RECONNECTING RIVER CHARLES, CAMBRIDGE, MA Data Interpretation: Four Criteria for Urban Intervention Locations Tong Wu CPLN503
Proposal and Criteria Based on the first Data Preparation Project, this Data Interpretation Project will explore the relationship between the River Charles and Camridge’s urban fabric (including existing public open space, building uses and street network) and how this relationship may influence the ways different groups of people access the river and use it.
Criteria
Recreational Open Space Access
Social: Income, Population Density and Crime Land Use: Activity Level and Opportunity Site Transportation: Street Connection
Data
File type
Then, based on the analysis, the key objective of this project is to identify the location where the urban fabrics should be improved to connect people to the river. After this project, the types of interventions on different locations will be determined in future project. The Criteria and Shapefile as well as skills used is as follow.
Purpose
2010 Census Block Group with Population Data
shapefile
analysis base
Recreation Location
shapefile
basemap
Open space
shapefile
basemap
Waterbodies
shapefile basemap and reference
Income
Tools Used Table Join, editing, field calculator, spatial join, union intersect, selection Buffer, Mesurement: area, intersect, union Union, spatial join, centroid, interpolation spatial join
Data Source Cambridge GIS Data; American Factfinder Cambridge GIS Data Cambridge GIS Data Cambridge GIS Data
csv
correlation analysis
table join, regression
American FactFinder
shapefile
public safety analysis
spatial join, field calculator
Open Data Cambridge
Land Parcel
shapefile
Land use and activity level analysis
dissolve, score, multiple part to single part, selection, spatial join, statistics
Cambridge GIS Data
Street Central Line
shapefile
analysis base
spatial Join, dissolve, selection measurement: length
Cambridge GIS Data
Traffic speed
shapefile
road speed analysis
Crime Location
spatial join
Cambridge GIS Data
Shapfiles Produced and Related Location Selections 1. Accessible Recreational Open Space per Capita
2. Monthly Crime Rate per 1000 Population
Legend HYDRO_WaterBodies HYDRO_WaterBodies
Rec_Capita
Crime_Rate
.000000 - 5.000000 5.000001 - 20.000000
.000000 - .965251
20.000001 - 40.000000
.965252 - 2.446980 2.446981 - 4.284950
40.000001 - 80.000000
4.284951 - 8.744040
80.000001 - 160.000000
8.744041 - 18.028799
160.000001 - 400.000000
18.028800 - 30.888000
400.000001 - 1600.000000 HYDRO_WaterBodies BOUNDARY_CityBoundary
Rec_Access_Deficiency Rec_Capita .000000 - 5.000000
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5.000001 - 20.000000
HYDRO_WaterBodies
20.000001 - 40.000000
Selected_high_crime_block
40.000001 - 80.000000
BOUNDARY_CityBoundary
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Open Space Deficiency
3. Activity Area: Distance to Riverfront
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High Crime Rate Area
4. Street with Mean Speed
DisToR
.000000 - 693.746377 693.746378 - 1478.713424 1478.713425 - 2422.606400
MEAN_SPEED
2422.606401 - 3371.577795 3371.577796 - 4322.697758
16.000000 - 23.500000
4322.697759 - 5661.963436
23.500001 - 27.055556
5661.963437 - 7485.827308
27.055557 - 29.764706
7485.827309 - 9740.042860
29.764707 - 33.333333
HYDRO_WaterBodies selection
33.333334 - 40.000000
BOUNDARY_CityBoundary
HYDRO_WaterBodies
MEAN_SPEED
BOUNDARY_CityBoundary
20.000000 - 24.000000 24.000001 - 27.000000
HYDRO_WaterBodies selection
27.000001 - 29.733333
Selected Site
29.733334 - 32.333333
opportunity
32.333334 - 38.555556
Existing
Activity_Corridor
selected blocks near river
HYDRO_WaterBodies selection
BOUNDARY_CityBoundary
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Selected Site within Average Distance
BOUNDARY_CityBoundary
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Street Connection to Riverfront
1. Recreational Open Space Accessibility by Block Group Tools: Buffer, Union, Intersect Legend
Legend
Legend
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recreationa area
Recreation
RecBuffer
HYDRO_WaterBodies
HYDRO_WaterBodies
RECREATION_GreenSpace
RECREATION_GreenSpace
BOUNDARY_CityBoundary
BOUNDARY_CityBoundary
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Step 1: import the Recreational Open Space point shapefile and Green Space polygon shapefile; prepare to use the Block Group shapefile
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Blockgroup2010 Blockgroup2010 HYDRO_WaterBodies BOUNDARY_CityBoundary
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Step 2: use tool GeoProcessing > Buffer: to get Step 3: use tool GeoProcessing > Union to comthe polygons highlighting the accessible and ben- bine the GreenSpace shapefile and buffer results, as the Recreational Area efit area of the recreational points (<100m)
Legend rec intersect
Legend
Blockgroup2010
rec union
Blockgroup2010
HYDRO_WaterBodies
HYDRO_WaterBodies
BOUNDARY_CityBoundary
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Step 4: use GeoProcessing > Union again, for layer Recreational Area and the BlockGroup 2010, in order to split up the Recreational Area shapefile by the block group boundaries; the output is called Rec Union
BOUNDARY_CityBoundary
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Step 5: use GeoProcessing > Intersect, for layer Rec Union from Step 4 and the Recreational Area again, to keep the recreational area only. Now there are the recreational area polygons split by block groups boundaries: the output is called Rec Intersect
1. Recreational Open Space Accessibility by Block Group Tools: Measurement Area, Spatial Join (Contain), Centroid, Interpolation Recreation Open Space Area by Block Group Legend HYDRO_WaterBodies
Rec_Area .000000 - 5805.500000 5805.500001 - 19492.400391 19492.400392 - 52452.101563 52452.101564 - 99871.203125 99871.203126 - 172932.000000 172932.000001 - 369197.000000 369197.000001 - 666354.000000 666354.000001 - 1611760.000000
¯ Step 6: create a new field in Rec Intersect’s attribute table and use Calculate Geometry > Area, to get the land area for each recreational polygon
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Step 7: ArcTool Box > Analysis Tool > Overlay > Spatial Join, to join the Rec Intersect on the Target Feature Blockgroups with Contain Option and Merge Rec Area by its Sum. Show the result as the up right map ------ ^
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Open Space IDW & Density
Legend HYDRO_WaterBodies
opensidw Value
High : 6.83859e+006 Low : 126.309
osden Value
Step 8: the map can be compared with the Interpolation map and Density Map made by: a) Calculate Geometry > Centroid and Area for Green Space polygon shapefile; b) ArcToolBox > Spatial Analyst > Interpolation > IDW for the green space area; c) Kernel Density in Spatial Analysis Tool for the recreational open space location poin; d) display both maps in 50% transparency. The map is shown on the right ------>
High : 0.630529 Low : 0
BOUNDARY_CityBoundary
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1. Recreational Open Space Accessibility by Block Group Tools: Field Calculator, Select by Attributes Accessible Recreation Legend Area per Capita HYDRO_WaterBodies
Rec_Capita .000000 - 5.000000 5.000001 - 20.000000 20.000001 - 40.000000 40.000001 - 80.000000 80.000001 - 160.000000 160.000001 - 400.000000 400.000001 - 1600.000000
Step 9: add a new field called Rec_Capita, for the shapefile made in Step 7 by spatial join: use Field Calculator, to calculate the accessible recreational area per person in each block groups: the result is presented on the right ------->
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Open Space Access Deficiency HYDRO_WaterBodies BOUNDARY_CityBoundary
Rec_Access_Deficiency Rec_Capita .000000 - 5.000000 5.000001 - 20.000000 20.000001 - 40.000000 40.000001 - 80.000000
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Step 10: Select by Attributes: to select the recreational open space deficient block groups (<= 80 sqm per person); export data as Rec Access Deficiency <---------These selected block groups lacking recreational open space are where the improvement in open space network should be done to serve local residents
2. Social Factor: Crime Rate by Block Group Tools: Table Edit, Spatial Join (contain)
HYDRO_WaterBodies CrimeLoc
Blockgroup2010 Blockgroup2010 BOUNDARY_CityBoundary
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Step 1: import the point shapefile of Crime Location in the past month (added by XY geocoding in Data Preparation) and start editting the table by adding a field Crime Count with the count 1 for each. <--------
HYDRO_WaterBodies
CriCount 0-1 2-3 4-5 6-7 8-9 10 - 12 13 - 15 16 - 28
Step 2: ArcTool Box > Analysis Tool > Overlay > Spatial Join, join the sum of crime counts of each block groups that contains these point. The result, Crime Counts in each block group is shown as the right ------>
Monthly Crime Count by Block Groups
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2. Social Factor: Crime Rate by Block Group Tools: Field Calculator Monthly Crime Rate (per 1000) by Block Group HYDRO_WaterBodies
Crime_Rate .000000 - .965251 .965252 - 2.446980 2.446981 - 4.284950 4.284951 - 8.744040 8.744041 - 18.028799 18.028800 - 30.888000
ÂŻ Step 3: add new field as Crime Rate, use Field Calculator, to calculate the monthly crime count per 1000 population in each block groups
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Step 4: adjust Symbology to show the result as above.
2. Social Factor: Crime Rate by Block Group Tools: Table Join, Regression HYDRO_WaterBodies
DEMOGRAPHICS_BlockGroups2010 Income / none .00000000 .000000001 - 41389.0000 41389.0001 - 71935.0000
Step 6: ArcToolbox > Spatial Statistics Tools > Modeling Spatial Relationships > Ordinary Least Squares, to examine the possible relationship between income level and crime rate: is it possible to reduce crime by increase economic investment.
71935.0001 - 89559.0000 89559.0001 - 113523.000 113523.001 - 154938.000 154938.001 - 242750.000 242750.001 - 1199260.00
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The Standard deviation is shown on bottom left. The report below shows the R-squared is only -0.01and P value is up to 0.75, the correlation is not reliable.
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HYDRO_WaterBodies
reg income crime StdResid < -2.5 Std. Dev. -2.5 - -1.5 Std. Dev. -1.5 - -0.5 Std. Dev. -0.5 - 0.5 Std. Dev. 0.5 - 1.5 Std. Dev. 1.5 - 2.5 Std. Dev. > 2.5 Std. Dev.
Standard Residual of Income-Crime Relationship
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Step 5: join the dbf table of income data into the Block Group layer as shown on the top left. <--------
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2. Social Factor: Crime Rate by Block Group Tools: Regression, Select by Attributes
Step 7: do the same regression modelling process again but with population density as independent variable and crime rate as dependent variable: examining the possible correlaiton between population density and crime rate. The report above shows the R-squared is higher as around 0.1 and P value is 0.0017 with a star, which means the coefficient is 98% confident no equalling to 0. Although the relationship is not very solid, it is more likely for lower density areas to have higher crime rate. Step 8: so there should be more pedestrian activities to reduce the crime, especially in high crime rate area. Select by Attributes: to select the block groups with crime rate >= 5/1000; these are the block groups where public facilities and open space should be increased. The exported shapefile is called Selected High Crime Block ------>
Selected High Crime Rate Area requiring Improvement
HYDRO_WaterBodies Selected_high_crime_block BOUNDARY_CityBoundary
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Health
Assisted Living/Boarding House
3. Landuse: Activity Level and Identifying Opportunity Sites Higher Education Industrial
Legend
Tools: Dissolve Table Edit
Government Operations
Mixed Use Industrial Health Health
Mixed Use Residential Higher Education
Assisted Living/Boarding House
Industrial
Cemetery
Mixed Use Commercial
Office
Privately-Owned Open Space Mixed Use Industrial
Education
Public Open Space
Government Residential Operations Health
Transportation
Mixed Use Residential Office Office/R&D Privately-Owned Open Space
Higher Education
Public Open Space
Industrial
Residential
Utility
Vacant Mixed Use Commercial Mixed UseMiles Education Vacant
Commercial
Utility Vacant
Mixed Use Residential
Vacant Commercial
Office
Vacant Industrial
Vacant Residential
Office/R&D
Step 2: ArcTool Box > Data Management > Dissolve, to dissolve the land parcels according to the land use category
Transportation
Mixed Use Industrial
Vacant Industrial
Step 1: import the shapefile layer of Land Use and display with adjusted symbology.
Mixed Use Education
Commercial
Education Residential
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Commercial
Mixed Use EducationEducation Residential
Office/R&D Charitable/Religious
1
Charitable/Religious
Mixed Use Commercial Education
HYDRO_WaterBodies
Category
Cemetery
Vacant Residential
Privately-Owned Open Space
<------
Public Open Space Residential
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Transportation Miles
Utility Vacant Vacant Commercial Vacant Industrial Vacant Residential
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Activity Level Map and Opportunity
HYDRO_WaterBodies
dissolve landuse Type low low medium medium medium high high opportunity
Step 3: now there are only 25 items in the Dissolve Landuse shapefile; start editting the table, assess the activity level for different land uses with score; identify public open space and vacant land as opportunity site for intervention. The activity level map is shown on the right ------>
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3. Landuse: Activity Level and Identifying Opportunity Sites Tools: Select by Attributes, Table Edit High Level Activity Corridor and Opportunity Site
Type existing open space opportunity site Activity_Corridor
land parcel land parcel HYDRO_WaterBodies
Step 4: Select by Attributes: Score >= 8 for high level activity, export as Activity Corridor
¯ Step 5: Select by Attributes: select the opportunity site, export as Opportunity Site
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Step 6: edit the table, set the type of public openspace as “existing” and the others are “opportunity” The output layers are displayed together as above map, the next step is to identity the scope of opportunity site by distance to river.
3. Landuse: Activity Level and Identifying Opportunity Sites Tools: Multipart to Single Part, Spatial Join (closest), Statistics Step 9: the join result is shown as below, with the distance to the river; use Statistics tool to see the Mean Distance is 3165 feet. It means new interventions have to be closer than 3165 feet to the river, so as to reduce the mean distance to riverfront and improve connectivity.
Step 7: Multipart to Singlepart: decompose the activity corridor into individual poligons again.
DisToR .000000 - 693.746377 693.746378 - 1478.713424 1478.713425 - 2422.606400 2422.606401 - 3371.577795 3371.577796 - 4322.697758 4322.697759 - 5661.963436 5661.963437 - 7485.827308 7485.827309 - 9740.042860 HYDRO_WaterBodies selection BOUNDARY_CityBoundary
Activity Area: Distance to River Step 8: Spatial Join: join the feature: closest to the target featuer single activity parts
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3. Landuse: Activity Level and Identifying Opportunity Sites Tools: Select by Location, Union Block Group Selections for Improvement Step 10: Select by Location: select the Open Space Deficiency Area and High Crime Blocks that are with the distance of 3000 feet to the riverfront ------>
HYDRO_WaterBodies selection Selected_high_crime_block
Rec_Access_Deficiency Rec_Access_Deficiency
These areas are where interventions can improve connection to River Charles by reducing average distance between high-level activity sites to the river
BOUNDARY_CityBoundary
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Selected Block Groups near River and Opportunity Site
Step 11: GeoProcessing > Union: combine the two selections into one shapefile called Selected Blocks near River. Overlap with the Opportunity Site layer to see the intersects; the map is shown on the right
HYDRO_WaterBodies selection
Type existing open space opportunity site selected blocks near river BOUNDARY_CityBoundary
------>
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3. Landuse: Activity Level and Identifying Opportunity Sites Tools: Multipart to Singlepart, Select by Location Selected Opportunity Site for Urban Intervention
Step 12: Multipart to Singlepart: decompose the Opportunity Site into individual poligons again.
HYDRO_WaterBodies selection
Selected Site opportunity Existing selected blocks near river BOUNDARY_CityBoundary
ÂŻ Step 13: Selection by Location: select out those opportunity sites that intersect the determined block groups near riverfront also within an distance of 100 feet (around 30m).
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Step 14: now the locations for new urban interventions, especially for recreational open space, public facility and water feature sqaure, are identified, as shown above, the opportunity site can be where new squares or public facilities will be built and the existing green space may have some upgrading programs Also, the street accessibility and connection improvement will be identified in the next section.
4. Transportation: Street Connection Assessment Tools: Spatial Join (closest)
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! ( ! ( ! ( (! (! ! ( (! ( (! ! (! ! ( ! ! ( ( ! (! ! ( ( ! ( ! ( ! (( ! ( ! (! ( ! ( (! ! ( ! ! ( ! ( ( ! ( ! ( ! ( (! ! (! ! ( ! (( ! ( ! ! (! ( ! (! (! (! ( ! (! (! (! ( ( ! ! (! ( ( !! ! ( ( ! ( ! ! ( ( ! ( ! ( ! ( ! ( ! ( ! (! ( ! ( ! ! ( ( ( (! ( ! (! ! ( ( (! ! ( ! ! (! ! (! ( ! ( ! ( ! ( ! ( ! ( ! ( ( ! ( ! ! ( ( ! ( ! ! ( ( (! ( ! (! ! (! ( ! ! ( ( ! ! (! ! (! ( (! ( ! ( ! ( ! ( ( ! ( ! ! (( ( ! ! ( ! ( (! (! ( ! ( ! ( ! ! ( (! ( ! ( ! ! ( ! (! ! ( ! ( ! ( ! ! ( ! ( ( ! ( ! ( ! ( ! ( ( ! ( ! (! ! ( ( ( (! ! ( ! ! ( ! ! ( ! ( ! ! ( ! ( ( ! ( ! ( ! ( ! (! ( ! ( ! ( ! ( ! ! ( (! ( ! (
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Step 1: import the point shapefile layers of the Traffic Speed Study points and the line shapefile of Transport Centerlines <---<---! (
Step 2: Spatial Join: join the feature of the traffic speed points into the street centerlines by the match option closest; so the street has the speed feature of its closest speed study points. The output is called Street Speed, on bottom left.
TRAFFIC_SpeedStudies TRANS_Centerlines
! (! ( (! ! ( ( ! !! ( ! ( ( ( ! (!
HYDRO_WaterBodies BOUNDARY_CityBoundary
! ( ! (
! ! ( ( ! ( ! ( ! ( ! ( ! (
! (
! ( !( ( ! ( ! !! ( ( ! ( ! ( ! ! ( ( ! ( ! ! ( ( ! ( !( ( ! ( ! ! (! ( ! ( ( ! ! (! ( ! ( ! ! ( ! ( ! ( ( ! ( ! ( ! ! ( ( ! ( ! ( ! ( ! ( ! ( ( ! ! ! ( (! ! (! ! (! (! ( ! ( (! ! ( ! ! ( ( ( ! ( ! ( ( ! ( ! ( ! ( ! (! ! ( (! ( ! ( ! ( (! (! ! ( ! ( ( (! ! ! (! (! (! ! ( ! ! ( !! ( ! (( ! ( ( (( ! ! (! ( (! ! ! ( ! ( ! ( ! ( ! ( ! (! ( ! ((! ( ! ( (! ! ( ! ( ! (( ( ! ! ! ( ! ! (! ! (( ! ( ! ( ( ! ( !! ( (! ( ! (
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! ( ! ( ! ( ! ( ! (! (
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SPEED_85TH .000000 - 21.000000 21.000001 - 24.000000 24.000001 - 27.000000 27.000001 - 29.000000
Step 3: Compare the Street Speed with Activity Corridor, it is difficult to see the street as connections when they are segments, which can be seen as below.
29.000001 - 31.000000
Activity_Corridor
SPEED_85TH
31.000001 - 33.000000
.000000 - 21.000000
33.000001 - 36.000000
21.000001 - 24.000000
36.000001 - 40.000000
24.000001 - 27.000000
HYDRO_WaterBodies
27.000001 - 29.000000 29.000001 - 31.000000
BOUNDARY_CityBoundary
31.000001 - 33.000000 33.000001 - 36.000000 36.000001 - 40.000000 HYDRO_WaterBodies BOUNDARY_CityBoundary
Street Traffic Speed
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Street Speed Compared with Activity Corridors Miles
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4. Transportation: Street Connection Assessment Tools: Dissolve Step 4: to better analyze the street connection to the river, GeoProcessing > Dissolve, dissolve the street segments by street name into complete streets. The speed is dissolved by the mean value. <------ The output is called Road Dissolve and is shown on the bottom left.
Dissolved Streets with Mean Traffic Speed MEAN_SPEED 16.000000 - 23.500000
Step 5: Compare the dissolved street with Activity Corridor, it can be observed how is the average traffic speed on streets connecting Activity Corridors and the riverfront, as below.
23.500001 - 27.055556
Dissolved Streets with Average Speed Compared with Activity Corridors
27.055557 - 29.764706 29.764707 - 33.333333
MEAN_SPEED
33.333334 - 40.000000
16.000000 - 23.500000
HYDRO_WaterBodies
23.500001 - 27.055556 27.055557 - 29.764706
BOUNDARY_CityBoundary
29.764707 - 33.333333 33.333334 - 40.000000 Activity_Corridor HYDRO_WaterBodies BOUNDARY_CityBoundary
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4. Transportation: Street Connection Assessment Tools: Select by Location, Measurement (Length) Street Connection to Riverfront MEAN_SPEED 20.000000 - 24.000000 24.000001 - 27.000000 27.000001 - 29.733333 29.733334 - 32.333333 32.333334 - 38.555556 Activity_Corridor HYDRO_WaterBodies BOUNDARY_CityBoundary
Step 6: to analyze how streets connecting riverfront, Select by Location for the streets that intersect the riverfront with the distance of 900 feet (around 300m), identifying (circle) where street regulation and pedestrian corssing improvement is in need. ------->
MEAN_SPEED 20.000000 - 24.000000 24.000001 - 27.000000 27.000001 - 29.733333
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29.733334 - 32.333333 32.333334 - 38.555556
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Activity_Corridor Miles HYDRO_WaterBodies BOUNDARY_CityBoundary
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Step 7: linear improvement along street shoud also be considered: use Calculate Geometry > Length to get the length of streets. <---<--In partucular, streets like Pearl Street, with the length of 1243, more than 1km, but connecting the main commercial corridor to riverfront, should improve its physical environment for better walking experience. <------