Matthieu Rigal wrote:
Hi folks,
I am currently implementing a tool to allow band-to-band computations on
array values out of 2 images with different projection and different
resolution in python.
The operation is quite complex, so I will summarize it here and below give
the solution I am currently testing to see if it is the best one and ask
for some enhancements and performance hints. Unfortunately, the high-level
warping class is, at my knowledge, only available in C++.
Workflow (could also be improved by all-in-one functions like for C++)
- Open image A, 5000*5000 pixels, 5m resolution, UTM
- Open image B, approx 100m resolution, LatLon, much larger than the
previous one
- Cut out the buffered extents of image A from image B
- Reproject this cutted image to the projection and resolution of image A
- Read full image A as array
- Read extents of image A from image B as array
Matthieu,
I think you might be able to short circuit some of the complexity by
creating a new memory dataset in UTM 5m with the same extents as
image A, and then just call ReprojectImage() to reproject from B to A.
Then this new memory dataset would be at the same resolution as A and
ready to compare, etc.
Best regards,
--
---------------------------------------+--------------------------------------
I set the clouds in motion - turn up | Frank Warmerdam, [email protected]
light and sound - activate the windows | http://pobox.com/~warmerdam
and watch the world go round - Rush | Geospatial Programmer for Rent
_______________________________________________
gdal-dev mailing list
[email protected]
http://lists.osgeo.org/mailman/listinfo/gdal-dev
