The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: BadZipFile
Message: zipfiles that span multiple disks are not supported
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 164, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1729, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1686, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1071, in get_module
module_name, default_builder_kwargs = infer_module_for_data_files(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 593, in infer_module_for_data_files
split_modules = {
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 594, in <dictcomp>
split: infer_module_for_data_files_list(data_files_list, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 535, in infer_module_for_data_files_list
return infer_module_for_data_files_list_in_archives(data_files_list, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 563, in infer_module_for_data_files_list_in_archives
for f in xglob(extracted, recursive=True, download_config=download_config)[
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1012, in xglob
fs, *_ = url_to_fs(urlpath, **storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 395, in url_to_fs
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 293, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 80, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 62, in __init__
self.zip = zipfile.ZipFile(
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 286, in _EndRecData
return _EndRecData64(fpin, -sizeEndCentDir, endrec)
File "/usr/local/lib/python3.9/zipfile.py", line 232, in _EndRecData64
raise BadZipFile("zipfiles that span multiple disks are not supported")
zipfile.BadZipFile: zipfiles that span multiple disks are not supportedNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for BioMassters for Global Prithvi
Dataset Description
Copied from BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series https://nascetti-a.github.io/BioMasster/
- Original Dataset: https://huggingface.co/datasets/nascetti-a/BioMassters
- Point of Contact For Updated Dataset: Denys Godwin ([email protected])
Dataset Summary
This dataset contains Sentinel-1 SAR and Sentinel-2 MSI imagery of Finnish forests for the years 2016-2021. There are 11,462 reference images of Above Ground Biomass (AGB). Each reference AGB has corresponding S1 and S2 imagery for the 12 months leading up to the AGB observation. Sentinel-1 data exists for each of the 12 months, while Sentinel-2 data does not have full temporal coverage. All imagery has height and width of 256x256.
Modifications for Prithvi
The directory structure of the dataset has been preserved. However, to enable the filtering needed for Prithvi training, some chip metadata has been calculated and stored in biomassters_chip_tracker.csv. Additional metadata are as follows:
- cloud_percentage: the percentage of clouds, defined as pixels where the cloud probability band of the input image exceeds 70
- corrupt_values: boolean representing whether there are corrupt values in the image. These are defined as blocks of identical values, which are present in some images
- red_mean: the mean value of the red band (band 3) of the Sentinel-2 image, used to filter scenes with anomalously high reflectance due to snow and Top of Atmosphere (ToA) correction issues
Data Splits
Training and testing splits are as given by The BioMassters original dataset. The training dataset has been further randomly split into training (80%) and validation (20%) sets. These are tracked in the 'split' column of the biomassters_chip_tracker.csv
Reference data:
- Reference AGB measurements were collected using LiDAR (Light Detection and Ranging) calibrated with in-situ measurements.
- Total 11,462 patches, each patch covering 2,560 by 2,560 meter area.
Feature data:
- Sentinel-1 SAR and Sentinel-2 MSI data
- 12 months of data (1 image per month)
- Sentinel-2 data does not exist for all months for all scenes
- Sentinel-2 data contains 10 selected spectral bands and 1 band of cloud probability
Dataset Specification
Data Size:
dataset | # files | size
--------------------------------------
train_features | 189078 | 215.9GB
test_features | 63348 | 73.0GB
train_agbm | 8689 | 2.1GB
test_agbm | 2773 | 705MB
Citation : under review
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