Datasets:

MayeulQ
/

MODMask-all-cities-UHI

Tags:
License:
Dataset card Files Files and versions
xet
Community
Dataset Viewer
Duplicate
Split (1)
train
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
Aachen__Germany__67: list<item: int64>
  child 0, item: int64
Aarau__Switzerland__1397: list<item: int64>
  child 0, item: int64
Acilia__Italy__3894: list<item: int64>
  child 0, item: int64
Aix-en-Provence__France__4221: list<item: int64>
  child 0, item: int64
Albacete__Spain__4179: list<item: int64>
  child 0, item: int64
Albano_Laziale__Italy__4146: list<item: int64>
  child 0, item: int64
Alcala_de_Henares__Spain__3797: list<item: int64>
  child 0, item: int64
Alcoi__Alcoy__Spain__4559: list<item: int64>
  child 0, item: int64
Aldershot__United_Kingdom__5553: list<item: int64>
  child 0, item: int64
Alessandria__Italy__555: list<item: int64>
  child 0, item: int64
Alkmaar__Netherlands__1394: list<item: int64>
  child 0, item: int64
Almelo__Netherlands__3504: list<item: int64>
  child 0, item: int64
Almere__Netherlands__2349: list<item: int64>
  child 0, item: int64
Alphen_aan_den_Rijn__Netherlands__1291: list<item: int64>
  child 0, item: int64
Altamura__Italy__5165: list<item: int64>
  child 0, item: int64
Amersfoort__Netherlands__2494: list<item: int64>
  child 0, item: int64
Amiens__France__3000: list<item: int64>
  child 0, item: int64
Amsterdam__Netherlands__1590: list<item: int64>
  child 0, item: int64
Ancona__Italy__4338: list<item: int64>
  child 0, item: int64
Andria__Italy__5013: list<item: int64>
  child 0, item: int64
Angers__France__1388: list<item: int64>
  child 0, item: int64
Angouleme__France__1773: list<item: int64>
  child 0, item: int64
Annecy__Franc
...
t<item: int64>
  child 0, item: int64
Zilina__Slovakia__568: list<item: int64>
  child 0, item: int64
Zurich__Switzerland__1689: list<item: int64>
  child 0, item: int64
Zwickau__Germany__5382: list<item: int64>
  child 0, item: int64
Zwolle__Netherlands__3290: list<item: int64>
  child 0, item: int64
s-Hertogenbosch__Netherlands__2423: list<item: int64>
  child 0, item: int64
cities: list<item: struct<city_key: string, city: string, country: string, ghsl_id: string, representative_l (... 489 chars omitted)
  child 0, item: struct<city_key: string, city: string, country: string, ghsl_id: string, representative_lon: double, (... 477 chars omitted)
      child 0, city_key: string
      child 1, city: string
      child 2, country: string
      child 3, ghsl_id: string
      child 4, representative_lon: double
      child 5, representative_lat: double
      child 6, ghsl_grid_cells: int64
      child 7, modmask_target_cells: int64
      child 8, successful_uhi_cells: int64
      child 9, failed_rural_search_cells: int64
      child 10, non_modmask_target_ghsl_cells: int64
      child 11, city_mask_source: string
      child 12, rural_reference_cells_UHI_px: int64
      child 13, rural_reference_cells_UHI_LR100: int64
      child 14, rural_reference_cells_UHI_LR200: int64
      child 15, rural_reference_cells_UHI_LR300: int64
      child 16, rural_reference_cells_UHI_LR500: int64
      child 17, uhi_success_percent_of_targets: double
      child 18, eligible_for_full_export: bool
to
{'cities': List({'city_key': Value('string'), 'city': Value('string'), 'country': Value('string'), 'ghsl_id': Value('string'), 'representative_lon': Value('float64'), 'representative_lat': Value('float64'), 'ghsl_grid_cells': Value('int64'), 'modmask_target_cells': Value('int64'), 'successful_uhi_cells': Value('int64'), 'failed_rural_search_cells': Value('int64'), 'non_modmask_target_ghsl_cells': Value('int64'), 'city_mask_source': Value('string'), 'rural_reference_cells_UHI_px': Value('int64'), 'rural_reference_cells_UHI_LR100': Value('int64'), 'rural_reference_cells_UHI_LR200': Value('int64'), 'rural_reference_cells_UHI_LR300': Value('int64'), 'rural_reference_cells_UHI_LR500': Value('int64'), 'uhi_success_percent_of_targets': Value('float64'), 'eligible_for_full_export': Value('bool')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Aachen__Germany__67: list<item: int64>
                child 0, item: int64
              Aarau__Switzerland__1397: list<item: int64>
                child 0, item: int64
              Acilia__Italy__3894: list<item: int64>
                child 0, item: int64
              Aix-en-Provence__France__4221: list<item: int64>
                child 0, item: int64
              Albacete__Spain__4179: list<item: int64>
                child 0, item: int64
              Albano_Laziale__Italy__4146: list<item: int64>
                child 0, item: int64
              Alcala_de_Henares__Spain__3797: list<item: int64>
                child 0, item: int64
              Alcoi__Alcoy__Spain__4559: list<item: int64>
                child 0, item: int64
              Aldershot__United_Kingdom__5553: list<item: int64>
                child 0, item: int64
              Alessandria__Italy__555: list<item: int64>
                child 0, item: int64
              Alkmaar__Netherlands__1394: list<item: int64>
                child 0, item: int64
              Almelo__Netherlands__3504: list<item: int64>
                child 0, item: int64
              Almere__Netherlands__2349: list<item: int64>
                child 0, item: int64
              Alphen_aan_den_Rijn__Netherlands__1291: list<item: int64>
                child 0, item: int64
              Altamura__Italy__5165: list<item: int64>
                child 0, item: int64
              Amersfoort__Netherlands__2494: list<item: int64>
                child 0, item: int64
              Amiens__France__3000: list<item: int64>
                child 0, item: int64
              Amsterdam__Netherlands__1590: list<item: int64>
                child 0, item: int64
              Ancona__Italy__4338: list<item: int64>
                child 0, item: int64
              Andria__Italy__5013: list<item: int64>
                child 0, item: int64
              Angers__France__1388: list<item: int64>
                child 0, item: int64
              Angouleme__France__1773: list<item: int64>
                child 0, item: int64
              Annecy__Franc
              ...
              t<item: int64>
                child 0, item: int64
              Zilina__Slovakia__568: list<item: int64>
                child 0, item: int64
              Zurich__Switzerland__1689: list<item: int64>
                child 0, item: int64
              Zwickau__Germany__5382: list<item: int64>
                child 0, item: int64
              Zwolle__Netherlands__3290: list<item: int64>
                child 0, item: int64
              s-Hertogenbosch__Netherlands__2423: list<item: int64>
                child 0, item: int64
              cities: list<item: struct<city_key: string, city: string, country: string, ghsl_id: string, representative_l (... 489 chars omitted)
                child 0, item: struct<city_key: string, city: string, country: string, ghsl_id: string, representative_lon: double, (... 477 chars omitted)
                    child 0, city_key: string
                    child 1, city: string
                    child 2, country: string
                    child 3, ghsl_id: string
                    child 4, representative_lon: double
                    child 5, representative_lat: double
                    child 6, ghsl_grid_cells: int64
                    child 7, modmask_target_cells: int64
                    child 8, successful_uhi_cells: int64
                    child 9, failed_rural_search_cells: int64
                    child 10, non_modmask_target_ghsl_cells: int64
                    child 11, city_mask_source: string
                    child 12, rural_reference_cells_UHI_px: int64
                    child 13, rural_reference_cells_UHI_LR100: int64
                    child 14, rural_reference_cells_UHI_LR200: int64
                    child 15, rural_reference_cells_UHI_LR300: int64
                    child 16, rural_reference_cells_UHI_LR500: int64
                    child 17, uhi_success_percent_of_targets: double
                    child 18, eligible_for_full_export: bool
              to
              {'cities': List({'city_key': Value('string'), 'city': Value('string'), 'country': Value('string'), 'ghsl_id': Value('string'), 'representative_lon': Value('float64'), 'representative_lat': Value('float64'), 'ghsl_grid_cells': Value('int64'), 'modmask_target_cells': Value('int64'), 'successful_uhi_cells': Value('int64'), 'failed_rural_search_cells': Value('int64'), 'non_modmask_target_ghsl_cells': Value('int64'), 'city_mask_source': Value('string'), 'rural_reference_cells_UHI_px': Value('int64'), 'rural_reference_cells_UHI_LR100': Value('int64'), 'rural_reference_cells_UHI_LR200': Value('int64'), 'rural_reference_cells_UHI_LR300': Value('int64'), 'rural_reference_cells_UHI_LR500': Value('int64'), 'uhi_success_percent_of_targets': Value('float64'), 'eligible_for_full_export': Value('bool')})}
              because column names don't match
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MODMask All Cities UHI

Web-ready urban heat island products generated with MOD_Mask.
The dataset contains:
GHSL city catalogue and geometries
AROME grid-cell geometries
city-to-grid membership
MOD_Mask diagnostics
monthly mean UHI
mean diurnal UHI cycle
Available UHI definitions:
UHI_px
UHI_LR100
UHI_LR200
UHI_LR300
UHI_LR500
Downloads last month: 13
Total file size:
13.9 MB
MODMask All Cities UHI

Space using MayeulQ/MODMask-all-cities-UHI 1
