Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Include r.grow.distance as a continuous alternative to r.buffer #23

Open
wenzeslaus opened this issue Feb 26, 2016 · 1 comment
Open

Comments

@wenzeslaus
Copy link
Member

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:

g.region raster=landuse96_28m -p
r.buffer roadsmajor output=roads_buffers distances=250,500,2500
r.mapcalc "noise = if(landuse96_28m==1 || landuse96_28m==2, roads_buffers, null())"
r.colors noise color=ryg

http://ncsu-osgeorel.github.io/geospatial-modeling-course/grass/buffers_cost.html
https://grass.osgeo.org/grass70/manuals/r.grow.distance.html

@wenzeslaus
Copy link
Member Author

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.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

1 participant