[GRASS-user] seeking advice on importing "unprojected" data

[Ken Mankoff]

Hi Michel, list,

I've come across a different method - using the CDO tools to remap the
rotated pole data set.

See thread here: https://code.mpimet.mpg.de/boards/2/topics/96
The answer there uses a simple ASCII "mygrid" as the target grid, but the
command can be "cdo remapbil,file.nc ifile ofile" where "file.nc" is a
netcdf file that represents the target grid. It has specific format
requirements discussed here:
https://earthscience.stackexchange.com/questions/8086/interpolate-gaussian-grids-to-regular-fixed-grids-using-bilinear-interpolation

I'm trying to figure out this CDO method, and having trouble converting my
GRASS GIS projection information (and the longitude and latitude
coordinates for each grid cell) to the correct NetCDF file... work is in
progress.

If I can't do it this way I'll hand-code it as you suggested in your reply.
I'm not totally clear on your method yet, so I may write and ask for more
details.

Thanks,

  -k.


On Thu, Aug 17, 2017 at 12:49 PM, Michel Wortmann <wortmann at pik-potsdam.de>
wrote:

> 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 <mankoff at gmail.com> 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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