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Data Collection
 
 

Preparatation and Manipulation

Constraints included in analysis:
Lakes and Water Bodies
Institutional
Transportation, Communication and Utilities
Industrial
Residential Single Family and Rural
Agricultural Lands

 

Factors included in analysis:
Location of existing pet shops
Location of existing daycare / boarding homes
Proximity to veteninary clinics
Proximity to parks
Proximity / accessibility to bike trails
Landuse types suitable for opening a new pet shop
Average family income
Population Density

 

 
   
  Data Collection Sources  
 

Raster files that I created for this project are: pet shop, vets, and daycare layers. First, I had to geocode all the known pet shops, vets, and day cares that were listed in the myTelus.com phonebook based on postal code. Once the postal code has been geocoded by geocoder.ca the latitude and longitude positions are recorded into a excel file with feature identification. When all the locations for the three columns are listed in the excel file it is then converted to a *.dbf format that is readily added to ArcMap. The dbf file must be in the same projection and datum as the base map in order for the locations of what I geocoded to be accurately referenced. Once data is added onto ArcMap and the projections are correct; the next step is to export it into a shapefile because a layer (*.lyr) is not sufficient and complete as shapefiles (*.shp).

 
   
  Files from Translink 2006 on the SFU S:drive - data warehouse had separate vector based files for Vancouver, Burnaby, and Richmond bike trails so I had to combine them together to create on single raster file that can be used in my spatial analysis. To join the 3 files (vantrail.vct, richtrail.vct, and bbytrail.vct) I had to first import them into IDRISI directly from a shapefile to raster format. Once imported, reclass was performed to rid the -9999 so minimum values begin at 0 and maximum is 255. The ADD module was used in this case to first combine A + B = AB and then AB + C = ABC. Landuse file is available on the SFU S: drive under "data warehouse" and in the folder "GVRD Landuse for 2003". Because the file includes all municipalities in the GVRD and I am only looking at three municipally, I used the selection option to "select new feature" based on "Name" of the municipality. Another option would be to clip the required data but since selection is possible based on name of municipality, I do not need to perform the clip function.  
   
  Census 2001 files were available on the SFU S: drive under "data warehouse" in the folder "351 - Lab 1 data.zip". Along with the census 2001.dbf is the disenumeration_areas.shp for GVRD. By joining the disenumeration_areas.shp and Census 2001.dbf based on DAUID (primary key) I can extract information about household income and population density. Because the disenumeration_area.shp consist of all regions of the GVRD I must clip my regions of interest to avoid cluttering of data and unnecessary areas to be included in my analysis.
 
   
   
 

All files used for this spatial analysis are based on:
Projected Coordinate System: NAD_1983_UTM_Zone_10N
Projection: Transverse_Mercator
False_Easting: 500000.00000000
False_Northing: 0.00000000
Central_Meridian: -123.00000000
Scale_Factor: 0.99960000
Latitude_Of_Origin: 0.00000000
Linear Unit: Meter

Geographic Coordinate System: GCS_North_American_1983
Datum: D_North_American_1983
Prime Meridian: 0
Angular Unit: Degree

  
 
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