Hi Ivan,
if you are using Python, then options are usually given as a list of
strings. I cannot find in the gdal docs at the moment (docs for python
bindings are quite scarce), but you can check in Nansat:
https://github.com/nansencenter/nansat/blob/develop/vrt.py#L1641
So for your case it may be ['TPS=True'] or ['METHOD=GCP_TPS']
Regarding Nansat, we can add your mapper in the repository, or I can
help a little with development of it (if you provide band description
and an example file). Our mailing list is [email protected]
Regards!
Anton
On 02/17/2014 05:51 PM, Ivan Price wrote:
Hi Anton,
thanks for responding,
I have tried adding the tps option like this:
gdal.ReprojectImage(input_ds, output_ds, input_ds.GetProjection(),
output_ds.GetProjection(),
gdal.GRA_NearestNeighbour, 0.5*1024*1024*1024, 0,
None, {'tps': True})
but it has no effect. despite the doco in the link you have there is a max of 9
arguments, (not 10), so i'm not sure its even being used for what it should be.
(i'm using the python bindings from gdal 1.9)
regarding nansat it looks very interesting..
after an initial usage I see that i need to make a new mapper module for
coastcolour data, presumably based on the MERIS L2 example.. as there are
metadata fields that are missing in the coastcolour data that the envisat
mapper is missing.
it is interesting to see is that the reprojection is done in python, but using
a VRT mechanism. maybe i can adapt this approach to get something working.
thanks very much for the pointer
-i
-----Message d'origine-----
De : [email protected] [mailto:[email protected]]
De la part de Anton Korosov
Envoyé : Monday, 17 February 2014 13:38
À : [email protected]
Objet : Re: [gdal-dev] reprojecting coastcolour (/meris) using python via GCPs
Hello Ivan,
ReprojectImage() has a parameter psOptions()
http://www.gdal.org/gdalwarper_8h.html#ad36462e8d5d34642df7f9ea1cfc2fec4
It should accept any of the warping options, e.g. '-tps'
http://www.gdal.org/gdalwarp.html
I'm not 100% sure (since I'm using Python) but it may work.
I'll take this chance also to promote Nansat, a scientist-friendly Python tool
for working with satellite and model data:
Repo: https://github.com/nansencenter/nansat
Wiki: https://github.com/nansencenter/nansat/wiki
and API-rference: http://nansencenter.github.io/nansat/
It is a wrapper around GDAL, which adds scientific meaning to the opened
images. Briefly: GDAL doesn't know much about e.g. band 22 in a MERIS image,
Nansat does. It provides full information and allows simple usage, e.g.:
n = Nansat(meris_image)
n.reproject(dstDomain, tps=True)
n.export('outFile.nc')
It can open MERIS as well as tens of other formats.
Best regards!
Anton
On 02/17/2014 10:46 AM, Ivan Price wrote:
Hello,
I am trying to reproject a window inside a coastcolour (=MERIS) image. As far
as I can see GDAL cannot read the coastcolour data directly, so i am reading
the coastcolour netcdf in python, building a source dataset using the memory
driver, adding GCPS (1 for every 10th pixel) and writing the data to it, then
reprojecting the source dataset to a destination dataset which is a spatial
subset of the original in wgs84 lat/long.
This works fine and is relatively fast, but the reprojection is not accurate,
the results are out by about 6-10 pixels (in various directions). On reading
the forums it seems if i was using gdalwarp i would be using -tps, however the
ReprojectImage() function does not seem to offer this parameter ? And i don't
have the option of using the commandline tool as even gdal 1.10 cannot
recognise the coastcolour data.
So i guess i have 2 questions.. has anyone had any success reading coastcolour
data with the gdal command line tools, and secondly:
how can i get ReprojectImage() to be more accurate, given i have a GCP for
every pixel ?
thanks and regards,
-ivan
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