While it should be straightforward to calculate great circle
distances, designing a rectangular grid on a sphere is not. There's a
solution for a global grid using hexagons (Teanby, 2006), but I
haven't seen it implemented in R (yet). My gut feeling is that for
Australia there's a standard projection used by geographers that's
reasonably distortion-free and should be plenty accurate given that
you're working on such a large scale. Checking the fine print of that
big map on your wall might be a good start.
HTH,
Martin
Martin Renner
current address:
Alaska Maritime NWR 907-226-4672 (work)
Homer, AK 99603, USA 907-235-7783 (fax)
@article{Teanby:2006aa,
Author = {Teanby, N. A.},
Journal = {Computers and Geosciences},
Number = {9},
Pages = {1442--1450},
Title = {An icosahedron-based method for even binning of globally
distributed remote sensing data},
Volume = {32},
Year = {2006}}
On 28 Apr 2009, at 01:37 , 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
[email protected] 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
_______________________________________
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: [email protected]<mailto:[email protected]
>
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--
Drs. Paul Hiemstra
Department of Physical Geography
Faculty of Geosciences
University of Utrecht
Heidelberglaan 2
P.O. Box 80.115
3508 TC Utrecht
Phone: +3130 274 3113 Mon-Tue
Phone: +3130 253 5773 Wed-Fri
http://intamap.geo.uu.nl/~paul
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