Created
March 1, 2017 22:59
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Vector dataset -> euclidean distance | |
Method: use GDAL. | |
Was able to make it work in QGIS. But the rasterize step did not work in the command line. Proximity did. | |
$ gdal_rasterize -a Shape_Leng -ts 3000 3000 -l philly_street_lines /Users/rbernet/Desktop/philly_street_lines.shp /Users/rbernet/Desktop/raster_testing/test_rasterize.tif | |
$ gdal_proximity.py /Users/rbernet/Desktop/raster_testing/philly_lines_3.tif /Users/rbernet/Desktop/raster_testing/phil_prox_test2.tif -distunits GEO -of GTiff |
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Goal: Create a web-based weighted raster overlay using open source tools. | |
- In the easiest way possible. For a small dataset. In Python | |
Why: | |
1. To learn how this type of analysis might be performed now. | |
2. Practice Python and open source tools | |
3. Understand limitations when datasets get to be too large | |
Approach. | |
Step 1. Create a python script that starts with vector data (.shp or geojson) and calculates euclidean distance. | |
Step 2. After can do this for 1 file. Do it for 3. With same extents. | |
3: Create static weighted raster overlay. AKA - add them together to create a "prioritization map" | |
4: Get this on the web.... |
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working in QGIS:
![image](https://cloud.githubusercontent.com/assets/8103418/23485294/ce1ac134-fea8-11e6-9c18-d6b6b5059158.png)
The datasets:
https://drive.google.com/drive/folders/0B8XPTQKFTcIhYU9fUi1pemVTTUU