land mask rasterization is not working with SLC products read with a resolution coarser than native's one

error
ValueError                                Traceback (most recent call last)
Cell In [3], line 9
      7 fig_path = '/tmp/ksdjflksdjfd.png'
      8 sarim_rough = xsar.Sentinel1Dataset(str_gdal, resolution='%sm' % 50)
----> 9 sarim_rough.add_high_resolution_variables()
     10 heading = sarim_rough.dataset.platform_heading
     11 print('heading',heading)

File /home1/datahome/agrouaze/sources/git/xsar/src/xsar/sentinel1_dataset.py:379, in Sentinel1Dataset.add_high_resolution_variables(self, luts, patch_variable)
    377 if self.s1meta.product == 'SLC' and 'WV' not in self.s1meta.swath: # TOPS cases
    378     logger.debug('a TOPS product')
--> 379     self.land_mask_slc_per_bursts() # replace "GRD" like (Affine transform) land_mask by a burst-by-burst rasterised land mask
    380 else:
    381     logger.debug('not a TOPS product')

File /home1/datahome/agrouaze/sources/git/xsar/src/xsar/sentinel1_dataset.py:1197, in Sentinel1Dataset.land_mask_slc_per_bursts(self)
   1195 for kk in da_dict:
   1196     logging.info('da_dict[kk] %s',da_dict[kk])
-> 1197     complet_mask = xr.combine_by_coords(da_dict[kk])
   1198     all_masks.append(complet_mask)
   1199 tmpds = self.datatree['measurement'].to_dataset()

File /home/datawork-cersat-public/cache/project/mpc-sentinel1/workspace/mamba/envs/xsar_oct22/lib/python3.9/site-packages/xarray/core/combine.py:982, in combine_by_coords(data_objects, compat, data_vars, coords, fill_value, join, combine_attrs, datasets)
    980     concatenated_grouped_by_data_vars = []
    981     for vars, datasets_with_same_vars in grouped_by_vars:
--> 982         concatenated = _combine_single_variable_hypercube(
    983             list(datasets_with_same_vars),
    984             fill_value=fill_value,
    985             data_vars=data_vars,
    986             coords=coords,
    987             compat=compat,
    988             join=join,
    989             combine_attrs=combine_attrs,
    990         )
    991         concatenated_grouped_by_data_vars.append(concatenated)
    993 return merge(
    994     concatenated_grouped_by_data_vars,
    995     compat=compat,
   (...)
    998     combine_attrs=combine_attrs,
    999 )

File /home/datawork-cersat-public/cache/project/mpc-sentinel1/workspace/mamba/envs/xsar_oct22/lib/python3.9/site-packages/xarray/core/combine.py:629, in _combine_single_variable_hypercube(datasets, fill_value, data_vars, coords, compat, join, combine_attrs)
    623 if len(datasets) == 0:
    624     raise ValueError(
    625         "At least one Dataset is required to resolve variable names "
    626         "for combined hypercube."
    627     )
--> 629 combined_ids, concat_dims = _infer_concat_order_from_coords(list(datasets))
    631 if fill_value is None:
    632     # check that datasets form complete hypercube
    633     _check_shape_tile_ids(combined_ids)

File /home/datawork-cersat-public/cache/project/mpc-sentinel1/workspace/mamba/envs/xsar_oct22/lib/python3.9/site-packages/xarray/core/combine.py:125, in _infer_concat_order_from_coords(datasets)
    122 # Assume that any two datasets whose coord along dim starts
    123 # with the same value have the same coord values throughout.
    124 if any(index.size == 0 for index in indexes):
--> 125     raise ValueError("Cannot handle size zero dimensions")
    126 first_items = pd.Index([index[0] for index in indexes])
    128 series = first_items.to_series()

ValueError: Cannot handle size zero dimensions
the correction would be to get the right values for each burst at the resolution sought.
umr-lops / xsar

land mask rasterization is not working with SLC products read with a resolution coarser than native's one #127
