Hi Ultrich, unfortunately, the approach Tom mentioned accounts for non-Euclidean distances, but not for downstream direction, as it asumes stationarity and *isotropy* with respect to the hydrologic distances. In the line of Tom's suggestion, you might be interested in looking at the 'soap' R package for smooth interpolation in funny regions. Bests ?acu.- El 17/11/09 12:45, Tomislav Hengl escribi?:
Hi Ultrich, Facundo Mu?oz apparently made a GRASS function to derive distances along streams: https://stat.ethz.ch/pipermail/r-sig-geo/2009-November/006851.html 17 observations only? That is really tight for any geostatistical analysis (on top, you want to do 3 dimensions!). I would instead consider fitting a smooth surface (splines) / simulating the flow processes. all the best, T. Hengl http://home.medewerker.uva.nl/t.hengl/
-----Original Message----- From: r-sig-geo-bounces at stat.math.ethz.ch [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of Ulrich Leopold Sent: Tuesday, November 17, 2009 10:53 AM To: R-sig-geo list; grass-user at lists.osgeo.org Subject: [R-sig-Geo] Spatial interpolation of river network observations Dear all, I would like to interpolate 17 pollution observations in a storage lake in 3 dimensions (x,y,z). As I understand variogram analysis and kriging are not straightforward as we are dealing with non-euclidean (hydrologic) distances and down-stream direction. Could someone point me to some algorithms which can roughly estimate the 3d pollution body accounting for hydrologic distances? Attached is a file which shows the sampling locations and the storage lake. Thanks very much. Best regards, Ulrich --
______________________________________________________________________ Ulrich Leopold Resource Centre for Environmental Technologies, Public Research Centre Henri Tudor, Technoport Schlassgoart, 66 rue de Luxembourg, P.O. BOX 144, L-4002 Esch-sur-Alzette, Luxembourg tel: +352 42 5591 618 fax: +352 42 5591 555 mobile: +352 691 304813 http://www.crte.lu , http://www.tudor.lu
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