Many thanks for the code! What are the units of R in marktable? I didn't find the information in the documentation.
2011/5/17 Marcelino de la Cruz <[email protected]> > On 16/05/2011 10:27, Matevž PavliÄ wrote: > >> Hi all, >> >> I read (just now) about the Simpson idex. This would probably be a good >> thing to try in my case. Do you have any ideas of how to create a diversity >> map using Simpson index? >> >> > library(vegan) > simpson <- diversity(lansing.tab, "simpson") > lansing.simpson <- setmarks(lansing,simpson) > lansing.simpson.s <-smooth.ppp(lansing.simpson) > plot(lansing.simpson.s) > > > . I have just a few more questions about the code : >> >> The line below as I understand sets a table for each point with the type >> of points that are in the near in the radius R=350 units? >> mol.tab<- marktable(mol.ppp,R=350) >> >> > > Yes. > To resolve questions like this about the arguments of the functions, please > read the help pages, e.g. > help(marktable) > > > And this line creates a surface(map) of diversity ? >> lansing.div.s<-smooth.ppp(lansing.div) >> > Yes again. > help(smooth.ppp); help(density.ppp) > > >> >> I think this map that is created with smooth.ppp is to rough giving to >> little detail on the diversity. Would it be possible to use kriging to >> create diversity map? >> >> > It depends on what do you think is "too rough". You may control > the"roughnes" of the map changing the "dimyx" argument (that controls the > final grid of the smoothed surface). You may be also interested in setting > the argument "sigma" (that controls the bandwith of the smoothing kernel). > Although it is possible to krige the results, I think that in this case is > preferable to trust the smoothed surface. > > Cheers, > Marcelino > > > > > Thanks for the help, >> >> m >> >> -----Original Message----- >> From: [email protected] [mailto:[email protected]] >> Sent: Monday, May 16, 2011 9:59 AM >> To: Matevž PavliÄ >> Cc: [email protected] >> Subject: RE: [R-sig-Geo] density /diversity of points >> >> Con fecha 15/5/2011, "Matevž Pavlič"<[email protected]> >> escribió: >> >> >> >>> Hi Marcelino, >>> >>> Was out of the office for a while... >>> Thanks for the help. I think this could work...but can you tell me what >>> this line does? >>> >>> diversity<- apply(mol.tab,1,function(x) sum(x>0)) >>> >>> >> >> mol.tab is a table with the number of occurrences of each type (columns) >> in the neighborhood of each point (rows). This line computes for each >> row (i.e. for each point) the number of types whose value is ">0" >> (i.e. types that are present in the neighborhood). This is a very simple >> definition of diversity (i.e. "richness"). From that table you could >> also compute Shannon or Simpson diversity indices, if you would prefer >> that. >> >> >> Marcelino >> >> >> >>> i cant figure out how diversity is calculated here? >>> >>> Thanks again for the help, >>> >>> matevz >>> >>> -----Original Message----- >>> From: Marcelino de la Cruz [mailto:[email protected]] >>> Sent: Thursday, May 12, 2011 2:03 PM >>> To: Matevà ¾ Pavlià Cc: [email protected] >>> Subject: Re: [R-sig-Geo] density /diversity of points >>> >>> On 12/05/2011 13:12, Matevà ¾ Pavlià wrote: >>> >>> >>>> Hi all, >>>> >>>> >>>> >>>> I have a point data set (SHP) with coordinates and a attribute (i.e. >>>> type of point). >>>> >>>> These points are scattered around a fairly big area. What i would like >>>> to do is to find a sub-area where density of points sombined with the >>>> diversity of type is the biggest. >>>> >>>> Does anyone have any idea iff this is somehowe possible to do in R? >>>> Any idea would be greatly aprpeciated, >>>> >>>> >>>> >>>> >>> To your first question: >>> >>> library(fortunes) >>> fortune("Yoda") >>> >>> ;-) >>> >>> More seriously, you could transform your shp data in a ppp object with >>> spatstat. See the vignette in spatstat. Then you can use some functions >>> there, for example (with the data set lansing): >>> >>> library(spatstat) >>> data(lansing) >>> plot(lansing) >>> # get an estimate of point density >>> lansing.den<- density.ppp(lansing) >>> plot(lansing.den) >>> >>> # get an estimate of point diversity (here, for the shake of brevity, at >>> the points themselves) >>> lansing.tab<- marktable(lansing,R=0.05) >>> diversity<- apply(lansing.tab,1,function(x) sum(x>0)) lansing.div<- >>> setmarks(lansing,diversity) lansing.div.s<-smooth.ppp(lansing.div) >>> >>> plot(lansing.div.s) >>> >>> # select areas with arbitrary high values of density and diversity plot( >>> eval.im(lansing.div.s>4.5& (lansing.den/max(lansing.den))>0.9)) >>> >>> >>> HTH. Cheers, >>> >>> Marcelino >>> >>> >>> >>> -- >>> _________________________________ >>> >>> Marcelino de la Cruz Rot >>> Departamento de Biologia Vegetal >>> E.U.T.I. Agricola >>> Universidad Politecnica de Madrid >>> 28040 Madrid >>> Tel: 34913365654 >>> _________________________________ >>> >>> >>> >> > > -- > _________________________________ Marcelino de la Cruz Rot Departamento de > Biologia Vegetal E.U.T.I. Agricola Universidad Politecnica de Madrid 28040 > Madrid Tel: 34913365654 _________________________________ > > > _______________________________________________ > R-sig-Geo mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > [[alternative HTML version deleted]]
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