Comments (2)
I should note that there are relevant cases where the dimensions should be renamed from (e.g.) lat
to y
, for instance when projecting from a geographic CRS with distance units in degrees to a projected coordinate system like a UTM zone with distance units in meters. Not sure if keeping/renaming dims should be user-controlled or not, but I've noted a workaround above. So these new dim names and units are expected:
da3 = da.rio.reproject("EPSG:2193")
print(da3.x.attrs)
# {'axis': 'X', 'long_name': 'x coordinate of projection', 'standard_name': 'projection_x_coordinate', 'units': 'metre'}
print(da.lon.attrs)
# {'long_name': 'longitude', 'standard_name': 'longitude', 'axis': 'X', 'units': 'degrees_east', 'valid_min': -180.0, 'valid_max': 180.0, 'comment': 'geolocations inherited from the input data without correction'}
it's just this dimension name that's inconsistent:
print(da2.x.attrs)
# {'axis': 'X', 'long_name': 'longitude', 'standard_name': 'longitude', 'units': 'degrees_east'}
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This was by design to keep the logic simple. As you demonstrated, there are cases where you would transform from geographic to projected coordinate systems or the other way around. Attempting to preserve coordinate names in some instances and not others would make the behavior somewhat unpredictable. With the current design, you always know what your dimensions will be in the output.
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Related Issues (20)
- Typo in docs: longitute
- Fail to reproject and reproject_match a dataset with rotation affine. HOT 3
- Xarray padding with mode='reflect'
- Padding and Croping doesn't end up same result HOT 2
- overview_level failing in xarray with engine='rasterio' due to missing doc? HOT 2
- Rio array merge missing HOT 3
- Delayed/chunked opening (sentinel) SAFE data with bands as variables fails HOT 1
- `reproject_match` raises `MissingSpatialDimensionError` with spatial dims set HOT 1
- Save larger raster with zstd compression writes dirty block HOT 3
- Memory leak when looping through data variables of a dataset loaded from a VRT HOT 4
- Having dict-encoded GCPs leads to `to_netcdf` failing with a `TypeError` HOT 1
- Incompatibility with numpy updates HOT 3
- TST: Several `AssertionError`s in tests on `aarch64-linux` HOT 3
- why does `write_grid_mapping` check for spatial dims? HOT 3
- add explore function like in geopandas HOT 3
- Improvements to band_tags HOT 4
- Expose sample on the rioxarray accessor HOT 3
- Test failures with rasterio 1.4
- Create a logo for the lib
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