Dear Robert, thanks a lot for your answer. It helped me much. I used your suggested random sampling approach also for the rasterization of shapefile dataset. My results, however, seems strange (according to the patches proportion) compare to for example the standard max assignment method. Im posting the example below. Is my code for rp.random wrong?
Thanks in advance, Robert used shapefile for download http://www.geography.sav.sk/personal/pazur/data/area.zip ### library(raster) library(rgdal) #read the polygon map <- readOGR(dsn="FOLDERFORSHAPEFILE", "0_00") r <- raster(ncol=300, nrow=300) #raster extent same as map extent extent(r) <- extent(map) #categoric to numeric code_00_num <- as.numeric(as.factor(map$code_00)) #rasterization with random sampling rp.random <- rasterize(map, r, 'code_00_num' ,fun=function(x, ...) sample(x, 1)) #rasterization by maximum area rp.maximum <- rasterize(map, r, 'code_00_num' ,fun=max) par(mfrow=c(2,1)) plot(rp.random) plot(rp.maximum) ##### ------------------------------------------------------- Robert Pazur<http://www.sav.sk/index.php?lang=sk&charset=&doc=user-org-user&user_no=6225> Institute of Geography Slovak Academy Of Sciences Mobile : +421 948 001 705 Skype : ruegdeg 2012/10/12 Robert J. Hijmans <[email protected]> > > Any suggestion? > > Yes, to provide a more complete description of the method and the context > in which it should be useful. If you cannot do that, you probably should > not use the method. > > Here is aggregation with "some probability function" that, at least for > the example data, has the property you desire (class frequencies are > similar). > > library(raster) > # create example data > r <- raster() > set.seed(999) > values(r) <- round(runif(ncell(r))*3) > > # aggregate with random sampling > a <- aggregate(r, fact=10, fun=function(x, ...) sample(x, 1)) > > # get frequencies > fr <- freq(r) > fa <- freq(a) > > # as percentage > fr[,2] <- round(100 * fr[,2] / sum(fr[,2])) > fa[,2] <- round(100 * fa[,2] / sum(fa[,2])) > > # combine > f <- cbind(fr, fa[,2]) > colnames(f)[2:3] <- c('original', 'aggregated') > f > > > > Best, Robert > > On Thu, Oct 11, 2012 at 3:23 AM, Robert Pazur <[email protected]>wrote: > >> Since the description in literature is not very detailed, i can only >> guess that its based on some probability function. >> Any suggestion? >> >> Robert Pazur >> >> >> 2012/10/10 Robert J. Hijmans <[email protected]> >> >>> I am sure there is a way. Can you describe how this is done? Robert >>> >>> On Wed, Oct 10, 2012 at 5:51 AM, Robert Pazur <[email protected]>wrote: >>> >>>> Dear all, >>>> >>>> using land cover fine scale data set with defined categories: >>>> is there a way ( perhaps in raster, or sp library) how to aggregate this >>>> raster by keeping the overall proportion of each land cover >>>> classes constant (as much as possible)? >>>> this aggregation procedure were described as "adjusted" by several >>>> authors >>>> : >>>> >>>> -Verburg, P. H., Denijs, T., Ritsemavaneck, J., Visser, H., & Dejong, K. >>>> (2004). A method to analyse neighbourhood characteristics of land use >>>> patterns. Computers, Environment and Urban Systems, 28(6), 667â690. >>>> doi:10.1016/j.compenvurbsys.2003.07.001 *page 8* >>>> >>>> -Schmit, C., Rounsevell, M., & Lajeunesse, I. (2006). The limitations of >>>> spatial land use data in environmental analysis. Environmental Science & >>>> Policy, 9(2), 174â188. doi:10.1016/j.envsci.2005.11.006 *page 5* >>>> >>>> -Dendoncker, N., Schmit, C., & Rounsevell, M. (2008). Exploring spatial >>>> data uncertainties in landâuse change scenarios. International Journal >>>> of >>>> Geographical Information Science, 22(9), 1013â1030. >>>> doi:10.1080/13658810701812836 *page 3* >>>> * >>>> >>>> * >>>> Thanks in advance, >>>> Robert. >>>> >>>> >>>> ------------------------------------------------------- >>>> Robert Pazur< >>>> http://www.sav.sk/index.php?lang=sk&charset=&doc=user-org-user&user_no=6225 >>>> > >>>> >>>> >>>> Institute of Geography >>>> Slovak Academy Of Sciences >>>> >>>> Mobile : +421 948 001 705 >>>> Skype : ruegdeg >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> >>>> _______________________________________________ >>>> R-sig-Geo mailing list >>>> [email protected] >>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>>> >>>> >>> >> > [[alternative HTML version deleted]]
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