Strange behaviour with vectorize

[matteodefelice]

test.zip

Today I discovered a strange behaviour when applying vectorize on a NetCDF. As expected, the GeoDataFrame and the DataArray have the same extent. However, when I sort the ycoordinate of the NetCDF using sortby the extents do not match any more. Here an example using the attached test.nc

# %%
import geocube.vector
import rioxarray
# %%
df = rioxarray.open_rasterio("test.nc")
df.rio.write_crs('EPSG:4326', inplace=True)
df = df.sortby("y")
print(df.rio.bounds())
# %%
v = geocube.vector.vectorize(df)
print(v.geometry.total_bounds)
# %%

Output

The extent (the bounds) of the NetCDF is:

(3.358333333333316, 53.550000000000004, 7.233333333333324, 50.75833333333334)

while the vectorized GeoDataFrame is:

[ 3.35833333 47.95        7.23333333 50.75833333]

They should be the same.

Environment Information

geocube v0.5.0

GDAL deps:
         fiona: 1.9.5
   GDAL[fiona]: 3.8.4
      rasterio: 1.3.9
GDAL[rasterio]: 3.8.4

Python deps:
       appdirs: 1.4.4
         click: 8.1.7
     geopandas: 0.14.3
       odc_geo: 0.4.3
     rioxarray: 0.15.1
        pyproj: 3.6.1
        xarray: 2024.2.0

System:
        python: 3.12.2 | packaged by conda-forge | (main, Feb 16 2024, 20:42:31) [MSC v.1937 64 bit (AMD64)]
    executable: C:\Users\matte\miniconda3\envs\geocube\python.exe
       machine: Windows-11-10.0.22631-SP0

Conda environment information (if you installed with conda):

Environment (conda list):

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[snowman2]

Deleted last comment as I learned some more after some digging.

Your file has a cached transform:

netcdf test {
dimensions:
    band = 1 ;
    x = 465 ;
    y = 337 ;
variables:
...

    int spatial_ref ;
...
        spatial_ref:GeoTransform = "3.358333333333316 0.008333333333333349 0.0 53.558333333333344 0.0 -0.008333333333333345" ;

Due to this, the bounds & transform will not update correctly after the sortby operation because it will pull the resolution from the cached transform.

To address this, you can update the cached transform (or delete it):

df = df.sortby("y")
df.rio.write_transform(df.rio.transform(recalc=True), inplace=True)

And everything works as expected:

df.rio.bounds()

(3.358333333333316, 50.75, 7.233333333333324, 53.558333333333344)

v = geocube.vector.vectorize(df)
v.geometry.total_bounds

[ 3.35833333, 50.75      ,  7.23333333, 53.55833333]