Projection of a large spherical surface on to a plane [SEC=UNCLASSIFIED]
Paul, as mentioned here: https://stat.ethz.ch/pipermail/r-sig-geo/2008-October/004456.html gstat does use spherical distances when data are in geographical coordinates, however the usual variogram models are typically not non-negative definite on the sphere, and no appropriate models are available. Some people use it despite this, but it would surely worry me. In experiments with random points and an exponential variogram without nugget, I've found very weird results. To be honest I dislike it so much that I'm thinking about making it as hard as cokriging without a valid LMC: break with an error message that you could override, as for experimenting, and so protecting people who don't understand what positive definite means. -- Edzer
Paul Hiemstra wrote:
Hi Jin Li, I seem to remember that gstat can deal with Great circle distances, but I could be wrong as I have never used them before. You say that a certain projection does not produce satisfactory results, how have you defined satisfactory? cheers, Paul Jin.Li at ga.gov.au wrote:
Dear all, We are going to interpolate biophysical variables into continuous surface data using point samples in Australian EEZ that covers an area of 10 utm zones and ca. 44 degrees in terms of latitude. Our data is in lat and long (i.e., WGS84). We intend to apply kriging methods to such a big area. Of course, we can divide the whole EEZ into some subregions and actually we are going to divide it into some subregions based on a number of factors, but these sub-regions are still quite large and can cover 2 to 3 utms and 7-15 degrees in terms of latitude. Obviously it is not quite appropriate to treat a spherical surface as a plane. Given that kriging can not handle a spherical surface (hope this assumption is still valid), perhaps an alternative is project such spherical surface on to a plane. We have tried some equal distance projections to convert our data for Australian EEZ, but it seems that none of them can produce satisfactory projections, although sinusoidal gave slightly bet!
te!
r results in comparison with utm projection. Any suggestions? Thanks in advance. Cheers, Jin
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Jin Li, PhD
Spatial Modeller/Computational Statistician
Marine & Coastal Environment
Geoscience Australia
GPO Box 378, Canberra, ACT 2601, Australia
Ph: 61 (02) 6249 9899; email: jin.li at ga.gov.au<mailto:jin.li at ga.gov.au>
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Edzer Pebesma Institute for Geoinformatics (ifgi), University of M?nster Weseler Stra?e 253, 48151 M?nster, Germany. Phone: +49 251 8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de/ http://www.springer.com/978-0-387-78170-9 e.pebesma at wwu.de