On Tuesday 18 August 2009, Etienne Bellemare Racine wrote: > Hi Wesley, > > It is unclear to me if you want to aggregate points to distinguish > individual tree, or if you want to locate the treetops ? > > Anyway, I suggest you first use your grid to locate treetops (using > maximum value as you said), then clustering using the treetops. Is your > plantation dense ? because if the crowns are touching each other, I > think it will be pretty hard to cluster them using only points. If you > have treetops, you can aggregate points around individuals treetops. > > To get maximum values, maybe sp::overlay can get you started, but I > think it is more to get grid value to point than reverse. I do it in > ArcGIS, but I would be happy to have a solution in R if you find one. > > Etienne
Also see r.in.xyz within GRASS GIS. Dylan > > Wesley Roberts a �crit : > > Dear R-sig-Geo, > > > > I am currently looking at clustering a LiDAR point cloud (trees in a > > plantation forest) using R and have some questions that I hope some of > > you may be able to answer. > > > > My method is a two stage approach, firstly I selected potential tree > > locations by overlaying a static grid on the point data and selecting the > > maximum value within each grid. These locations were stored as potential > > tree locations and have been used as sample data in a spatial clustering > > approach (I would have liked to use a moving filter but could not find a > > local maximum approach implemented in R). These points and the original > > data are now being clustered using the clus algorithm in the spatclus > > package. > > > > My query regards the use of an algorithm developed for disease mapping > > (Kuldorff's circular zone in 2D) with Lidar data. The density of the > > lidar points is around 5 per square meter and I am concerned that the > > algorithm will not be able to identify clusters based on height. I am yet > > to inspect the results as the clus algorithm is still running so I cant > > comment on that right now, but I was wondering if anyone on the list had > > any suggestions wrt the clustering and or segmentation of lidar point > > clouds using R. I am unwilling to use interpolation as I want to avoid > > the lengthy process of selecting the correct interpolation procedure and > > or model and would like to stick with the point cloud. > > > > Any advice on this matter would be greatly appreciated. > > Many thanks and kind regards, > > > > Wesley > > > > > > Wesley Roberts MSc. > > Researcher: Earth Observation > > Natural Resources & the Environment (NRE) > > CSIR > > Tel: +27 (0)21 888-2490 > > Fax: +27 (0)21 888-2693 > > "To know the road ahead, ask those coming back." > > - Chinese proverb > > [[alternative HTML version deleted]] -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341
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