Why not use cross-validation to empirically determine which method performs best for this dataset (in addition to asking if they are better than a random draw)? Robert
2009/2/9 Tomislav Hengl <t.he...@uva.nl>: > > Dear Yong Li, > > I hope you will not mind me joining this interesting discussion. > > If there is no evident spatial auto-correlation structure (pure nugget > effect), IDW/OK are as good > as randomly drawing a value from the global (normal) distribution. You can > even test this using > cross-validation! In principle, there is no justification to use > distance-based interpolators if > there is no evident spatial auto-correlation structure (maybe only the > moving-window kriging, as > implemented in e.g. Vesper, or stratified kriging techniques could discover > some local spatial > dependence). In addition, IDW should be considered an outdated technique, > applicable only for > situations where the variogram is close to linear (e.g. elevation data and > similar smooth surfaces). > > What you should really consider using are the globaly available free > maps/images (e.g. MODIS EVI, > SRTM DEM parameters etc.), and then see if you can explain some of the > variability in your target > variable. > > But there will always be situations (especially in DSM applications) where > you simply can not > explain much of the target variability, neither with auxiliary maps nor with > spatial > auto-correlation. What to do then? I guess you simply have to collect more > samples / more auxiliary > maps and then try again. > > HTH > > T. Hengl > > See also: > > Compendium of Global datasets: > http://spatial-analyst.net/wiki/index.php?title=Global_datasets > > Regression-kriging: > http://spatial-analyst.net/wiki/index.php?title=Regression-kriging > > Pebesma, E., 2006. The Role of External Variables and GIS Databases in > Geostatistical Analysis. > Transactions in GIS, 10(4): 615-632. > http://dx.doi.org/10.1111/j.1467-9671.2006.01015.x > > >> -----Original Message----- >> From: r-sig-geo-boun...@stat.math.ethz.ch >> [mailto:r-sig-geo-boun...@stat.math.ethz.ch] On Behalf >> Of Edzer Pebesma >> Sent: Monday, February 09, 2009 9:08 AM >> To: Yong Li >> Cc: r-sig-geo@stat.math.ethz.ch >> Subject: Re: [R-sig-Geo] FW: Interpolcation option: IDW or OK? >> >> Yong Li wrote: >> > Hi Edzer, >> > >> > I would say the spatial structure is regarded not significant when >> > c0/c0+c1 is very much greater >> than 75%. In my case I used even distance intervals and calculated c0/c0+c1 >> for log(OLSENP) >> greater than 85%. I knew this index sometimes is very fragile, very much >> depending on how we fit >> the model. >> > >> > However when I zoomed in by using variable distance intervals >> (boundaries=c(100,200,300,400,600,900,1000,1500,2000))and maxdist=2000 >> meters, I found a pretty >> good model-fitted experimental variogram. But the local OK interpolation >> using such a fitted model >> did not make sense when compared the predictions to the observations as in >> most areas values of >> OLSENP were severely underestimated. You may have seen my code with which I >> have tried the nested >> models, but unfortunately no luck either. I maybe think the parameters for >> local ordinary kriging >> are not optimized, but I have tried lots of sets of nmin, nmax and maxdist >> and did see the hopeful >> end. >> > >> > The journal editor insists in OK being better than IDW. I need to collect >> > my evidence to defend >> my IDW choice. That is my intention raised such a question in our forum here. >> > >> I cannot find evidence in your data for such a claim; the cross >> validation statistics (rmse) seem to favour OK with your nested model. >> >> In your first email, you stated the following: >> >> Normally if we do not find a significant spatial structure for a soil >> >> variable, we may choose IDW or other methods. >> What is the argumentation behind this? Who claimed this? >> >> -- >> Edzer Pebesma >> Institute for Geoinformatics (ifgi), University of Münster >> Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251 >> 8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de/ >> http://www.springer.com/978-0-387-78170-9 e.pebe...@wwu.de >> >> _______________________________________________ >> 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 > _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo