I do use Windows, and thank you very much for the help! I know how to do this in GIS as Jonathan suggested; however, I haven't tried it in R with the solution Rick recommended since i am still cleaning my input data.
The problem of this task is very obvious: it will be super inefficient if all the distances have to be calculated. My initial thought was to locate the target points and subset the dataset before any calculations being made, but it may require quite a bit coding...... What you described sounds great to me, and i am looking forward to seeing it. b.t.w. the link you provided doesn't work, would you please double check it? X.W. On Thu, Apr 9, 2009 at 3:07 AM, Roger Bivand <roger.biv...@nhh.no> wrote: > On Wed, 8 Apr 2009, x wong wrote: > > Thank you very much, that is very helpful. >> >> >> x.w. >> >> On Wed, Apr 8, 2009 at 12:47 PM, rick reeves <ree...@nceas.ucsb.edu> >> wrote: >> >> Assuming that this dataset fits within the confines of R, this could be >>> done with sp package: spdistsN1() function >>> See attached sample solution: >>> >>> >>> >>> http://nceas.ucsb.edu/scicomp/GISSeminar/UseCases/AssignClosestPointsR/AssignClosestPointsR.html >>> >>> Hope this helps! RR >>> >>> > Note that this will be inefficient in that it calculates all the distances. > I have an off-CRAN package interfacing ANN, which - given two sets of > points, returns the k nearest in the first set (with distances) for each > point in the second set. ANN builds a tree of the first set, so searches for > nearest neighbours efficiently. Look for: > > http://spatial.nhh.no/R/etc/ann* > > The Windows binary wasn't built for the current release of R, so probably > needs rebuilding - let me know if you use Windows, and I'll re-build it. > > Hope this helps, > > Roger > > > >>> Jonathan Greenberg wrote: >>> >>> It seems that a raster-based approach would make more sense, rather than >>>> the hugely computationally inefficient approach you are suggesting -- >>>> how >>>> about using a least cost path or euclidean distance approach? Both are >>>> available in many GIS packages (ArcMap, GRASS GIS, etc...) >>>> >>>> --j >>>> >>>> x wong wrote: >>>> >>>> dear all, >>>>> >>>>> >>>>> >>>>> I have a raster GIS map converted to points. Now, I am trying to >>>>> calculate >>>>> the nearest neighbor distance for every point to a cluster of points >>>>> within >>>>> this map. Since the number of points is more than two millions, I am >>>>> wondering whether there is a computation efficient way to do this. >>>>> >>>>> >>>>> >>>>> The following is what the data looks like: >>>>> >>>>> point_id,x_coord,y_coord,class >>>>> >>>>> 675,-821292,6896866,GL >>>>> >>>>> 738,-819294,6895866,GL >>>>> >>>>> 803,-819294,6894867,GL >>>>> >>>>> 804,-818295,6894867,GL >>>>> >>>>> 805,-817296,6894867,GL >>>>> >>>>> 806,-816297,6894867,RCK >>>>> >>>>> 873,-818296,6893867,GL >>>>> >>>>> 874,-817297,6893867,GL >>>>> >>>>> 875,-816298,6893868,RCK >>>>> >>>>> 876,-815299,6893868,RCK >>>>> >>>>> 877,-814300,6893868,RCK >>>>> >>>>> 878,-813300,6893868,GL >>>>> >>>>> 945,-817297,6892867,GL >>>>> >>>>> 946,-816298,6892868,RCK >>>>> >>>>> 947,-815299,6892868,RCK >>>>> >>>>> 948,-814300,6892868,RCK >>>>> >>>>> 949,-813301,6892868,GL >>>>> >>>>> 950,-812302,6892869,GL >>>>> >>>>> 951,-811303,6892869,GL >>>>> >>>>> 1021,-816298,6891868,RCK >>>>> >>>>> 1023,-814300,6891868,RCK >>>>> >>>>> 1024,-813301,6891869,GL >>>>> >>>>> 1025,-812302,6891869,GL >>>>> >>>>> 1027,-810304,6891869,GL >>>>> >>>>> 1028,-809305,6891870,GL >>>>> >>>>> 1029,-808306,6891870,GL >>>>> >>>>> 1098,-816299,6890868,RCK >>>>> >>>>> 1099,-815300,6890868,RCK >>>>> >>>>> 1100,-814301,6890868,GL >>>>> >>>>> 1101,-813302,6890869,GL >>>>> >>>>> ............................................ >>>>> >>>>> >>>>> >>>>> I want to calculate, for example, the nearest distances for all GL >>>>> points >>>>> to >>>>> the RCK class. >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> X.W. >>>>> >>>>> [[alternative HTML version deleted]] >>>>> >>>>> _______________________________________________ >>>>> R-sig-Geo mailing list >>>>> R-sig-Geo@stat.math.ethz.ch >>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>>>> >>>>> >>>>> _______________________________________________ >>>> R-sig-Geo mailing list >>>> R-sig-Geo@stat.math.ethz.ch >>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>>> >>>> >>> >>> -- >>> Rick Reeves >>> Scientific Programmer/Analyst and Data Manager >>> National Center for Ecological Analysis and Synthesis >>> UC Santa Barbara >>> www.nceas.ucsb.edu >>> 805 892 2533 >>> >>> >>> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> R-sig-Geo mailing list >> R-sig-Geo@stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >> >> > -- > Roger Bivand > Economic Geography Section, Department of Economics, Norwegian School of > Economics and Business Administration, Helleveien 30, N-5045 Bergen, > Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43 > e-mail: roger.biv...@nhh.no > > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
