Raster GIS Work Samples
XINLIN HUANG University of Pennsylvania Master of City Planning ‘13 Landscape Studies ‘13
Traffic Impact Assessment for Bridge Closures Individual Assignment
3. CALCULATE COST DISTANCE TO HOSPITAL
1. ISOLATE BRIDGES FROM THE ROADS Roads
Raster Calculator -- Multiply Region Group
NoData = Penn Bridge 0= all the others
Reclassify Hospital layer to isolate Hospital, and use 3 friction layer to generate Cost Distance for each senario: Friction
Cost Distance
Reclassify Each Bridge Lanes
Current Condition
Reclassify NoData = Two Bridges 0= all the others
Water
Penn Bridge Shut-down
2. CREATE FRICTION LAYERS FOR 3 SENARIOS Since the biking speed on road is17.04545...Miles/Hour = 25ft/second, and the non road area the bikes are 10 times slower:
2 Small Bridges Shut-down
The Friction for road grid = 0.04 second/ft = 4 hundredseconds/ft The Friction for non road grid = 0.4 second/ft = 40 hundred seconds/ft Raster Calculator: Road * 0.1 + Water* 20
The Current Senario Friction 2 Small bridges Senario Friction
Reclassify into Water = NoData Roads and bridges =4 Non Roads = 40
Penn Bridge Senario Friction
Use Convertion Tools to turn the Biker Home layer into a new grid layer call “AllBikers”. Biker Pixels has the value of 1 while other grids are NoData
In Raster Calcula Multiply the “All Bikers” layer with each Cost Distan Layer Above
ator, lh nce
5. MEASURE TRAFFIC INCREASE ON THE SPECIFIED BRIDGE Cost Distance
4. CALCULATE TRAVEL TIME INCREASE
Zonal -Mean
Travel Time
245.83sec
New Layers that records Cost Distance of Bikers on each biker pixel
Zonal -Mean 4.391min
Zonal 4.820min -Mean
Zone
Increase
Penn Bridge Shut-down
17.6Sec
2 Small Bridges Shut-down
Reclassify the Road layer to get a Zone for Zonal Statistic
Flow Accumulation
6. FINAL RESULTS
Result
4
Zonal 2 -Maximum
Current Condition
N/A
43.4Sec
Flow Direction
N/A
Zonal -Maximum
2 Zonal -Maximum
22
12
8
4
20
Increased Time
Traffic flow on the specified bridge
Increased Traffic flow
4.097min
N/A
6
N/A
Penn Bridge Shut-down
4.391min
17.6s
14
8
2 Small Bridges Shut-down
4.820min
43.4s
26
20
Senario
Average Commuting Time
Current Condition
Best town to encouter a professional Clown
the
Individual Assignment This analysis is based on two assumptions: 1. In order to reduce commute time and cost, professional clowns tend to live closely to their work places. 2. Demands for clown performance are not limited to areas near clowns’ residences. Nevertheless, the demographic pattern of the areas near clowns’ residences indicated what a potential market for clowns might look like. Therefore, the characteristics of known markets can be used as parameters of identifying other potential markets for clown performance.
1. FIND OUT THE DEMOGRAPHIC CHARACTER OF CLOWNS’ MARKETS Mid-income Layer
Mid-income within Market zones
Mid-income Raster Map Interpolation - IDW
Low
income Group 60004-90003 30006-60004 90003-120001 7.589-30006 120001-150000
High
Population Density Layer
Population Density Raster Map
Population Densitywithin Market zones
Low
Interpolation - IDW
Clowns’ AvailabilityLayer Kernel Density Radius: 5miles
Clowns’ Housing - Market Zones
Low
Reclassify
High
5 4 3 2 1
Use the same operation for the Population Density Layer Population DensityGroup
High
Existing Clowns’ Residence
Reclassify into 5 income categories and use attribute table to see the count of each income group. And rank the income group based on the count:
1335-1761 55.2-482 482-908 908-1335 1761-8643
5 4 3 2 1
2. SEARCH FOR POTENTIAL MARKETS FOR CLOWN PERFORMANCE Mid-income heat map
Mid-income Raster Map
3. EVALUATE EACH TOWN’S POTENTIAL OF ATTRACTING CLOWNS Towns
Zonal Statistics - average Conversion- from polygon to raster
Reclassify according to the 5 Ranks from previous step
Population Density heat map
Population Density Raster Map Reclassify according to the 5 Ranks from previous step
High:11.305
Population Density heat map
Clowns’ AvailabilityLayer
Low:6.843
INDEX FOR ENCOUNTERING CLOWN(S) Low:4
Reclassify according to the 5 Ranks from previous step
WINNER !
High:15
Site Suitability Analysis for a New Telephone Tower Team: Xinlin Huang, Xin Ge In order to determine the potential locatioins for a new cellphone tower, we generated 6 criteria for our analysis. Each criteria was assigned different weight when calculating the final result, because they have different degrees of influence to cell -tower site selection: Weight 1. Population Density 3 2. Accessibility to roads 2 3. Ideal elevation 1 4. Distance to the shoreline 1 5. Distance to Current Towers 2 6. Current underserved zones 3 In our final map, areas marked with red represents the most likely locations for a new cellphone tower:
Existing Towers
Potential for new cell tower Low
High
1. SITING THE AREA WITH HIGHER POPULATION DENSITY Population density relates to the demand of cellphone signals. Altough we do not have the population data for this region, we believe that the density of urban roads is a good indicator for population concentration. Note: We did not distinguish the difference among roads, instead, we reclassify all the roads into one class. Then we use “Focal statistic” tool to calculate each grid’s road density environment. The Neighborhood we use is 50 * 50, which is a 500 * 500 meters square. Reclassify the result into two categories with median value(which is 104, on a range of 1-758). 1 means higher then 104, 0 means the opposite.
2. EVALUATING ACCESS TO MAINTENANCE Towers are more likely to be located in places that have good connection to roads, which provides access for cell tower maintenance Note: We use “ Euclidean Distance” to measure each grid’s distance to roads.
Reclassify: pixels from road within 100m - 500m get values of 1s, the other pixels get 0s:
3. ESTIMATING THE MINIMUM ELEVATION FOR A CELL TOWER The transmission of cellphone signal will be easily blocked by hills, which sets the demand for putting the tower at a relatively high location. We estimate the elevation of the 5 current towers, and base on our estimation we set the minimum height for our new tower. Note: Convert point to raster -> get a grid layer for the 6 towers. With this layer and elevation layer, use zonal statistics to calculate the elevation for each tower: All the towers are located at an elevation higher than 170 meters, except for one tower that locates at the elevation of 15 meters, Base on this trend, We decide to use 170 as the minnimum elevation for a new tower. Reclassify the elevation layer, pixels with elevation higher than 170 get values of 1s, while the others get 0s
4. EXCLUDING THE SEASURFACE AND SHORELINE Both shorelines and sea are no ideal location for a new cell tower. We believe that cell towers are more likely to be located on a stable ground that is less vulnerable when nature disasters, such as tunami and earthquake
Note: the dark brown area is the sea and its shoreline
Calculate each grid’s distance from the sea
Reclassify, area within 1km from the sea get values of 0s, the other get 1s
5. AVOIDING SIGNAL INTERFERENCE WITH CURRENT TOWERS A new cellphone tower will probably not locates too close to an existing tower, because the cellphone signals will interference with each other during the transmission. Also, it is economically inefficient to put a new tower near to existing ones.
Euclidean distance from towers
6. DETECTING CURRENT UNDERSERVED ZONES The transmission of cellphone signals behaves like the trasmission of light. Therefore, some valleys are more likely to be underserved because the signals are blocked by its adjacent hills. We captured the areas that current tele signals cannot reach. These underserved zones indicates a higher possibility of having a new cell tower built near them.
Use elevation layer and tower layer to generate viewshed layer
Reclassify: area within 1609m (i.e. one mile) from the towers get values of 0s, while the others get 1s`
in applying the Reclassify: visible “view shed” funcarea as 0s, invisible tion, Change OFF- area as1s SETA to 100m, add RADIUS2 as 35000m (it's GSM maximum coverage distance)
XINLIN HUANG 4420 LOCUST, PHILADELPHIA, PA 19104 1-215-882-0712
Skills and Strengths
xinlinhuang7@gmail.com
Education UNIVERSITY OF PENNSYLVANIA, SCHOOL OF DESIGN Master of City Planning in Urban Design + Certificate of Landscape Studies
May 2013
SUN YAT-SEN UNIVERSITY, SCHOOL OF GEOGRAPHY AND PLANNING Bachelor of Science in Urban/Rural Planning & Management & Resource Environment
July 2011
Exchange student in UNIVERSITY OF COLOGNE, GERMANY. Studied urban development and design strategies of deindustrialized cities under globalizaztion
Mar. - Aug. 2010
Professional Experience Intern in EMBARQ INDIA, MUMBAI OFFICE Conducted research and info-graphic design for open space design parameters as the office’s open space design guidelines; Participated in the master plan of a 158 acre new urban sector and designed 2 lake front parks, 1 neighborhood park and a playground Part-time in URBAN PLANNING & DESIGN INSTITUTE OF GUANGDONG, CHINA Participated land use impact analysis and design recommendations for future inter-city lightrail stations of Longshan Town; Accomplished regional landscape and feature plan for Nansha, a 575km2 port district of Guangzhou Intern in QUANZHOU PLANNING, DESIGN & RESEARCH INSTITUTE Conducted tourist resources evaluation and development plan for a city’s mountain district of 16000 acres, and contributed to its post-earthquake tourist trail design
May - Aug. 2012
Oct. 2010 - Feb. 2011
Jul.- Aug. 2008
+ 6 years of training focused on understanding cities through their social, economic, and political aspects + Familiar with researches for planning projects, including data mining, field study, spatialized analysis of demographic, land use, transportation and other socio-economic data + Experience of working in public and nonprofit sector + Experience in planning and design projects from regional scale to city block + Expertise and passion for visual communication + Proficiency in Adobe Creative Suite, ArcGIS, AutoCAD, MS Office ( Excel + Word +PowerPoint ), RhinoCeros, SketchUp, and V-ray
Additional Experience One of the translators for book POLITICAL GEOGRAPHY: WORLD ECONOMY, NATIONSTATE AND LOCALITY (6th edition) Research assistant for an academic project focusing on the gentrifying communities of Guangzhou
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