Hi Dana,
I fear this will not earn me your undying gratitude, but have a look at
r.mapcalc and the r.mapcalc tutorial. With a little bit of script-writing
you can produce the same results as r.neighbours, and more, since it allows
you to query and process any cell neighboring the cuurent cell (in any
direction and at any distance) separately. Good luck,
Martijn
P. Martijn van Leusen -------------------------------------------------------+
Leverhulme Research Fellow, The Wroxeter Hinterland Project |
University of Birmingham Field Archaeology Unit |
Edgbaston, Birmingham B15 2TT Phone +44 121 414 5513 Fax +44 121 414 5516 |
E-mail P.M.van-Leusen@bham.ac.uk |
URL http://www.bham.ac.uk/BUFAU/Staff/vanleupm.html__________________________|
I am using hyperclustered TM imagery to map deciduous
forests in New England as part of the GAP Analysis program.
This treatment produces a large number of spectral classes which
we then reclass into our vegetation types with "i.infer". I found
that quantifying neighborhood associations increased our accuracy
and have used "r.neighbors" to identify the most frequently
occurring spectral class around each pixel. However, I need a
way to identify the second and third most frequent neighbors as
well and produce percentages of each if possible. I have tried to do
this in the MIPS sml language without much luck, being among
the programmably challenged, and would prefer to use GRASS
because it's in the public domain.Could any of you help with a modification of "r.neighbors",
either with multilayer output or as a set of programs applied in
sequence. Not only would you receive the undying gratitude of my
department, co-authors and self, but your efforts would be fully
credited in any subsequent publication.Dana Slaymaker
Department of Forestry and Wildlife Management
University of Massachusetts in Amherst
dana@fnr.umass.edu
(413) 545-4853