Hi all, I am trying to detect and summarize changes in categorical rasters.
I have two rasters. Each raster is a land use map, with values ranging from 1 to 15 and representing different land-use classes. r1 is my control scenario, and r2 is my climate change scenario where changes in climate induce changes in land use classes. Here is some example data: ## scratch a raster brick with 120 timesteps (10 years) r2 <- r1 <- brick(nrows=18, ncols=36, xmn=0, xmx=18, ymn=0, ymx=36, nl=120) ## fill some random values set.seed(4) r1[] <- round(runif(18 * 36 * 120, min=1, max=15), digits=0) set.seed(5) r2[] <- round(runif(18 * 36 * 120, min=1, max=15), digits=0) What I would like to do is for each time step (brick layer), compare each cell of r2 relative to r1 in this way: - is the value different? yes/no - if yes, what was the change? for example 1 to 10, or 2 to 7 and so on. By the end, I would like to be able to: - plot a map showing the occurence of changes - have a table with the frequency of changes in each class (i.e. 1 to 10, 2 to 7 etc) Is there any tool to perform this analysis in R? Which one? If no, what would be the best approach to implement that by myself? Thanks in advance, -- Thiago V. dos Santos PhD student Land and Atmospheric Science University of Minnesota http://www.laas.umn.edu/CurrentStudents/MeettheStudents/ThiagodosSantos/index.htm Phone: (612) 323 9898 _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
