David,
Would this help?
https://sites.google.com/site/mironehowtos/satellite/import-a-modis-l2-sst-hdf-grid
I do the projection using the geolocation arrays and an internal
interpolation using a minimum curvature algorithm. Works pretty nicely
with MODIS L2 SSTs and chlorophyll
Joaquim
Rutger,
Thanks for the reply. I tried the s_srs tag and it still didn't
help. I also tried using the -geoloc flag which I had tried earlier
too and still get the 441 out of 441 failed to transform error. I
have tried PyTroll, but there KDTree algorithm seems to be too slow
for the amount of data I'm using (not sure why), I have contacted them
in the past.
I'm attempting to project satellite data to an AWIPS grid. Assuming I
have the grid defined correctly with proj4 parameters, I've been using
"+proj=latlong +datum=wgs84" as my s_srs parameters. Does that sound
correct for satellite data? So my command line call (still for
testing) becomes:
gdalwarp -s_srs "+proj=latlong +datum=wgs84" \
-te 59.844 -123.044 14.335 -65.091 \
-ts 5120 5120 \
-t_srs "+proj=lcc +lon_1=-95.000 +lon_0=-113.133 +lat_2=25.0001
+lat_1=24.9999 +lat_0=16.369" \
-geoloc -of GTIFF \
image.vrt out.tif
The output grid is 5120x5120 and I wasn't sure if -te was lat/lon
points, but that's what I used. -te has lat/lon of upper left pixel
of the grid and lat/lon of the lower right pixel of the grid. Does
any of this look correct? Thanks for the help.
-Dave
On 6/12/12 7:04 AM, gdal-dev-requ...@lists.osgeo.org wrote:
Message: 2
Date: Tue, 12 Jun 2012 02:08:21 -0700 (PDT)
From: Rutger<kass...@gmail.com>
To:gdal-dev@lists.osgeo.org
Subject: Re: [gdal-dev] reproject python numpy binary swath/lat/lon
Message-ID:<1339492101512-4980686.p...@n6.nabble.com>
Content-Type: text/plain; charset=us-ascii
Hello David,
A while back i did some tests with GDAL geolocation arrays using
MODIS swath
data. I found that specifying the "s_srs" tag when running gdalwarp
gets rid
of the 'too many points' error, even if you already have a SRS in
your VRT.
If you use gdalwarp, your target grid can be completely described by the
-t_srs -tr and -t switches. The Python equivalent of these are the
dataset.SetProjection() and dataset.SetGeoTransform(). Getting the
input SRS
from only the coordinate values seems impossible to me, the SRS
should be
either read from some metadata or specified by the user.
For me the geolocation arrays worked technically well, and very
convenient.
However. i found the resulting image quality very disappointing (for my
specific MODIS case) compared to MRTswath and Pyresample. This might
be due
to the irregular coordinate grids as a result of the swiping image
sensor or
something like that. Maybe in different cases it would give good quality
results.
I ended up using the Pyresample module which is part from the Pytroll
project. See:
http://pytroll.org/index.html http://pytroll.org/index.html
This worked great for my case.
Regards,
Rutger
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