Dear Grass Users --

I am struggling to understand the usage of the

"solver=" option featured by both r.cost and

r.walk.

The r.walk manual page gives no details about it.

The r.cost manual page does contain an illustration

of the working principle, but no examples on how

to quantify the cells in the solver map. So it's

all a little too abstract for me.

I understand the basic premise: I have a relatively

coarse cost map, and r.cost's algorithm will often

encounter cells with many neighbours that have the

same cost. This produces ugly quantization effects

("steps") in least cost paths derived from such

surfaces. To work around this problem, I have so

far simply added some random noise to my cost

maps. However, it seems to me that the "solver="

option might be a more elegant, deterministic

solution to this problem.

So: Does anybody here have some experience with

the "solver=" option of r.cost? What kind of

values (ranges?) would a solver map contain?

How does r.cost interpret theses values (as

additional costs?). Could anyone come up with

an example of how to quantify a useful solver

map in practice?

Thanks!

Ben

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