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Hi Ken,<br>
I have had to compare lonlat data with ncdf rotated pole data before
and also chose to import the centroids of the rotated grid into a
vector. To fill the cells I actually converted the points to much
smaller resolution (e.g. you could use the 30m of your other
dataset) raster cells with an ID and used r.grow.distance to create
an ID grid. I could then just reclass this ID grid for each
timestep, meaning no excess data in the grass db. At the time it
seemed like a bit of a workaround, but reading the thread below
makes me think this is the way to go.<br>
<br>
Regards,<br>
Michel<br>
<br>
<br>
<br>
<div class="moz-cite-prefix">On 15.08.2017 14:38, Ken Mankoff wrote:<br>
</div>
<blockquote type="cite"
cite="mid:CAFdBzEpBqJjM2gHM1g1JoaBwRt8F_cG+c=h7ZKssG4_Wif2W3A@mail.gmail.com">
<div dir="ltr">It seems that my suggested approach might be the
right one based on this thread from 2012: <a
href="https://lists.osgeo.org/pipermail/grass-dev/2012-March/058179.html"
moz-do-not-send="true">https://lists.osgeo.org/pipermail/grass-dev/2012-March/058179.html</a>
<div><br>
</div>
<div> -k.</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Tue, Aug 15, 2017 at 1:59 PM, Ken
Mankoff <span dir="ltr"><<a
href="mailto:mankoff@gmail.com" target="_blank"
moz-do-not-send="true">mankoff@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">Hi GRASS
list,<br>
<br>
I'm trying to compare two data sets and need to import them
into the same location. One is a GeoTIFF in WGS84 lon,lat
coordinates. When I create a new GRASS location using "-c
file.tif" everything appears to work, and<br>
<br>
$ g.region -p<br>
projection: 99 (unnamed)<br>
zone: 0<br>
datum: wgs84<br>
ellipsoid: wgs84<br>
etc...<br>
<br>
And from gdalinfo:<br>
<br>
Coordinate System is:<br>
PROJCS["unnamed",<br>
GEOGCS["WGS 84",<br>
DATUM["WGS_1984",<br>
SPHEROID["WGS 84",6378137,298.257223563,<br>
AUTHORITY["EPSG","7030"]],<br>
AUTHORITY["EPSG","6326"]],<br>
PRIMEM["Greenwich",0],<br>
UNIT["degree",0.<wbr>0174532925199433],<br>
AUTHORITY["EPSG","4326"]],<br>
PROJECTION["Polar_<wbr>Stereographic"],<br>
PARAMETER["latitude_of_origin"<wbr>,70],<br>
PARAMETER["central_meridian",-<wbr>45],<br>
PARAMETER["scale_factor",1],<br>
PARAMETER["false_easting",1],<br>
PARAMETER["false_northing",1],<br>
UNIT["metre",1,<br>
AUTHORITY["EPSG","9001"]]]<br>
Origin = (107900.000000000000000,-<wbr>655550.000000000000000)<br>
Pixel Size = (30.000000000000000,-30.<wbr>000000000000000)<br>
<br>
<br>
I have a second data set that I would like to co-locate with
this one. That data comes in a NetCDF file but the
projection is a custom rotated-pole projection. I have three
variables in the NetCDF file: lon, lat, and the data.<br>
<br>
What is the best method to convert on data set to the other?
My first approach might be to convert the NetCDF to
lon,lat,data ASCII file, import as points with m.proj, then
convert to raster. I'm wondering if this is what the experts
on this list would do. Note that I have one TIF, and 50,000
NetCDF time steps, so it may be more efficient to convert
the TIF to the custom NetCDF projection, but it is not a
requirement.<br>
<br>
Thanks for any advice you may have,<br>
<br>
-k.<br>
<br>
<br>
</blockquote>
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