Hi Anton, just letting you know that adding either or both of those strings still doesn't force tps warping via the python bindings.
regarding nansat, i'd like to have a working coastcolour mapper file for future projects, unfortunately at this time i can't justify the time given i have a working solution now (partly thanks to nansat-learned techniques). from what i saw of my initial attempt though it should be achievable next time i need to do something similar. for info the data is available here: http://www.coastcolour.org/data/archive/mediterranean_blacksea/2010/L2R/ .. essentially MERIS L2 data but with certain vars missing/extra which break the nansat meris/envisat code. i'll contact the nansat list when it comes time to make the mapper. thanks again for your help -i -----Message d'origine----- De : Anton Korosov [mailto:[email protected]] Envoyé : Tuesday, 18 February 2014 09:49 À : Ivan Price; [email protected] Objet : Re: [gdal-dev] reprojecting coastcolour (/meris) using python via GCPs 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#ad36462e8d5d34642df7f9ea1cfc2fe > c4 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 >> >> >> >> >> >> _______________________________________________ >> gdal-dev mailing list >> [email protected] >> http://lists.osgeo.org/mailman/listinfo/gdal-dev >> > > _______________________________________________ > gdal-dev mailing list > [email protected] > http://lists.osgeo.org/mailman/listinfo/gdal-dev > _______________________________________________ gdal-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/gdal-dev
