My colleague Sean Harkins is telling me that there was an issue in gdal which was fixed in 3.3 (https://github.com/OSGeo/gdal/pull/4656). Could you make sure conda install gdal>=3.3 or that you are us

I just installed rasterio==1.2.0b1 on a fresh virtual env (with no GDAL/PROJ env set) and I'm getting a proj error Not sure what's going on :-(

This is really cool, thanks for the hard work Sean!

I can confirm that writing a Jpeg2000 from memory losses the geo information

Hi All, I'll answer for Kyle but he can jump back if needed. The problem Kyle was facing was due to GDAL3 (running on AWS Lambda, CentOS) being extremely slow for image reprojection. We faced this in

FYI: https://github.com/corteva/rioxarray/issues/92 and https://github.com/corteva/rioxarray/issues/92

Hi Guillaume, thanks for raising this, it happens to me often too. I'm thinking about multiple solutions: - check if the file has other georeferenced information (like rpc or gpc) internally before ra

Yes it is set to yes, here the full log https://gist.github.com/vincentsarago/36473e6322336e84cf928ef445db64cc

Then I get "not recognized as a supported file format." ``` >>> f = open("/local/OR_ABI-L1b-RadF-M6C04_G16_s20193221600287_e20193221609595_c20193221610025.nc", "rb") >>> with MemoryFile(f) as mem: ...

Thanks for your answer Even, and be assured that I always read the manual before asking question :-) ``` $ more /proc/version Linux version 4.9.184-linuxkit (root@a8c33e955a82) (gcc version 8.3.0 (Alp

I'm seeking some advice here, I'm trying to reduce the memory/disk usage of one of my script where I try to translate a netcdf file to COG. Ideally I'd love not to save any file to disk. The problem I

I started a PR over https://github.com/mapbox/rasterio/pull/1740

Hi Guillaume, I'm + 1 with the idea of adding this feature. I've had the same challenge while working on rio-cogeo, if there is a GDAL API I think it could be useful to add a method in rasterio. Vince

Hi Ryan, This is just an idea but can you try with ``` with open(image_bytes, 'rb') as f, MemoryFile(f.read()) as memfile: with memfile.open() as src: arr = reshape_as_image(src.read()) ```

Hi James, The level of overviews is usually linked to the size of the raster and its internal tiles (block). here is an example in rio-cogeo: https://github.com/cogeotiff/rio-cogeo/blob/master/rio_cog

It seems the docs it wrong, looking at the code it take the max extent of all the dataset https://github.com/mapbox/rasterio/blob/b9f34ee559039239c7c0c97bd911b466701a39cd/rasterio/merge.py#L77-L92

Hi James, Rasterio has a cli command called `merge` (`rio merge`) which is the equivalent of `gdal_merge.py` with rasterio. If you are looking for a way to do it within python you can check https://gi

This is not something I've been seen for now. does this happens with Rasterio wheels and rasterio build on gdal source ?

Hi Sean, sorry for not being really clear. > Can you explain what processes produced those images? What program produced the blurry one and what program produced the non-blurry one? Which resampling a

This was previously discussed on multiple Issues and PR: - https://github.com/mapbox/rasterio/issues/1206 - https://github.com/mapbox/rasterio/pull/1238 - https://github.com/mapbox/rasterio/pull/1239