Open wenzeslaus opened 8 years ago
Perhaps the combination of noise and schools can be done once using a classified buffer (r.buffer) and once distance (r.grow.distance) and then classified later or not at all. However, the exercise would make the point only if some of the actual distances is a close to initial buffer sizes (e.g. school in 251 m falling into 250-500 category). We could also compute a difference of buffer size (or middle of the interval, i.e. (500 - 250) / 2 + 250
for the second interval) and actual distance (stored in a table or as raster) to see how far is the category from the actual distance.
The buffers and cost assignment for GRASS GIS uses r.buffer. In the example with roads, it would be good to include r.grow.distance as well and let students compare the results (perhaps also with the cost to roads). Here is the current example with r.buffer:
http://ncsu-osgeorel.github.io/geospatial-modeling-course/grass/buffers_cost.html https://grass.osgeo.org/grass70/manuals/r.grow.distance.html