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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 313.2 was truncated converting to int64
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1963, in array_cast
                  return array.cast(pa_type)
                File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast
                  return call_function("cast", [arr], options, memory_pool)
                File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Float value 313.2 was truncated converting to int64
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1529, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1154, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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id
int64
is_positive
int64
frp
float64
firepixel
string
timestamp
string
t_21
float64
t_31
float64
confidence
int64
inferred_type
int64
resolution
int64
t_m13
int64
t_m15
int64
t_i4
int64
t_i5
int64
lat
float64
lon
float64
daynight
int64
week_sin
float64
week_cos
float64
is_vegetation_fire
int64
1
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14.1
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2002-01-01 08:39:00
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2002-01-01 08:39:00
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2002-01-01 10:18:00
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2002-01-01 10:18:00
337.7
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2002-01-01 10:19:00
313.3
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2002-01-01 10:19:00
310.9
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2002-01-01 21:26:00
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2002-01-01 21:26:00
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2002-01-02 09:22:00
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2002-01-02 11:00:00
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2002-01-02 11:00:00
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2002-01-02 11:00:00
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2002-01-05 19:20:00
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2002-01-05 19:20:00
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2002-01-05 22:38:00
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2002-01-07 11:20:00
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2002-01-07 19:07:00
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End of preview.
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

Hotspot disambiguation dataset

This repository contains the dataset assembled as part of a work A Multimodal Supervised Machine Learning Approach for Satellite-based Wildfire Identification in Europe. Tha paper has been presented at the International Geoscience and Remote Sensing Symposium (IGARSS) 2023. The full paper is available at https://arxiv.org/abs/2308.02508 .

The data folder contains two files:

  • dataset.csv: this file contains the full cross-referenced dataset, obtained by conducing a temporal and spatial data intersection between the EFFIS burned areas and the MODIS/VIIRS hotspots.
  • dataset_500.csv: this file contains a subset of the previous dataset (~500k data points), subsampled to obtain a dataset stratified with respect to the spatial distribution, and with a positive-negative proportion of 10%-90%. In addition to MODIS/VIIRS data points, additional columns have been added to improve the models' performances. This file is the one used to obtain the results showed in the paper.

Code

The code and models used in this work are available at https://github.com/links-ads/hotspot-disambiguation .

Contributions

BibTex 

@inproceedings{urbanelli2023hotspot,
  title={A Multimodal Supervised Machine Learning Approach for Satellite-based Wildfire Identification in Europe},
  author={Urbanelli, Angelica and Barco, Luca and Arnaudo, Edoardo and Rossi, Claudio},
  booktitle={2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS},
  year={2023}
}

Licence

cc-by-4.0

Acknowledgments

This work was carried out in the context of two H2020 projects: SAFERS (GA n.869353) and OVERWATCH (GA n.101082320), and presented at IGARSS 2023.

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