the built-up areas asset base and the risk threshold value. This will be fur ther dissolved so each municipality will have its unique built-up total asset base and risk threshold value. These estimates will be combined with the critical point facilities and lifeline utilities risk estimates for the purposes of risk prioritization. 60.Dissolve your dataset based on the RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName. Statistical fields of the sum of SUM_TotRis, SUM_AFFtot, and SUM_BUtot,AFFValue, 40perAFFVal. T h e m a x i m u m o f B U Va l u e ,

20perBUVal (refer to table H-15). Save your dataset as Prioritization_Municipal_RiskProperty _(hazard type)_(your province). 61.Notice that after dissolving the dataset, each municipality is represented as one record with separate fields indicating the total risk, asset base, and risk threshold values for AFF and built-up areas. This will serve as the risk prioritization dataset where risk estimates from the critical point facilities and lifeline utilities will be combined. 62.Proceed with the risk estimation for critical point utilities and lifeline utilities.

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Estimate risk to critical point facilities

This involves the risk estimation of critical infrastructure like bridges, power plants/sub-stations, communication towers, water related facilities such as water pumping and storage facilities. This will also include schools, hospitals, protective services, gover nment administrative buildings. Such facilities will be indicated as point data where

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the replacement or construction cost will also be indicated per structure. Data gathering activities to spatially locate and map critical point utilities of the province can be done through GPS surveys and using longitude and latitude tabular data that are available with regional government agencies. Prepare a critical point utilities exposure dataset 1. The point data attribute table shall contain the minimum information (refer to table H-16).

Table H-16. Attribute table data fields for risk estimation for the various hazard occurrences. FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Regional Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

RegPSGC

Long Integer, Precision 0

Region Name

Name of the Region

RegName

TEXT, Length 50

Provincial Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

ProvPSGC

Long Integer, Precision 0

Province Name

Name of the Province

ProvName

TEXT, Length 50

Municipal/City Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

MunPSGC

Long Integer, Precision 0

Municipal/City Name

Name of the City or Municipality

MunName

TEXT, Length 50

Critical Infrastructure type

The type of critical infrastructure (i.e. bridges, power plants/substations, communication towers, water related facilities such as water pumping and storage facilities, schools, hospitals, protective services, government administrative buildings)

CriInfra

TEXT, Length 50

Unique name of the point structure

Unique reference name for the point structure

Name

TEXT, Length 50

Unit cost

The estimated replacement/construction cost of the point structure. Unit cost expressed as either construction or replacement can be assigned through consultation with mandated agencies.

UnitCost

Float, Precision 20, Scale 2,

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Table H-17. Attribute table data fields for consequence and risk estimation for critical point facilities FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Factor for property damage for frequent events

Factor indicating the damage ratio to property for frequent events based on historical records.

FDFreq

Float, Precision 20, Scale 10,

Factor for property damage for likely events

Factor indicating the damage ratio to property for likely events based on historical records.

FDLike

Float, Precision 20, Scale 10,

Factor for property damage for likely events

Factor indicating the damage ratio to property for rare events based on historical records.

FDRare

Float, Precision 20, Scale 10,

Estimated consequence of property damage for frequent events

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for frequent events.

ConsqFreq

Float, Precision 20, Scale 2,

Estimated consequence of property damage for likely events

Estimated property damage resulting from a likely event based on the extent of affected area and the factor of property damage for likely events.

ConsqLike

Float, Precision 20, Scale 2,

Estimated consequence of property damage for rare events

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for rare events.

ConsqRare

Float, Precision 20, Scale 2,

Return period of a frequent event

RPFreq

Short Integer, scale 0

Return period of a likely event

RPLike

Short Integer, scale 0

Return period of a rare event

RPRare

Short Integer, scale 0

Incremental risk of frequent and likely events

The incremental risk of the computed likely consequence multiplied by the difference between the reciprocal of return periods of frequent and likely hazard events)

IncRiskFL

Float, Precision 20, Scale 2

Incremental risk of likely and rare events

The incremental risk of the computed rare consequence multiplied by the difference between the reciprocal of return periods of likely and rare hazard events)

IncRiskLR

Float, Precision 20, Scale 2

Total Risk for Critical Infrastructure

The total risk critical point infrastructure. This will be added to the computed risk of built up areas to derive the total urban area risk

CITotRisk

Float, Precision 20, Scale 2

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Table H-18. Selection and computation syntaxes for consequence estimation on critical point facilities Risk Field Description

Selection Syntax

Field

Computation Syntax

Frequent Events

"HazCode" = 'HSA'

[ConsqFreq]

[UnitCost]* [FDFreq]

Likely Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA'

[ConsqLike]

[UnitCost]* [FDLike]

Rare Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA'

[ConsqRare]

[UnitCost]* [FDRare]

2. Municipal infor mation can be appended to the critical point dataset by intersecting the point dataset with the polygon municipal base map. 3. Input the unique construction cost per point facility. User can choose to assign a unit cost per type facility if the construction cost is not available. 4. If the unique names of the facilities are available, encode the name for future reference. Prepare a critical point facilities hazard exposure dataset 5. Intersect the critical infrastructure map data (point) with the hazard map (polygon) and save the output intersect data as point data. This will append the hazard codes to your point data which will be used as

basis for the consequence and risk estimation. 6. By this step, hazard susceptibility of each point can be determined. Compute for the consequence and risk 7. Add twelve (12) additional fields that will contain the factor of damage, consequence per hazard occurrence, return period and risk estimation estimates. Use the recommended field header labels and value formats (refer to table H-17). 8. Input the factor of damage for critical point facilities. In general, the factor of damage will be similar to built-up areas. 9. Compute for the consequence for frequent events. Select all point facilities that fall within the high

Table H-19. Incremental and total risk computation Risk Field Description

Field

Incremental risk of frequent and likely events

IncRiskFL

[ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

Incremental risk of likely and rare events

IncRiskLR

[ConsqRare] *((1/ [RpLike] )-(1/ [RpRare]))

Total risk of critical point facilities

CITotRisk

[IncRiskFL]+[IncRiskLR]

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susceptible areas, compute for the consequence by multiplying the unit cost with the factor of damage for frequent events. Do the same with the other hazard occurrences (likely and rare) using the corresponding factor of damage (refer to table H-18). The consequence will be expressed as unit value in Philippine Pesos. 10.Input the return period per hazard occurrence. Make a batch edit of all return period fields per hazard occurrence. 11.Compute for the first incremental risk (frequent-likely) by using the field calculator (refer to table H-19) and using the computation syntax: [ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

12.Compute for the second incremental risk f(frequent-likely) by using the field calculator and using the computation syntax: [ConsqRare] *((1/ [RpLike] )-(1/ [RpRare]))

13.C o m p u t e f o r t h e s u m o f a l l incremental risk in the CITotRisk field by adding the two incremental risk fields.

[IncRiskFL]+[IncRiskLR] 14.The estimated annualized risk are computed per critical facility and can be aggregated to the municipal level in the succeeding steps. The estimated risk shall be combined with the built-up and lifeline utilities risk to determine the total urban risk per municipality. Aggregate critical point facilities risk estimates to the municipal level 15.Summarize the risk estimates for the critical point facilities. Open the attribute table, then right click any field. Select the summarize table function. Select MunName as the f i e l d t o s u m m a r i z e , c re a t e a statistical sum of the CITotRisk field. This operation will sum all the estimated risk of all points at the municipal level.Save your summary table as CI_Risk_Munilevel_(Hazard type)_province.dbf. This table will be fur ther combined to the Risk prioritization dataset where the total critical infrastructure risk will be combined to the built-up and lifeline utilities computed risk. 16.Proceed with risk estimation for lifeline utilities.

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Estimate risk to lifeline facilities

Prepare a lifeline utilities exposure dataset

Lifeline utilities include roads, potable water distribution lines, communication and power transmission lines, These features are commonly represented as line data in GIS. Provinces are encouraged to map out all necessary lifelines in their jurisdiction with the assistance of regional, national agencies and private corporations. For illustration purposes, only transportation road utilities will be used in risk estimation.

1. Prepare a separate risk estimation of lifeline utilities (mostly road network) will be conducted and the supporting line feature type map data shall be prepared with the following minimum attribute information (refer to table H-20). 2. If the existing lifeline dataset does not have municipal information, intersect the road line data with the municipal boundary map to append the road data with approximate municipal location. Save the file as road network_municipal level.

Table H-20. Minimum attribute data fields for lifeline utilities exposure dataset FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Regional Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

RegPSGC

TEXT, Length 50

Region Name

Name of the Region

RegName

TEXT, Length 50

Provincial Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

ProvPSGC

TEXT, Length 50

Province Name

Name of the Province

ProvName

TEXT, Length 50

Municipal/City Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

MunPSGC

TEXT, Length 50

Municipal/City Name

Name of the City or Municipality

MunName

TEXT, Length 50

Unique name of the Road

Unique reference name for the road line data

Name

TEXT, Length 50

Road Classification

Road classification whether national, provincial, municipal or barangay

RdClass

TEXT, Length 50

Road Type

Road type whether paved

RdType

TEXT, Length 50

Unit cost

The estimated replacement/construction cost of the line

UnitCost

Float, Precision

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Table H-21. Data fields for individual road length and value FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Length

Estimated road length in linear kilometers to be derived using the GIS calculate geometry (length) tool.

RdLength

Float, Precision 20, Scale 4,

Road Value per road type

Sub-total value per road type.

RdValue

Float, Precision 20, Scale 2,

3. Input the unit cost (construction cost) per linear kilometer of road by surface type (asphalt, concrete, etc) and road classification (national, provincial, municipal, barangay) in the unit cost field. Determine the total value of the lifeline assets and risk threshold values 4. Add two additional fields to contain the segment road asset statistics (refer to table H-21). 5. Compute for the length of each road segment (RdLength field) by using the calculate geometry and expressing the length in linear kilometers. 6. Compute for the road value by multiplying the segment length with the unit cost. Use the computation syntax: [RdLength]*[UnitCost]

7. Add two additional fields that will contain the municipal road value totals (refer to table H-22). 8. Populate the MunRdValue field, encode the total road value per municipality by selecting first all the road segments of a particular municipality (refer to table H-23). 9. In the RdValue field, use the field statistics to determine the sum of all selected road segments of the municipality. 10.Encode the derived sum in the M u n R d Va l u e o f t h e s e l e c t e d municipality. This value will indicate t h e t o t a l ro a d a s s e t s o f t h e municipality in Philippine pesos. 11.Repeat the above steps until all of the values are encoded in the MunRdValue for each municipality. 12.Note that all records per municipality will have the same value indicated in the MunRdValue. This will indicate

Table H-22. Data fields for summary municipal level road and risk threshold values FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Road Value Municipal

Total value for all road types per municipality.

MunRdValue

Float, Precision 20, Scale 2,

20% of the total road value at the Municipal level

Total value for all road types per municipality.

20perMunRV

Float, Precision 20, Scale 2,

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Table H-23. Sample data fields for summary municipal level road and risk threshold values MunName Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Sablan Tublay Tublay Tublay Tublay Tublay Tublay Tublay Tublay Tublay Tublay

UnitCost

RdValue1

RdLength 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00 17,000,000.00

0.0571 0.0906 8.3943 7.4316 0.4107 3.5700 1.2479 0.3697 0.4470 1.1591 1.5368 0.7317 0.2843 0.2490 0.0398 0.0746 6.0805 0.5637 0.6427 0.7099 1.5738 5.3488 5.3084 5.8168

MunRdValue2

970,700.00 1,540,200.00 142,703,100.00 126,337,200.00 6,981,900.00 60,690,000.00 21,214,300.00 6,284,900.00 7,599,000.00 19,704,700.00 26,125,600.00 12,438,900.00 4,833,100.00 4,233,000.00 676,600.00 1,268,200.00 103,368,500.00 9,582,900.00 10,925,900.00 12,068,300.00 26,754,600.00 90,929,600.00 90,242,800.00 98,885,600.00

441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 441,656,600.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00 444,703,000.00

20perMunRV3 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,331,320.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00 88,940,600.00

1The

road value is the product of the segment length and unit cost per road segment within a municipality. municipal road value is the sum of all the road value segments per municipality. This represents the total road assets of the municipality. 3The 20% of the municipal road value is the total municipal road value multiplied by 20%. This will serve as the risk threshold value for roads and will be added to the threshold value for built-up areas which will indicate the total urban risk threshold 2The

the total road value for each municipality. 13.In the 20perMunRV field, compute for the 20% of the total road value at the Municipal level for all records. 14.Users can use the same municipal ro a d i n v e n t o r y d a t a s e t w h e n overlying with other hazard maps where the total road asset value and the risk threshold has been computed. Prepare the hazard exposure lifeline dataset 15.Intersect the line exposure dataset with the polygon based hazard map. This will append the susceptibility levels (hazcodes) to the line data. Save the file as the lifeline hazard exposure dataset (indicating the type of the hazard and province).

16.Add thirteen (13) additional fields that will contain the factor of damage, consequence per hazard occurrence, return period and risk estimation estimates. Use the recommended field header labels and value formats (refer to table H-24). 17.In the AffRoad field, calculate the length of road per record. Use the attribute table calculate geometry function. 18.Input the factor of damage per hazard occurrence (frequent likely and rare). All records will have the same factors for each hazard occurrence. Use the same factor of damage used in the risk estimation for built-up areas. 19.Compute for the consequence per hazard occurrence. Consequence shall be expressed in Philippine

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Table H-24. Attribute data fields for lifeline utilities consequence and risk estimation FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Affected road

Affected area expressed as linear kilometers of road

AffRoad

Float, Precision 20, 6

Factor for property damage for frequent events

Factor indicating the damage ratio to property for frequent events based on historical records.

FDFreq

Float, Precision 20, Scale 10,

Factor for property damage for likely events

Factor indicating the damage ratio to property for likely events based on historical records.

FDLike

Float, Precision 20, Scale 10,

Factor for property damage for likely events

Factor indicating the damage ratio to property for rare events based on historical records.

FDRare

Float, Precision 20, Scale 10,

Estimated consequence of property damage for frequent events

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for frequent events.

ConsqFreq

Float, Precision 20, Scale 2,

Estimated consequence of property damage for likely events

Estimated property damage resulting from a likely event based on the extent of affected area and the factor of property damage for likely events.

ConsqLike

Float, Precision 20, Scale 2,

Estimated consequence of property damage for rare events

Estimated property damage resulting from a frequent event based on the extent of affected area and the factor of property damage for rare events.

ConsqRare

Float, Precision 20, Scale 2,

Return period of a frequent event

RPFreq

Float, Precision 7, Scale 4,

Return period of a likely event

RPLike

Float, Precision 7, Scale 4,

Return period of a rare event

RPRare

Float, Precision 7, Scale 4,

Incremental risk of frequent and likely events

The incremental risk of the computed likely consequence multiplied by the difference between the reciprocal of return periods of frequent and likely hazard events)

IncRiskFL

Float, Precision 20, Scale 2

Incremental risk of likely and rare events

The incremental risk of the computed rare consequence multiplied by the difference between the reciprocal of return periods of likely and rare hazard events)

IncRiskLR

Float, Precision 20, Scale 2

Total Risk to road infrastructure

The total risk for road infrastructure. This will be added to the derived built up computed risk to to derive the total urban risk.

RdTotRisk

Float, Precision 20, Scale 2

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Table H-25. Selection and computation syntaxes for consequence estimation on lifeline utilities Risk Field Description

Selection Syntax

Field

Computation Syntax

Frequent Events

"HazCode" = 'HSA'

[ConsqFreq]

[UnitCost]*[AffRoad]* [FDFreq]

Likely Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA'

[ConsqLike]

[UnitCost]* [AffRoad]* [FDLike]

Rare Events

"HazCode" = 'HSA' OR "HazCode" = 'MSA' OR "HazCode" = 'LSA'

[ConsqRare]

[UnitCost]*[AffRoad]*[FDRare]

Pesos (Php). 20.To compute for consequence for frequent events, first select all roads within the high susceptibility areas (HSA) using the select by attributes tool. 21.Multiply the estimated affected length (AffRoad field) with the unit cost and the factor of damage per hazard occurrence (refer to table H-25). 22.Repeat the steps for likely and rare events by using the proper selection syntaxes and computation syntax to determine the estimated consequence. 23.Repeat the steps for likely and rare events by using the proper selection syntaxes and computation syntax to determine the estimated consequence.

24.Input the return period per hazard occurrence. Use the batch edit field calculator function. All records will have the same return period for frequent, likely and rare events. 25.Compute for the first incremental risk (frequent-likely) by using the field calculator and using the computation syntax: [ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

26.Compute for the second incremental risk f(frequent-likely) by using the field calculator and using the computation syntax: [ConsqRare] *((1/ [RpLike] )-(1/ [RpRare]))

27.C o m p u t e f o r t h e s u m o f a l l incremental risk in the RdTotRisk field by adding the two incremental risk fields. [IncRiskFL]+[IncRiskLR]

Table H-26. Incremental and total risk computation Risk Field Description

Field

Incremental risk of frequent and likely events

IncRiskFL

[ConsqLike]*((1/ [RpFreq])-(1/ [RpLike]))

Incremental risk of likely and rare events

IncRiskLR

[ConsqRare] *((1/ [RpLike] )-(1/ [RpRare]))

Total risk of critical point facilities

CITotRisk

[IncRiskFL]+[IncRiskLR]

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Aggregate lifeline utilities risk estimates to the municipal level 28.Summarize the risk estimates for lifeline utilities. Open the attribute table, then right click any field. Select the summarize table function. Select MunName as the field to summarize, create a statistical sum of the RdTotRisk field, maximum of

the MunRdValue and 20perMunRV. This operation will sum all the estimated risk for all lifeline segments at the municipal level including the lifeline asset base and the risk threshold. Save your summary table as Rd_Risk_Munilevel_(Hazard type) _province.dbf.

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Municipal risk to property prioritization There are two general risk to property types, one is measuring the risk to agriculture, fisheries and forestry assets (AFF) and the other is risk to the urban assets. Estimating the AFF risk has been covered in the polygon type risk estimation portion where the total risk has been computed and the asset base and risk thresholds has been established. Additional geoprocessing and table joining is needed to determine the total risk to urban areas. The risk estimates derived from the land use risk dataset (polygon dataset) is only limited to the built up areas and the agricultural, fisheries, and forest risk estimates. It does not include the risk estimates for roads and critical infrastructure. The risk estimates derived from the lifeline utilities and critical point facilities should be added to the total risk for built-up areas for the urban risk prioritization. Since these datasets are of different feature types, the attribute tables of the datasets containing the risk estimates and the value should be combined. Once combined, the risk estimates and the total urban value should be added (built-up expressed as total floor area, road value expressed as total cost of all linear kilometers of road, and the total cost of replacement of critical point infrastructure). The total computed risk shall be compared to the 20% that total value to derive the risk percentage score for the purposes of prioritization. By this time, user should have the municipal aggregated risk estimates for the land use covering AFF and built-up areas, the municipal level risk estimates (table format) for critical point facilities and lifeline utilities.

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Join all municipal level risk tables 1. Join the risk estimates of the critical point and road line infrastructure tables with the dissolved Prioritization_Municipal_ RiskProperty_(hazard type)_(your province) dataset. Use the municipal PSGC codes or the municipal names as the basis of the table join. 2. O p e n t h e C I _ R i s k _ M u n i l e v e l _ (Hazard type)_province.dbf and Rd_Risk_Munilevel_(Hazard type) _province.dbf. You will notice that the tables were added in the Table of Contents and has shifted to the Source Data Tab. Right click the CI_Risk_Munilevel_(Hazard type) _province.dbf and click Open to view the attribute information. 3. Scrutinize the attribute tables and determine if the municipal PSGC or municipal names are present. This will be the field that will be used as basis for table joining when you add these tables to the polygon type municipal aggregated property land use risk estimate shapefile. 4. Now proceed with the table joining. Go to the Prioritization_ Municipal_RiskProperty_(hazard type)_(your province).shp and open the attribute table, view the options button and select join and relates, and select Join, you will be prompted to the Join Data Window. 5. In the Join Data Window, select Join attribute from a table in the “What do you want to join to this layer” drop down menu. 6. In item 1, Select MunPSGC or MuniName in the “Choose the field in this layer that the join will be based on” 7. In item 2, select CI_Risk_Munilevel_ (Hazard type)_province.dbf in the

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“Choose the table to join to this layer” (this is pertaining to the dbf table) 8. In item 3, select the MunPSGC or MuniName field in the “Choose the field in the table to base the join on” (this pertains to the field in the *.dbf table where the municipal PSGC codes are located which will be the basis for the table record matching > tick the keep all records (If there are records where matching can not be made, unmatched records will contain a null values for all fields being appended in to the target table from the join table) > Click Ok. 9. Scrutinize the results of the matching by opening the attribute table of the Municipal_RiskProperty_(hazard type)_(your province).shp. You should have an expanded attribute table with the all the values and fields of your polygon map and the appended table. 10.Repeat the procedures for joining the Rd_Risk_Munilevel_(Hazard type)_province.dbf. with the Municipal_RiskProperty_(hazard type)_(your province).shp. 11.After joining the road risk estimate table, scrutinize your Municipal_RiskProperty_(hazard type)_(your province).shp attribute table. It should contain the municipal level risk estimates for the land use property, critical point facilities and lifeline utilities risk estimates. 12.Joining the tables is not permanent meaning you will lose the table join the next time you open your shapefile. If you want to permanently attach the joined attribute information from the various files, you will need to export it to a new shapefile.

13.T o s a v e r i g h t c l i c k t h e Municipal_RiskProperty_(hazard type)_(your province).shp > Data > Export, you will be prompted to the Export Data window. 14.I n t h e e x p o r t d a t a w i n d o w, Municipal_RiskProperty_(hazard type)_(your province).shp, choose All features in the Export drop down menu > tick the layers’s source data > specify a filename and location. Save your file as Municipal_Risk to Property and Infrastructure_(hazard type)_(your province).shp 15.Add the Municipal_Risk to Property and Infrastructure_(hazard type)_ (your province).shp in your list of datasets. Compute for the Urban risk and threshold values 16.Add the prioritization fields that will contain the risk percentage and the prioritization categories (refer to table H-27). 17.Derive the updated urban value by adding the total value of the built up areas and the road (lifeline utilities) infrastructure. Select the UrVal field and use the calculate field tool to derive the sum. Your computation syntax should be as follows: [MAX_BUValu]+[MAX_MunRdV] Note: Identify the exact field containing the urban values estimated for built up areas and the road infrastructure. During the dissolve, field names may vary. Always refer to the *.dbf file to determine the Municipal level road value.

18.Derive the updated 20% threshold of the urban value by adding the total risk threshold of the built up areas and the road (lifeline utilities) infrastructure. Select the 20perUrVal field and use the calculate field tool to derive the sum. [MAX_20perB]+[MAX_20perM]

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Table H-27. Attribute data fields for lifeline utilities consequence and risk estimation FIELD

FIELD HEADER LABEL

Description

TYPE AND FORMAT

Revised urban value

This is the computed total urban value combining the total assets value of the total floor area, and road infrastructure. It is assumed that the critical point infrastructure is already included in the BUValue.

UrVal

Float, Precision 20, Scale 2,

40% threshold of the urban value

This is the computed 40% of the total urban value combining the total assets value of the total floor area, critical point and road infrastructure.

20perUrVal

Float, Precision 20, Scale 2,

Revised risk

Revised computed urban risk combining the risk estimates of the built up, critical point and road infrastructure

UrRisk

Float, Precision 20, Scale 2,

Risk to Value percentage of agriculture, fisheries and forest assets

Percentage of the total estimated risk to the total agriculture, fisheries and forest assets. This is derived by dividing the total computed agriculture, fisheries and forest (AFF) risk to 40% of the total AFF value

RiskPerAFF

Float, Precision 7, Scale 4,

Risk to Value percentage of all urban assets.

Percentage of the total estimated risk to the built-up areas, critical point and road infrastructure. This is derived by dividing the total computed urban risk to 20% of the total urban value

RiskPerUr

Float, Precision 7, Scale 4,

Numerical Priority Score for agricultural lands

The assigned numerical priority index depending on the percentage value of total risk to value for agricultural lands

RPrioAFFNm

Integer 1,Precision

Text Priority Score for agricultural lands

The assigned text priority index depending on the percentage value of total risk to value for agricultural lands

RPrioAFFTx

Text, length 50

Numerical Priority Score for built-up areas

The assigned numerical priority index depending on the percentage value of total risk to value for urban areas

RPrioUrNum

Integer 1,Precision

Text Priority Score for builtup areas

The assigned text priority index depending on the percentage value of total risk to value for urban areas

Note: Identify the exact field containing the 20% threshold urban values estimated for built up areas and road infrastructure. During the dissolve, field names may vary. Always refer to the *dbf file to determine the 20% Municipal level road value.

19.Compute for the total urban risk by adding the risk estimates of the built up areas, critical point facilities and lifeline utilities. Compute the sum in t h e U r R i s k f i e l d . Yo u r f i e l d computation syntax should be as follows: [SUM_RdTotR]+ [SUM_CITotR]+ [SUM_BuTotR] 20.Notice that no computation will be done for AFF areas. User can proceed with the risk prioritization based on the municipal level risk to

RPrioUrTx

Text, length 50

AFF and the threshold value per municipality. Compute for the Risk Percentage for Urban and AFF areas 21.Compute for the risk percentage. In the RiskPerUr field, divide the values in the UrRisk (sum of total computed risk for built up, critical point and ro a d i n f r a s t r u c t u re ) w i t h t h e 20perUrVal (sum of the 20 percent urban value threshold) field. Your field computation syntax should be as follows: [UrRisk]/ [20perUrVal]*100 22.The risk percentage for urban indicates the proportion between the

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computed risk and the risk threshold. A value of 100% means the annual risk is equivalent to the risk threshold meaning every year the municipality will incur damages brought about by the hazard to the urban areas equivalent to 20% (threshold for declaring a state of calamity) of its total urban assets making indicating that the municipality need is in urgent need of disaster mitigation/intervention measures to minimize the risk. 23.Compute for the percentage risk per municipality dividing the total agriculture, fisheries and forest (AFF) value and the total computed AFF risk. In the RiskPerAFF field, divide the values in the SUM_SUM_AF (sum of total

computed risk for AFF) with the SUM_ 40perA (sum of the 40 percent AFF value) field and multiply by 100 to express it in terms of percentage. 24.The risk percentage for AFF areas indicate the proportion between the computed risk and the risk threshold. A value of 100% means the annual risk is equivalent to the risk threshold meaning every year the municipality will incur damages brought about by the hazard equivalent to 40% of the total AFF asset base (threshold for declaring a state of calamity). 25.In the select by attributes tool, select the value ranges in RiskPerAFF and RiskPerUr field using the selection

Table H-28. Selection syntaxes and recommended symbologies for risk prioritization levels for AFF areas. Risk Levels

Description

High risk to Very High risk

Municipal Risk %

>=40%

GIS Selection Syntax

Prioritization Index Field RiskPrio

RiskPerAFF >= 40

RiskTex t

Urgent

Symbology (RGB)

255/0/0

Acceptability and action needed

Moderate risk

< 40 - 20%

Very Low risk to Low risk

>0 to <20%

No hazard data available

= 0%

RiskPerAFF >= 20 AND <40

RiskPerAFF < 20 AND > 0

RiskPerAFF = 0

High Priority

197/0/255

Intolerable. Further investigation, planning and implementation of options required to reduce risk to acceptable levels. Tolerable, provided plan is implemented to maintain or reduce risks. May require investigation and planning of options.

Low Priority

255/255/0

No Data

255/255/255

Usually accepted. Treatment requirements and responsibility to be defined to maintain or reduce risk. Unsurveyed areas in terms of hazard susceptibility or hazard is not present in the areas.

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syntax per priority index. For the selected records per value range, type the corresponding risk prioritization index for the AFF and urban risk both in numerical and text formats (refer to table H-28 to 29).

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The resulting scores shall be used for the creation of the municipal level risk composite hazard prioritization map (priority index scores for fatality, agriculture and built-up damage).

Table H-29. Selection syntaxes and recommended symbologies for risk prioritization levels for Built-up areas. Risk Levels

Description

High risk to Very High risk

Municipal Risk %

>=20%

GIS Selection Syntax

Prioritization Index Field RiskPrio

RiskPerUr >= 20

RiskTex t

Urgent

Symbology (RGB)

255/0/0

Acceptability and action needed

Moderate risk

< 20 - 10%

Very Low risk to Low risk

>0 to <10%

No hazard data available

= 0%

RiskPerUr >= 10 AND <20

RiskPerUr < 10 AND > 0

RiskPerUr = 0

High Priority

197/0/255

Low Priority

255/255/0

No Data

255/255/255

Usually accepted. Treatment requirements and responsibility to be defined to maintain or reduce risk. Unsurveyed areas in terms of hazard susceptibility or hazard is not present in the areas.

Malimono

745

San Francisco

982

939

1052

701

Tubod

SURIGAO DEL NORTE

694

Placer

423

Taganaan

313

Load Island

Socorro

Caye Island

Bayagnan Island

Opong Island

Mahaba Island

114

Alegria

975

366

945

AGUSAN DEL NORTE 1128

Bacuag

457

209 Bonga Island

Dinago Island Masapelid Island, Placer

346 Hinatuan Island

Gigaquit

Lapinigan Island

Island, Gigaquit

Cabgan Island

Nagubat Island

Talavera Island 185

548

334

Ondona Island Masapelid Island, Tagana-an

Maanoc Island

196

Sugbu Island

Nonoc Island

Lamagon Island Island

Rasa Island

335

Santa Monica

Awasan Island

333

1187

854

1168

1170

Aling Island

Claver

Halian Island

360

405

SURIGAO DEL SUR

Amaga Island

180

271

Poneas Island

159

245 282

225

Bucas Grande Island

259

137

242

274

207

183

Casulian Island

183East Bucas Island, Socorro

Pilar

225

San Isidro

Burgos

Bancuyo Island

Abanay Island

Dapa

San Benito 204

Middle Bucas Island 291

Tona Island, Del Carmen

Laonan Island

Poneas Island, Del Carmen 303

Kangbangyo Island

Cawhagan Island Megancub Island

Poneas Island, San Benito

Kangun Island

199

Sta. Monica

Date Published: Month 2011

Mamon Island Antokon Island

Lajanosa Island

Daco Island

Anajauan Island

Gen. Luna

Island, Pilar

Provincial Boundaries Road Network Spot Elevation Rivers

Map prepared by:

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale

Map Sources:

No Data Low Priority High Priority Urgent

PRIORITY RANKING

µ 0

BASE DATA LEGEND

Kilometers

1:315,000

REGION 13- CARAGA

PROVINCE OF SURIGAO DEL NORTE

AGGREGATED TO MUNICIPAL/CITY LEVEL

AND FISHERIES TO RISK PROPERTY AGRICULTURAL TOAGRICULTURE, RISK LANDSLIDE RAIN INDUCED FROMINDUCED FORESTRY LANDSLIDES FROM RAIN

P HYSICAL F RAMEWORK P LANS

661

Mainit

Sison

Surigao City

Mangrove Island

Kabo Island

Hanigad Island

172

Dinagat

Cagdianao

490

126°0'0"E

AND

395

303

134

Sibale Island Island

West Cabalian Island

Hikdop Island

Danaon Island

Lingig

Capaquian Island

San Jose

631

540

P ROVINCIAL D EVELOPMENT

139

170

Unib Island

303

Sumilon Island

276

Basilisa (Rizal)

M AINSTREAMING DRR/CCA

Sibanac Island

Kotkot Island, Basilisa

125°30'0"E

Figure H-2 Sample risk prioritization map in terms of property for agriculture, fisheries and forestry areas from rain induced landslide, Province of Surigao del Norte, CARAGA Region.

10°0'0"N

FOR

9°30'0"N

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1052

701

Tubod

Opong Island

Mahaba Island

114

1187

854

1168

Claver

1170

360

405

SURIGAO DEL SUR

Amaga Island

159

282

225

137

242

274

Casulian Island

183East Bucas Island, Socorro

Bancuyo Island

Abanay Island

Dapa

242

Pilar

183

Date Published: Month 2011

Mamon Island Antokon Island

Lajanosa Island

Daco Island

Anajauan Island

Gen. Luna

Island, Pilar

Provincial Boundaries Road Network Spot Elevation Rivers

Map prepared by:

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale

Map Sources:

No Data Low Priority High Priority Urgent

PRIORITY RANKING

µ 0

BASE DATA LEGEND

Kilometers

1:315,000

REGION 13- CARAGA

PROVINCE OF SURIGAO DEL NORTE

AND

945

Gigaquit

Aling Island

245

Bucas Grande Island

259

Middle Bucas Island 291

Poneas Island

207

225

San Isidro

Burgos

P ROVINCIAL D EVELOPMENT

AGUSAN DEL NORTE 1128

975

366

Lapinigan Island

Island, Gigaquit

Cabgan Island

180

271

Tona Island, Del Carmen

Laonan Island

Poneas Island, Del Carmen 303

Kangbangyo Island

Cawhagan Island Megancub Island

Poneas Island, San Benito

San Benito 204

199

Sta. Monica

AGGREGATED TO MUNICIPAL/CITY LEVEL

RAIN PROPERTY FROM URBANRESIDENTIAL RISK PROPERTY BUILT-UP TOTO RISK LANDSLIDE INDUCED LANDSLIDES INDUCED FROM RAIN

Alegria

Bacuag

457

209 Bonga Island

Dinago Island Masapelid Island, Placer

Nagubat Island

Talavera Island 185

Hinatuan Island

346

Halian Island

Kangun Island

126°0'0"E

M AINSTREAMING DRR/CCA

661

423

Socorro

Caye Island

Bayagnan Island

548

334

Ondona Island Masapelid Island, Tagana-an

Maanoc Island

196

Sugbu Island

Nonoc Island

Santa Monica

335

333

Awasan Island

Dinagat

Cagdianao

490

Lamagon Island Island

Rasa Island

Taganaan

313

Load Island

172

Hanigad Island

SURIGAO DEL NORTE

694

134

Sibale Island Island

Kabo Island

Placer

Mangrove Island

Surigao City

Mainit

Sison

303

West Cabalian Island

Hikdop Island

Danaon Island

Lingig

Capaquian Island

San Jose

631

540

FOR

982

939

170

Unib Island

Sibanac Island

303

M ANUAL

Malimono

745

San Francisco

395

139

Sumilon Island

276

Basilisa (Rizal)

125°30'0"E

9°30'0"N

Kotkot Island, Basilisa

10°0'0"N

Figure H-3 Sample risk prioritization map in terms of urban assets from rain induced landslide, Province of Surigao del Norte, CARAGA Region.

100 P HYSICAL F RAMEWORK P LANS

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Composite Risk Prioritization and Evaluation

ANNEX I

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103

Annex I: Composite Risk Prioritization and Evaluation The composite risk prioritization and evaluation combines the results of prioritization indexes derived from the risk to fatality, urban assets and agriculture, fisheries and forestry (AFF) assets. The cumulative index will be used to determine which municipality in the province should be prioritized for risk mitigation intervention measures. 1. Prepare the risk prioritization maps for fatality and property (urban and AFF)

options button and select join and relates, and select Join, you will be prompted to the Join Data Window.

2. Combine the fatality risk estimate table with the property risk dataset. User can use the join table option in GIS to join the risk to fatality table to the property risk dataset to create the composite risk prioritization map.

5. In the Join Data Window, select Join attribute from a table in the “What do you want to join to this layer” drop down menu.

3. Now proceed with the table joining. Add the Municipal_Risk to Property and Infrastructure_(hazard type)_ (your province).shp and the Municipal_RiskFatality_(hazard type) _(your province).shp. Make sure you are adding the risk estimates for the same hazard. 4. O p e n t h e a t t r i b u t e t a b l e Municipal_Risk to Property and Infrastructure_(hazard type)_(your province).shp. Click and view the

6. In item 1, Select MunPSGC or MuniName in the “Choose the field in this layer that the join will be based on” 7. I n item 2, select Municipal_RiskFatality_(hazard type) _(your province).shp in the “Choose the table to join to this layer”. 8. In item 3, select the MunPSGC or MuniName field in the “Choose the field in the table to base the join on” (this pertains to the field in the risk to fatality table where the

Table I-1. Composite prioritization attribute table fields FIELD

Description

FIELD HEADER LABEL

TYPE AND FORMAT

Numerical Composite Score

Composite prioritization index combining the risk prioritization scores for fatality, AFF and Urban.

CompNum

Integer, Precision 1

Composite prioritization category

The assigned text priority category depending on the composite risk score

CompText

Text, length 50

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municipal PSGC or municipal names are located which will be the basis for the table record matching > tick the keep all records. Note that if there are records where matching can not be made, unmatched records will contain null values for all fields being appended in to the target table from the join table) > Click Ok. 9. Scrutinize the results of the matching by opening the attribute table of the Municipal_Risk to Property and Infrastructure_(hazard type)_(your province).shp. You should have an expanded attribute table where the risk prioritization for fatality and property are present.

P ROVINCIAL D EVELOPMENT

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10.Create two new fields that will contain the composite prioritization index (refer to table I-1). 11.Compute for the composite risk score per municipality. At the CompNum field, derive the sum of the risk prioritization indexes of fatality, property damage to AFF, and urban. Use the selection syntax as follows: [RPrioAFFNm]+ [RPrioUrNum]+ [RPrioFaNum] 12.Create the composite priority index map for the particular hazard using the recommended range composite prioritization risk values, legend labels and symbologies (refer to table.

Table H-27. Selection syntaxes and recommended symbologies for risk prioritization levels for Built-up areas. Risk Levels Composite Risk Prioritization Category (CompText)

Urgent

Composite Risk Prioritization Index

GIS Selection Syntax

Symbology (RGB)

Acceptability and action needed

(CompNum)

7-9

CompNum >=7 AND <=9

255/0/0

High Priority

Low Priority

No Data

4-6

1-3

CompNum >=4 AND <=6

CompNum >=1 AND <=3

CompNum = 0

197/0/255

255/255/0 Usually accepted. Treatment requirements and responsibility to be defined to maintain or reduce risk.

255/255/255

Unsurveyed areas in terms of hazard susceptibility or hazard is not present in the areas.

172

134

548

Hanigad Island

Hikdop Island

Poneas Island, Del Carmen 303

Awasan Island

Sibale Island Island

303

Pilar

Santa Monica

M ANUAL

335

Tona Island, Del Carmen

M AINSTREAMING DRR/CCA

FOR

P ROVINCIAL D EVELOPMENT

Nonoc Island

P HYSICAL F RAMEWORK P LANS

AND

105

Island, Pilar

242

Poneas Island

Gen. Luna Rasa Island

Provincial Boundaries Road Network Spot Elevation Rivers

346

Kabo Island Mangrove Island

BASE DATA LEGEND

274

Dapa

Sugbu Island

Load Island

Hinatuan Island

Bayagnan Island

Lamagon Island Island Surigao City

Abanay Island

Figure H-3 Sample composite risk prioritization map for rain induced landslide, Province of Surigao del Norte, CARAGA Region. Daco Island

Talavera Island 185

Maanoc Island

271

SPHEROID.................................................... PROJECTION.........................UNIVERSAL TRA VERTICAL DATUM......................................... HORIZONTAL DATUM...................................

207

Laonan Island

Bancuyo Island

Caye Island Socorro Ondona Island Masapelid Island, Tagana-an

Middle Bucas Island 291

Mahaba Island

Casulian Island

125°30'0"E

303 540

Cagdianao

199

333 Dinagat

Sumilon Island

Poneas Island, Del Carmen 303

548

346 Hinatuan Island

Bayagnan Island

Lamagon Island Island

271

Cabgan Island

Talavera Island 185

Maanoc Island

Caye Island

313

Socorro

457

745

Dinago Island

939

209 Bonga Island

init

PRIORITY RANKING

457

Mainit

Island, Gigaquit

No Data Low Priority High Priority Urgent

Lajanosa Island

Anajauan Island

245

Cabgan Island

Mamon Island Antokon Island

282

209 Bonga Island

9°30'0"N

854

Anajauan Island

245

Cabgan Island

180

854

209 Bonga Is land

Map Sources:

Bucas Grande Island Lajanosa Island

Anajauan Is land

245

Cabgan Island Is land, Gigaquit

282

Map Sources:

SURIGAO DEL NORTE

Bacuag

Mines and Geosciences Bureau, Rain-induced landslide hazard map Amaga Is land

Map prepared by:

366

Alegria

854

Claver

Map prepared by:

159

1170 242

242

137 661

225

360

AGUSAN DEL NORTE 1128

661

SURIGAO DEL SUR

945

1187 360 SURIGAO DEL SUR

945

1168

225

1168

Alegria

854

Date Published: Month 2011

Risk to Agriculture, Fisheries and 405 Claver Forestry areas 159

Risk to Gigaquit Population 975

Risk to Urban areas

1170 125°30'0"E

COMPOSITE RISK PRIORITIZATION POPULATION LANDSLIDE INDUCED RAIN TO FOR RISK FROM RAIN INDUCED LANDSLIDES

126°0'0"E

276

Kotkot Island, Basilisa

242

303

Basilisa (Rizal)

Provincial Government of Surigao del Norte in coordination with the Nati Authority-Region 1 (NEDA-R1) under the Integrating Disaster Risk Reduct

137

1187

1168

Mines and Geosciences Bureau, Rain-induced landslide hazard map

405

975

159

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NA

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale Aling Is land

701

1170

AGUSAN DEL NORTE 1128

Mamon Island Antokon Island

Lapinigan Is land

Gigaquit

Claver

No Data Low Priority High Priority Urgent

259

Nagubat Island

405

Gigaquit

975

360

Provincial Boundaries Road Network Spot Elevation Rivers

PRIORITY RANKING

Masapelid Island, Placer

114

694

Mines and Geosciences Bureau, Rain-induced landslide hazard map

Alegria

SURIGAO DEL SUR

Middle Bucas Island 291 Casulian Island

Dinago Is land

423

Map prepared by:

242

945

BASE DATA LEGEND

183East Bucas Island, Soc orro

Placer

Administrative Boundaries, National Roads, Rivers and Spot Mainit Elevation, NAMRIA Topographic MapTubod 1:250,000 scale

Amaga Island

366

Amaga Island

225

Daco Island

Bancuyo Island

Sison

Malimono

Bacuag Aling Island

1187

Gen. Luna

274

Abanay Island

982

Map Sources:

159

Taganaan

939

1052

282

137 661

Mamon Island Antokon Island

Lapinigan Island

701

Dapa

271

Mahaba Island

Opong Island

457

Island, Gigaquit

1170

AGUSAN DEL NORTE 1128

No Data Low Priority High Priority Urgent

Bucas Grande Island Lajanosa Island

405 Claver

PRIORITY RANKING

259

Nagubat Island

Aling Island

Map prepared by:

Mamon Island Antokon Island

Anajauan Island

Socorro Ondona Is land Masapelid Island, Tagana-an

745

Masapelid Island, Placer

114

SURIGAO DEL NORTE

366

346 Hinatuan Island

Talavera Island 185

313

Middle Bucas Island 291

Mines and Geosciences Bureau, Rain-induced landslide hazard map Amaga Island

Gigaquit

Sugbu Is land

Bayagnan Island

Maanoc Is land

VERTICAL DATUM............................................. MEAN SEA LEVEL HORIZONTAL DATUM........................................... LUZON DATUM

242

Poneas Island

Lamagon Island Is land

SPHEROID............................................................. CLARKE 1866 PROJECTION.........................UNIVERSAL TRANSVERSE MERCATOR

Pilar

Is land, Pilar

Load Is land

Casulian Island Dinago Island

423

207

Tona Island, Del Carmen

Kabo Island Mangrove Island

Surigao City

San Franc isco

Placer

Malimono Mainit NAMRIA Topographic Map 1:250,000 scale Administrative Boundaries, National Roads, Rivers and Spot Elevation, Tubod

Aling Island

366

Alegria

975

180

Sison

694

Lajanosa Island

Laonan Island

Rasa Island

Provincial Boundaries Road Network 395 Spot Elevation Rivers

Daco Island

183East Bucas Island, Socorro

982

Map Sources:

Bacuag

Tubod

701

548 Santa Monica

335

Caye Island

457

282

Abanay Island Bancuyo Island

Mahaba Island

Opong Island

Taganaan

939

1052

Lapinigan Island

SURIGAO DEL NORTE

Malimono

Bucas Grande Island

Lapinigan Island

Bacuag

Tubod

745

Casulian Island

259

Nagubat Island

114

694

245

271

Socorro Ondona Island Masapelid Island, Tagana-an

Island, Gigaquit

Masapelid Island, Placer

423

Placer

1052

346 Hinatuan Island

Talavera Island 185

313

225

Poneas Island, Del Carmen 303

Awasan Island

Hanigad Island

µ Kilometers

Kangbangyo Island

334

172

134 Sibale Island Island

139

BASE DATA LEGEND

274

Dapa

Sugbu Island

Bayagnan Island

1:315,000

San Isidro

Cawhagan Island Meganc ub Island

Nonoc Is land

Gen. Luna Rasa Island

Maanoc Island

VERTICAL DATUM............................................. MEAN SEA LEVEL HORIZONTAL DATUM........................................... LUZON DATUM

Island, Pilar

242

Poneas Island

REGION 13- CARAGA

San Benito 204 Poneas Island, San Benito Halian Island

No Data Low Priority High Priority Urgent

PROVINCE OF SURIGAO DEL NORTE

183

Kangun Island

196

303 SPHEROID............................................................. CLARKE 1866 Hik dop Island PROJECTION.........................UNIVERSAL TRANSVERSE MERCATOR

Pilar Tona Island, Del Carmen

Lamagon Island Island

Sumilon Island

207

Laonan Island

Load Island

Surigao City

San Francisco

Middle Bucas Island 291

982

Poneas Island, Del Carmen 303

548 Santa Monica

335

Kabo Island Mangrove Island

395

225

Kangbangyo Island

334 Awasan Island

Hanigad Island

Dinagat

West Cabalian Island

Danaon Island

Caye Island

Sison

SURIGAO DEL NORTE

Provincial Boundaries Road Network Spot Elevation Rivers

Daco Island

Bancuyo Island

183East Bucas Island, Socorro

Mahaba Island

Opong Island

Abanay Island

180

Ondona Island Masapelid Island, Tagana-an

Taganaan

1:315,000

Kilometers

139

BASE DATA LEGEND

274

Dapa

Sugbu Island

Load Island

Surigao City

172

134 Sibale Island Island

199

333

Lingig

Capaquian Island

REGION 13- CARAGA

San Isidro

Cawhagan Island Megancub Island

Nonoc Island

Gen. Luna Rasa Island Kabo Island Mangrove Island

395

Hikdop Island

139

San Francisco

0Sumilon Island

VERTICAL DATUM............................................. MEAN SEA LEVEL HORIZONTAL DATUM........................................... LUZON DATUM

Island, Pilar

242

Poneas Island

Burgos Cagdianao

PROVINCE OF SURIGAO DEL NORTE

183

San Benito 204

Poneas Island, San Benito

Halian Island

SPHEROID............................................................. CLARKE 1866 303 PROJECTION.........................UNIVERSAL TRANSVERSE MERCATOR

Pilar Tona Island, Del Carmen

Nonoc Island

114

207

Laonan Island Santa Monica

259

Kangun Island

196

San Jose

Unib Island Sibanac Island

Bucas Grande Island

West Cabalian Island

Danaon Island

335

694

µ Kilometers

225

Kangbangyo Island

334 Awasan Island

Hanigad Island

199

Dinagat

1:315,000

San Isidro

Cawhagan Island Megancub Island

172

134 Sibale Island Island

303

Hikdop Island

Placer

Lingig

Capaquian Island

REGION 13- CARAGA

San Benito 204

Poneas Island, San Benito

Halian Island

333

PROVINCE OF SURIGAO DEL NORTE

183

Kangun Island

Nagubat Island

196

Burgos Cagdianao

Sta. Monica

490

170

9°30'0"N

Lingig Capaquian Island

West Cabalian Island

Danaon Island

AGGREGATED TO MUNICIPAL/CITY LEVEL

631

San Jose

Unib Island

Sibanac Island

PRIORITY RANKING

540

AGGREGATED TO MUNICIPAL/CITY LEVEL

Sta. Monica

490

170

10°0'0"N

Burgos

RISK TO BUILT-UP RESIDENTIAL PROPERTY FROM RAIN INDUCED LANDSLIDES

126°0'0"E

303

Basilis a (Rizal)

540 631

Sta. Monica

490

San Jose

Sibanac Island

125°30'0"E

Kotkot Island, Basilis a

Basilisa (Rizal) AGGREGATED TO MUNICIPAL/CITY LEVEL

631

209 Bonga Island 170

Unib Island

RISK TO AGRICULTURAL 276PROPERTY FROM RAIN INDUCED LANDSLIDES

126°0'0"E

303

Kotkot Island, Basilisa

Masapelid Island, Placer

Basilisa (Rizal)

10°0'0"N

RISK TO POPULATION FROM RAIN INDUCED LANDSLIDES 276

126°0'0"E

276

Kotkot Island, Basilisa

423

9°30'0"N

125°30'0"E

Dinago Island

9°30'0"N

Opong Island

Taganaan

183East Bucas Island, Socorro

180

10°0'0"N

313

540

AGGREGATED TO MUNICIPAL/CITY LEVEL

631

137 1187 490

333

Lingig Capaquian Island

Burgos

SURIGAO DEL SUR

Cagdianao

945

Sta. Monica

225

360

San Jose

Sibanac Island

10°0'0"N

AGUSAN DEL NORTE 170 1128 Unib Island

199

Dinagat

REGION 13- CARAGA

San Benito 204

196

Sumilon Island

Cawhagan Island Megancub Island

Kilometers

225

Kangbangyo Island

334 172

134

Poneas Island, Del Carmen 303

Awasan Island

Sibale Island Island

303

548

Hanigad Island

Hikdop Island

1:315,000

San Isidro

Poneas Island, San Benito Halian Island

Danaon Island

Pilar

Island, Pilar Nonoc Island

139

Gen. Luna Rasa Island

Dapa

Sugbu Island

Mangrove Island

BASE DATA LEGEND

274

346

Load Island

Hinatuan Island

Bayagnan Island

Lamagon Island Island Surigao City

271

Talavera Island 185

Maanoc Island

242

Poneas Island

Kabo Island

Date Published: Month 2011 CLARKE 1866 SPHEROID............................................................. PROJECTION.........................UNIVERSAL TRANSVERSE MERCATOR VERTICAL DATUM............................................. MEAN SEA LEVEL HORIZONTAL DATUM........................................... LUZON DATUM

Tona Island, Del Carmen

335

395

207

Laonan Island Santa Monica

PROVINCE OF SURIGAO DEL NORTE

183

Kangun Island

1168 West Cabalian Island

Abanay Island

Provincial Boundaries Road Network Spot Elevation Rivers

Daco Island

Bancuyo Island

Caye Island

313

San Francisco

745

Socorro Ondona Island Masapelid Island, Tagana-an

Middle Bucas Island 291

Mahaba Island

Opong Island

Taganaan

Casulian Island Dinago Island

939

183East Bucas Island, Socorro

180

PRIORITY RANKING

Masapelid Island, Placer

209 Bonga Island

423

No Data Priority High Priority Urgent

Sison

259

Nagubat Island

Bucas Grande Island Lajanosa Island

982 Placer

1052

114

694

457 SURIGAO DEL NORTE

Malimono

Mainit

Tubod

Anajauan Island

245

Cabgan Island Island, Gigaquit

Mamon Island Antokon Island

282

Map Sources:

Lapinigan Island Bacuag

Administrative Boundaries, National Roads, Rivers and Spot Elevation, NAMRIA Topographic Map 1:250,000 scale Aling Island

Mines and Geosciences Bureau, Rain-induced landslide hazard map Amaga Island

701

Map prepared by:

366

9°30'0"N

661

Alegria

854 405

Gigaquit

975

Claver

159

1170 242

137 661

AGUSAN DEL NORTE 1128

1187 360

225

SURIGAO DEL SUR

945 1168

Date Published: Month 2011

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Consequence in terms of fatality

ANNEX J

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Annex J: Consequence in terms of fatality Procedures for consequence estimation is a deterministic quantitative approach to loss estimation. This section will focus on event specific seismic hazards such as ground shaking, liquefaction, earthquake induced landslide, tsunami and will also cover volcanic related hazards such as lava flows, pyroclastic flows, and lahar. Consequence in terms of fatalities is expressed as the direct fatalities arising from a particular event. Fatality Consequence Estimation Prepare the Barangay Administrative exposure map with the necessary attribute field Similar to risk estimation, consequence estimation in terms of fatality will require the necessary exposure and hazard maps. In the case of seismic hazards, separate consequence estimates will be prepared for each scenario. 1. Prepare a province wide barangay aggregated population density Map. The Barangay aggregated map should have the minimum attribute fields and data (refer to table J-1). 2. Encode the necessary values for the PSGC and reference name of the various administrative levels. The standard codes can be derived from the official NSCB 3. Encode the barangay population and average household size. 4. Compute for the area of the barangay. Select the BrgyArea field header and use the calculate

geometry tool in the attribute table options. 5. Compute for the municipal area in hectares. Populate the MunArea field with the sum of the land area of all barangays belonging to a particular municipality. 6. Compute for the population density by dividing the BrgyPopn with the BrgyArea. Prepare the hazard exposure map 7. Open your hazard map and create a new field for the reclassified hazard susceptibility code. Add a field HazCode (Text, length 10) and reclassify the raw susceptibility/ exceedance levels. Dissolve the dataset based on the HazCode and the raw susceptibility levels. The hazard dataset should also indicate areas that are not susceptible to hazards. Ideally, the hazard map should have the same geometry as your administrative map. In general, for single hazard, the HazCode will be limited to prone and not prone with a numerical hazard code of 1 and 0 respectively (refer to table J-2).

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Table J-1. Minimum data requirements for population density exposure map for consequence estimation in terms of fatality

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Regional Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

RegPSGC

TEXT, Length 50

Region Name

Name of the Region

RegName

TEXT, Length 50

Provincial Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

ProvPSGC

TEXT, Length 50

Province Name

Name of the Province

ProvName

TEXT, Length 50

Municipal/City Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

MunPSGC

TEXT, Length 50

Municipal/City Name

Name of the City or Municipality

MunName

TEXT, Length 50

Municipal Area

The computed area based on the GIS geometry expressed in sq. kilometers or hectares.

MunArea

Float, Precision 20, Scale 8,

Municipal/City Population

Latest Population Count per Municipality or City

MunPopn

Long Integer, Precision 0

Barangay Philippine Standard Geographic Code

The Standard Geographic Code reference number for the region

BrgyPSGC

TEXT, Length 50

Barangay Name

Name of the Barangay

BrgyName

TEXT, Length 50

Barangay Area

Computed area of the barangay based on the GIS dataset geometry expressed as square kilometers

BrgyArea

Float, Precision 20, Scale 8,

Barangay Population

Latest Population Count per Barangay

BrgyPopn

Long Integer, Precision 0

Barangay Population Density

PopDen

Float, Precision 10, Scale 4,

Barangay Average Household Size

Official statistics on the household size expressed as persons per household. Values can be derived by dividing population count per barangay and the total number of households

AveHHSize

Float, Precision 10, Scale 4,

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Table J-2. Hazard code reclassification for consequence estimation.

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Hazard Code per susceptibility level in text format

This field will contain the reclassified hazard code in text format (i,e. Prone, None) based on the raw susceptibility codes of the hazard map.

HazCode

Text, Length 50

Hazard Code per susceptibility level in numerical formal

This field will contain the reclassified hazard numerical code (1, 0) based on the raw susceptibility codes of the hazard map.

HazCodeNum

Integer, precision 0

the fields to contain the estimated area affected for areas prone to the hazard, affected population, the factor of fatality, and the computed consequence (refer to table J-3). 10.Select records falling within the prone areas. In the attribute table option, use the select by attributes and enter the proper selection syntax. 11.Compute for the estimated area affected in hectares using the calculate geometry tool and input the values in the AfAreaPro field.

Table J-3. Attribute data fields for consequence estimation in terms of fatality

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Affected areas for prone areas

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in square kilometers

AfAreaPro

Float, Precision 20, Scale 8,

Affected population for prone areas

This field will contain the estimated number of population affected based on the computed area and population density

AffPopPro

Float, Precision 20, Scale 8,

Factor of fatality for prone areas

Factor indicating the number of ratio of deaths to affected persons based on historical records.

FFPro

Float, Precision 20, Scale 8,

Estimate consequence for prone areas

The estimated deaths based on the affected persons and factor of fatality

ConsqPro1

Float, Precision 20, Scale 8,

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Table J-4. Recommended symbologioes for individual areas and municipal level consequence values. Range Values for Consequence

Level

Label

Symbology (RGB)

No Data

No Deaths

> 0 to <= 100

Equal or less than 100 fatalities

>100 to 250

Above 100 to 250 fatalities

255/181/189

>250 to 500

Above 250 to 500 fatalities

197/0/255

>500 to maximum value

Above 500 fatalities

12.Encode the factor of fatality in the FFPro field. 13.Compute for the consequence by multiplying the values in the AffPopPro and FFPro. 14.Prepare a consequence estimation scenario map for individual areas. Follow the range values and the re c o m m e n d e d s y m b o l o g y f o r estimated consequence (refer to table J-4). Consequence estimation at the municipal level 15.Dissolve the dataset at the municipal level based on the RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName, MunArea, MunPopn, BrgyPSGC, BrgyName,

255/255/255 255/255/0

255/0/0

BrgyArea, BrgyPopn, PopDen, and AveHHSize. Include a statistical field of the sum of the AfAreaPro, AffPopPro, ConsqPro and minimum value of the FFPro (refer to table J-5). 16.Prepare a consequence estimation scenario map aggregated to the municipal level. Follow the range values and the recommended symbology for the total consequence per municipality (refer to table J-4). 17.Repeat the steps for the other scenario maps. 18.Compile the results in a summary matrix presenting the computed consequence per municipality per scenario (refer to table J-6).

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Table J-5. Dissolve and statistical dissolve fields for consequence estimates at the municipal level. Field

Statistical dissolve type

Field Description

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

MunArea

The computed area based on the GIS geometry expressed in sq. kilometers or hectares.

Dissolve Field

MunPopn

Latest Population Count per Municipality or City

Dissolve Field

BrgyPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

BrgyName

Name of the Barangay

Dissolve Field

BrgyArea

Computed area of the barangay based on the GIS dataset geometry expressed as square kilometers

Dissolve Field

BrgyPopn

Latest Population Count per Barangay

Dissolve Field

PopDen

Dissolve Field

AveHHSize

Official statistics on the household size expressed as persons per household. Values can be derived by dividing population count per barangay and the total number of households

Dissolve Field

AfAreaPro

This field will contain the affected area for classified frequent events computed using the calculate geometry tool. Value is expressed in square kilometers

Sum

AffPopPro

This field will contain the estimated number of population affected based on the computed area and population density

Sum

FFPro

Factor indicating the number of ratio of deaths to affected persons based on historical records.

Min

ConsqPro

The estimated deaths based on the affected persons and factor of fatality

Sum

Table J-6. Dissolve and statistical dissolve fields for municipal level data aggregation. Estimated consequence in terms of fatalities for each scenario Municipality Scenario 1 Municipality 1 Municipality 2 Municipality 3 Municipality 4 Municipality 5 Municipality 6 Municipality 7 Municipality 8 Municipality 9 Municipality 10

Scenario 2

Scenario 3

Scenario 4

Scenario5

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Consequence in terms of property damage

ANNEX K

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Annex K: Consequence in terms of property damage This section assesses the potential damages to property as a result of an event specific hazard. This covers property damage in terms of the agricultural, fisheries and forestry assets, including its urban assets which will include the built-up, critical point facilities and lifeline utilities. Similar to the consequence estimation in terms of fatality, this section will only cover event specific seismic and volcanic hazards .Consequence in terms of property damage is expressed as the monetary value in direct damages arising from a particular event. Property damage consequence estimation for AFF and Built-up areas

necessary land use areas and total floor area to built-up ratio must be specified. Prepare the hazard exposure map

Prepare the Property Inventory Maps Similar to risk estimation, consequence estimation in terms of property damage will require the necessary exposure and hazard maps. In the case of seismic hazards, separate consequence estimates will be prepared for each scenario. 1. User can use the municipal level land use property inventory map prepared in Annex H, (preparation of the municipal aggregated exposure map, step 18) can be used for this section. The minimum attribute fields for the three feature type inventory datasets are outlined in Annex-H, table H-1 to 4. The land use inventory map should be aggregated at the municipal level, land use property types classified as AFF and built-up areas, unit cost should be included. Furthermore the

2. The scenario and hazard maps will be identical to the input hazard maps used in the consequence in terms of fatality estimation. In general, hazard codes will be limited to prone and areas not prone to the hazard. Consequence estimation for individual areas Calculation of the affected areas for non-built up areas (AFF) will be based on the derived areas in GIS. For built up areas, it will be based on the derived areas multiplied by the built-up area to Total Floor Area Ratio. 3. Union the municipal base layer with the hazard map to create the hazard exposure dataset. Save your file a Exposure_Property_(Hazard Type)_ (your province).

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Table K-2. Attribute data fields for AFF and built-up areas consequence estimation in terms of property damage FIELD

FIELD HEADER LABEL

DESCRIPTION

TYPE AND FORMAT

Computed Area

The total extent of the area affected based on the land cover map.

CompuArea

Float, Precision 20, Scale 5,

Affected areas for prone areas

This field will contain the affected area estimated using the calculate geometry tool. Value is expressed in hectares

AfAreaPron

Float, Precision 20, Scale 5,

Factor of Damage for prone areas

The factor of damage for hazard prone areas based on historical damage data.

FFProne

Float, Precision 20, Scale 5,

Estimated Consequence in terms of damage

This field will contain the estimated consequence in terms of the damage to AFF and built up areas. Use a numerical subscrpt at the negining of the field to represent the scenario.

1TotConsq

Float, Precision 20, Scale 2,

Estimated Consequence in terms of damage AFF areas

This field will contain the estimated consequence in terms of the damage to AFF and built up areas

1AffConsq

Float, Precision 20, Scale 2,

Estimated Consequence in terms of damage built up areas

This field will contain the estimated consequence in terms of the damage to AFF and built up areas

1BuConsq

Float, Precision 20, Scale 2,

Note: A numerical subscript is added in the TotConsq, AffConsq, BuConsq fields representing the scenario number specifically for seismic hazards. This will help organize field names when all scenarios are combined in the summary table. Use should change the numerical subscript when intersecting with other scenarios.

4. Open the attribute table of the exposure dataset and add six (6) additional fields to determine the estimated area of the polygon record and the estimated area affected for prone areas (refer to table K-2). 5. Compute the for the area per polygon (all records) by selecting the CompuArea field, use the calculate geometry to derive the estimated area in hectares. 6. There will be different areas estimation for built-up and non-built up areas and this will be computed in the AfareaPron field. 7. First estimate the area affected for non-built up areas. Use the select by

attributes tool and select all Prop_type classified as AFF and those that are prone to the hazard. Your selection syntax should be as follows: "Prop_Type" <> 'Built-up areas' AND "HazCode" = 'Prone' 8. In the AfAreaPron field, calculate the selected records by copying the values in the CompuArea field. 9. Estimate the area affected for built up areas. Use the select by attributes tool and select all Prop_type classified as AFF and those that are prone to the hazard. Your selection syntax should be as follows:

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"Prop_Type" = 'Built-up areas' AND "HazCode" = 'Prone' 10.Calculate the affected area for built up areas by multiplying the values in the CompuArea field multipled by the TFAtoBU field. This will calculate the actual floor area affected based on the derived land area of built up zone and the estimated total flor area and built up area ratio. Your field calculation syntax should be as follows: [CompuArea]*[TFAtoBU] 11.Encode the factor of damage for prone areas in the FFProne field. Depending on the hazard, built-up areas will have a different factor of damage from the AFF areas. Use the proper selection syntaxes to input the proper factor of damage depending on the property type. 12.In the 1TotConsq field, compute for the estimated total consequence (AFF and Built-up) by multiplying the affected area with the factor of damage. [AfAreaPron]*[FDProne]

13.S e p a r a t i n g t h e c o n s e q u e n c e estimates depending on the property type will allow municipal aggregation in succeeding steps. 14.Compute for the AFF estimated consequence by first selecting all non-built up areas using the following syntax: "Prop_Type" <> 'Built-up areas' AND "HazCode" = 'Prone' 15.Populate the 1AffConsq field with the by copying the values in the 1TotConsq field 16.Populate the 1BuConsq with the built-up estimated consequence by selecting all built-up areas using the following syntax: "Prop_Type" = 'Built-up areas' AND "HazCode" = 'Prone' 17.Copy the values in the 1TotConsq field to the 1BuConsq field. 18.Prepare a consequence in terms of property damage map for AFF and built up areas. by using the recommended range values and symbology (refer to table K-3).

Table K-3. Recommended symbologioes for individual areas and municipal level property consequence values. Range Values for Consequence

Level

Label

Symbology (RGB)

No Data

No Damage/No Data Available

10,000,000

Php 10,000,000 and Below

10,000,000 - 50,000,000

Php 10,000,000 to Php 50,000,000

255/181/189

50,000,000 - 100,000,000

Php 50,000,000 to Php 100,000,000

197/0/255

100,000,000 - 150,000,000

Php 100,000,000 to Php 150,000,000

255/0/0

255/255/255 255/255/0

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Municipal level consequence estimate for AFF and Built-up areas 19.Dissolve the property built up and AFF consequence dataset down to municipal level using the dissolve tool. Dissolve based on the RegPSGC, RegName, ProvPSGC, ProvName, MunPSGC, MunName. Create statistical fields by getting

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the sum of the 1BuConsq and 1AffConsq (refer to table K-4). Save your dataset as Municipal Consequence_(hazard type_scenario number)_(your province). This will be the polygon dataset where the rest of the consequence estimates will be linked.

Table K-4. Dissolve and statistical dissolve fields for property land use consequence estimates at the municipal level.

Field

Field Description

Statistical dissolve type

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

1BuConsq

This field will contain the estimated consequence in terms of the damage to AFF areas

Sum

1AffConsq

This field will contain the estimated consequence in terms of the damage to built up areas

Sum

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Estimate consequence for critical point facilities

as basis for the consequence estimation.

Critical point consequence estimation for individual areas Similar to property risk estimation, the consequence estimates for urban areas will be based on the total consequence of built-up areas, critical point facilities and lifeline utilities. Prepare the consequence estimates for critical point a n d a g g re g a t e t h e d a t a t o t h e municipal level.

3. Add fields that will contain the factor of damage and consequence. Use the recommended field header labels and value formats (refer to table K-5). 4. Encode the factor of damage for all records.The factor of damage will be similar to the factor of damage for built-up areas. However, special studies can be made to assign a unique factor of damage for each type of critical point facility.

1. User can use the same critical point facilities map prepared in Annex H during the risk estimation steps. In general, point facilities should have a unit cost and municipal information.

5. Compute for the consequence by first selecting all points within prone areas. The selection syntax is as follows:

2. Intersect the critical point facilities map (point feature type) with the hazard map (polygon) and save the output intersect data as point data. This will append the hazard codes to your point data which will be used

6. Compute for the values for the 1CiConsq field by multiplying the FDProne field with the UnitCost field. Your calculation syntax is as follows:

"HazCode" = 'Prone'

[FDProne]*[UnitCost]

Table K-5. Attribute data fields for consequence estimation in terms of property damage

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Factor for property damage for frequent events

Factor indicating the damage ratio to property based on historical records.

FDProne

Float, Precision 20, Scale 10,

Estimated consequence of critical infrastructure points

Estimated property consequence estimate for critical point facilities

1CiConsq

Float, Precision 20, Scale 2,

Note: A numerical subscript is added in the CiConsq, field representing the scenario number specifically for seismic hazards. This will help organize field names when all scenarios are combined in the summary table. Use should change the numerical subscript when intersecting with other scenarios.

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Municipal level consequence estimation for critical point facilities 7. Aggregate you data to the municipal level. Summarize the consequence estimates for the critical point facilities as an attribute table. The table will be combined to the municipal level land use consequence polygon file. 8. Open the attribute table, then right click any field. Select the summarize table function. Select MunName as the field to summarize, create a statistical sum of the 1CiConsq. This operation will sum all the estimated

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consequnce of all points at the municipal level. Save your summary table as CI_Consequence _ M u n i l e v e l _ ( H a z a rd t y p e a n d scenario number)_province.dbf. 9. Scrutinize the dissolved table. You will notice that all consequence for each municipality has been summed and included in the field SUM_1CiCon 10.This table will be joined with the rest of the consequence estimates in the succeeding steps. 11.Repeat the steps for the other scenarios.

Table K-6. Dissolve and statistical dissolve fields for property land use consequence estimates at the municipal level.

Field

Field Description

Statistical dissolve type

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

1CiConsq

Estimated property consequence estimate for critical point facilities

Sum

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Estimate consequence for lifeline utilities

determine which segments are prone to the hazard.

The succeeding steps will estimate the consequence for lifeline utilities. The lifeline utilities is a line feature type map. THis will be combined to the builtup areas, critical point facilities consequence estimates to compute for the total urban consequence. 12.User can use the same lifeline utilities inventory map prepared in Annex H, Estimate risk to lifeline facilities, step 14. 13.The lifeline utilities dataset in general should have the necessary road segments, unit cost and municipal information. 14.Intersect the line dataset with the polygon based hazard map. This will append the susceptibility levels (hazcodes) to the line data to

15.Add fields that will contain the affected road segment in terms of length, factor of damage and the consequence. Use the recommended field header labels and value formats (refer to K-7). 16.Calculate the length of road per record for prone areas. First select the all roads that are within hazard prone areas. The selection syntax is expressed as: "HazCode" = 'Prone' 17.Use the attribute table calculate geometry function to derive the affected road length expressed in linear kilometers. Calculate the length in the AffRoad field. 18.Input the factor of damage for prone areas for all records. The factor of damage will be similar to the built-up areas factor of damage. However,

Table K-7. Attribute data fields for consequence estimation in terms of lifeline utilities

FIELD

DESCRIPTION

FIELD HEADER LABEL

TYPE AND FORMAT

Affected road

Affected area expressed as linear kilometers of road

AffRoad

Float, Precision 20, 6

Factor for property damage for prone areas

Factor indicating the damage ratio to roads based on historical records.

FDFreq

Float, Precision 20, Scale 10,

Estimated consequence in terms of property damage

Estimated consequence for lifeline utilities.

1RdConsq

Float, Precision 20, Scale 2,

Note: A numerical subscript is added in the RdConsq, field representing the scenario number specifically for seismic hazards. This will help organize field names when all scenarios are combined in the summary table. Use should change the numerical subscript when intersecting with other scenarios.

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special studies can be made to determine the factor of damage applicable for lifeline utilities depending on the hazard. 19.Compute for the consequence for lifeline utilities within prone areas. Consequence shall be expressed in philippine pesos. In the 1RdConq field, multiply the estimated affected length with the unit cost and the factor of damage. USe the calculation syntax: [AffRoad]*[FDProne]*[UnitCost] 20.The computed consequence will be the value of direct damages to lifeline utilities. Municipal level consequence estimation for lifeline utilities 21.Similar to critical point, the estimated consequence per segment should be summarized at the municipal level. User can use the statistical table dissolve to prepare a municipal level consequence estimate for lifeline utilities.

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22.S u m m a r i z e t h e c o n s e q u e n c e estimates for the lifeline utilities. Open the attribute table, then right click any field. Select the summarize table function. Select MunName as the field to summarize, create a statistical sum of the 1RdConsq. (refer to table K-8) This operation will sum all the estimated consequence of all roads at the municipal level. Save your summar y table as Rd_Consequence__Munilevel_ (Hazard type and scenario number) _province.dbf. 23.Scrutinize the dissolved table. You will notice that all consequence for each municipality has been summed and included in the field SUM_1RdCon field. 24.This table will be combined with the municipal level estimates for built-up and critical point facilities to determine the total urban consequence. 25.Repeat the steps for the other scenarios.

Table K-8. Dissolve and statistical dissolve fields for property lifeline utilities consequence estimates at the municipal level.

Field

Field Description

Statistical dissolve type

RegPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

RegName

Name of the Region

Dissolve Field

ProvPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

ProvName

Name of the Province

Dissolve Field

MunPSGC

The Standard Geographic Code reference number for the region

Dissolve Field

MunName

Name of the City or Municipality

Dissolve Field

Estimated consequence for lifeline utilities.

Sum

1RdConsq

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Municipal aggregated consequence for AFF and urban assets Additional geoprocessing and table joining is needed to determine the total consequence to urban areas. The consequence estimates derived from the land use consequence estimates (polygon dataset) is only limited to builtup areas and agricultural, fisheries, and forest (AFF). It does not include the consequence estimates for critical point facilities and lifeline utilities and these should be added to the total consequence for built-up areas to determine the total urban consequence. Organize your datasets. User should have prepared the polygon based feature type municipal aggregated consequence for AFF and built-up, and a summary consequence table for critical point facilities, and lifeline utilities.

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28.Right click the and click open to view the attribute information. Scrutinize the attribute tables and determine if the municipal PSGC or municipal names are present. This will be the field that will be used as basis for table joining when you add these tables to the polygon type municipal aggregated consequence estimates for land use (polygon feature type). 29.Proceed with the table joining, Use the municipal consequence land use dataset where all the table will be joined. 30.Open the attribute table, click options, use the “Join and Relates” option and use the join tool. User will be prompted to the Join Data Window. 31.In the Join Data Window, select Join attribute from a table in the “What do you want to join to this layer” drop down menu.

Table joining for municipal level consequence estimation for AFF and urban assets

32.Select MuniName in the “Choose the field in this layer that the join will be based on”

26.Join the consequence estimates of the critical point facilities and lifeline utilities (table format) with the Municipal Consequence_LandUse_ (hazard type)_(your province).shp dataset. Use the municipal PSGC or Municipal names as the basis of the join.

33.Select CI_ Consequence_Munilevel_ (Hazard type and scenario number) _province.dbf. in the “Choose the table to join to this layer” (this is pertaining to the dbf table)

27.O p e n t h e C I _ C o n s e q u e n c e _ Munilevel_(Hazard type and scenario number)_province.dbf. and the Rd_Consequence__Munilevel_ (Hazard type and scenario number) _province.dbf. You will notice that the tables were added in the Table of Contents and has shifted to the Source Data Tab.

34.Select the MuniName field in the “Choose the field in the table to base the join on” (this pertains to the field in the dbf table where the municipal names codes are located which will be the basis for the table record matching. 35.Use the keep all records (If there are records where matching can not be made, unmatched records will contain a null values for all fields being appended in to the target

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table from the join table). Execute the table join. 36.Scrutinize the results of the matching by opening the attribute table of the Municipal Consequence_LandUse_ (hazard type)_(your province).shp. You should have an expanded attribute table with the all the values and fields from your polygon dataset and your critical point facilities table. Make sure of the matching of municipal names. User should have the SUM_1BuCon, SUM_1AffCo and SUM_1CiCon fields present in the expanded table. 37. Repeat the steps and join the lifeline consequence table to your expanded table. Similar to the critical point consequence table, the municipal PSGC or names will be the basis of the join. 38.Once the table has been expanded, make sure that all property type consequence estimates are present per municipality. These will be SUM_1CiCon, SUM_1RdCon, SUM_1BuCon and SUM_1AffCo 39.Since the expanded table as a result of the table joining is not permanent, export the Municipal Consequence_LandUse_(hazard type)_(your province).shp as a new dataset and change the file name to

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Municipal Consequence_(hazard type)_(scenario number)_(your province).shp 40.Once exported, add the additional field that will contain the urban consequence estimates per municipally by getting the sum of the built up areas, critical point and lifeline utilities. Name the field 1UrConsq (Float, Precision 20, Scale 2). Calculate the urban consequence 41.Click the 1UrConsq field and calculate the sum of all urban consequence. The calculation syntax is as follows: [SUM_1CiCon]+[SUM_1RdCon]+ [SUM_1BuCon] 42.Prepare two additional municipal level consequence maps. Prepare separate maps for consequence in terms of damage to AFF and Urban assets using the prescribed value range and symbologies (refer to table K-2). 43.Repeat the steps for the rest of the scenarios. 44.Prepare a summary table of the municipal level consequence estimates (refer to table K-9).

Municipality 10

Municipality 9

Municipality 8

Municipality 7

AFF

Built-up

Critical Facilities

Lifeline Utilities Urban

AFF

Built-up

Critical Facilities

Lifeline Utilities Urban

AFF

Built-up

Critical Facilities

Lifeline Utilities Urban

AFF

Built-up

Critical Facilities

Lifeline Utilities Urban

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Urban

Scenario 4

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Municipality 5

Lifeline Utilities

Scenario 3

Municipality 4

Critical Facilities

Scenario 2

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Municipality 3

Municipality 2

Built-up

Scenario 1

FOR

Municipality 1

Municipality

Table K-9. Sample municipal level summary consequence table

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