pyproj.CRS has a to_proj4 method that should be able to do that: https://pyproj4.github.io/pyproj/stable/examples.html

I think this is the problem: https://pyproj4.github.io/pyproj/stable/gotchas.html#internal-proj-error-sqlite-error-on-select

The new wheel now includes the proj.db, which is close to the size of grids that were removed. Also, PROJ requires more dependencies, so that is also a likely factor. It might work, but I wouldn't rec

Thanks for working on this Sean! I verified that PROJ_NETWORK=ON works with a basic test: rio_geom.py: from rasterio.warp import transform_geom geometry = [ { "type": "Polygon", "coordinates": [ [ [-9

This should be fixed in 1.1.5 IIRC: #1248

I believe that this is what you are looking for: https://rasterio.readthedocs.io/en/latest/topics/resampling.html

My first thought is that if you do make the switch, I think it would make sense to do it in the 1.2 release. > I have heard from those who would rather stick with 2.4.4 for a while yet due to increase

Here is an example using rioxarray: https://corteva.github.io/rioxarray/stable/examples/interpolate_na.html It uses scipy griddata.

Add some history for reference: https://rasterio.groups.io/g/dev/topic/switch_from_proj_4_format_to/28991934

Here are instructions for rasterio to geopandas: https://gis.stackexchange.com/a/350231/144357 For geopandas to rasterio, you will need something like: if LooseVersion(rasterio.__gdal_version__) > Loo

Hi Nic, I think you are looking for rioxarray. An example of what you want to do is here: https://corteva.github.io/rioxarray/stable/examples/clip_geom.html Best, Alan

Hello, It appears the GeoPackage format can support vector and raster data in GDAL similar to the FIleGDB format. https://gdal.org/drivers/raster/gpkg.html https://gdal.org/drivers/vector/gpkg.html No

Hi Amine, rasterio is definitely a great tool. But, if you are looking for an interface to it similar to pandas, you may be interested in rioxarray. It wraps the rasterio code and gives you an xarray

After looking at the docs, I think you need to remove `.read(1)` as that returns a numpy array and `mask` expects a dataset: https://rasterio.readthedocs.io/en/stable/api/rasterio.mask.html#rasterio.m

I wonder if you are looking for `from rasterio.features import geometry_mask`? https://rasterio.readthedocs.io/en/stable/api/rasterio.features.html#rasterio.features.geometry_mask Example code: https:

I think this would be quite useful. i made a start at it using subdatasets in rioxarray here: https://github.com/corteva/rioxarray/pull/33 But, it is missing 1 dimensional variables such as time at th

I am not entirely sure what you are referring to, but I am assuming you want the bounds of the raster in lat/lon? If so, then `EPSG:4326` is a pretty standard projection for lat/lon coordinates. So, y

You are indeed correct Sean. Thanks for catching that and providing the correct answer! It seems I skimmed through the original message too fast.

Hi Javier, The blocksize is not a dynamic attribute. It represents the blocksize of the file on disk. So, if you want to change the blocksize, you will need to write it to a new file with a new blocks

Hi Leah, If you would like to try the rioxarray as an xarray extension, it is now available on pypi. An example of what you would like to do is here: https://corteva.github.io/rioxarray/html/examples/