Hi Ken,
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.
Regards,
Michel
On 15.08.2017 14:38, Ken Mankoff wrote:
It seems that my suggested approach might be the right one based on
this thread from 2012:
https://lists.osgeo.org/pipermail/grass-dev/2012-March/058179.html
-k.
On Tue, Aug 15, 2017 at 1:59 PM, Ken Mankoff <[email protected]
<mailto:[email protected]>> wrote:
Hi GRASS list,
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
$ g.region -p
projection: 99 (unnamed)
zone: 0
datum: wgs84
ellipsoid: wgs84
etc...
And from gdalinfo:
Coordinate System is:
PROJCS["unnamed",
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84",6378137,298.257223563,
AUTHORITY["EPSG","7030"]],
AUTHORITY["EPSG","6326"]],
PRIMEM["Greenwich",0],
UNIT["degree",0.0174532925199433],
AUTHORITY["EPSG","4326"]],
PROJECTION["Polar_Stereographic"],
PARAMETER["latitude_of_origin",70],
PARAMETER["central_meridian",-45],
PARAMETER["scale_factor",1],
PARAMETER["false_easting",1],
PARAMETER["false_northing",1],
UNIT["metre",1,
AUTHORITY["EPSG","9001"]]]
Origin = (107900.000000000000000,-655550.000000000000000)
Pixel Size = (30.000000000000000,-30.000000000000000)
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.
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.
Thanks for any advice you may have,
-k.
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