torchgeo.datasets ================= .. module:: torchgeo.datasets In :mod:`torchgeo`, we define two types of datasets: :ref:`Geospatial Datasets` and :ref:`Non-geospatial Datasets`. These abstract base classes are documented in more detail in :ref:`Base Classes`. .. _Geospatial Datasets: Geospatial Datasets ------------------- :class:`GeoDataset` is designed for datasets that contain geospatial information, like latitude, longitude, coordinate system, and projection. Datasets containing this kind of information can be combined using :class:`IntersectionDataset` and :class:`UnionDataset`. .. csv-table:: :widths: 30 15 20 36 20 15 :header-rows: 1 :align: center :file: datasets/geo_datasets.csv Aboveground Woody Biomass ^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: AbovegroundLiveWoodyBiomassDensity AgriFieldNet ^^^^^^^^^^^^ .. autoclass:: AgriFieldNet Airphen ^^^^^^^ .. autoclass:: Airphen Aster Global DEM ^^^^^^^^^^^^^^^^ .. autoclass:: AsterGDEM Canadian Building Footprints ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: CanadianBuildingFootprints Chesapeake Land Cover ^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: Chesapeake .. autoclass:: ChesapeakeDC .. autoclass:: ChesapeakeDE .. autoclass:: ChesapeakeMD .. autoclass:: ChesapeakeNY .. autoclass:: ChesapeakePA .. autoclass:: ChesapeakeVA .. autoclass:: ChesapeakeWV .. autoclass:: ChesapeakeCVPR GlobalBuildingMap ^^^^^^^^^^^^^^^^^ .. autoclass:: GlobalBuildingMap Global Mangrove Distribution ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: CMSGlobalMangroveCanopy Cropland Data Layer ^^^^^^^^^^^^^^^^^^^ .. autoclass:: CDL EDDMapS ^^^^^^^ .. autoclass:: EDDMapS EnMAP ^^^^^ .. autoclass:: EnMAP EnviroAtlas ^^^^^^^^^^^ .. autoclass:: EnviroAtlas Esri2020 ^^^^^^^^ .. autoclass:: Esri2020 EU-DEM ^^^^^^ .. autoclass:: EUDEM EuroCrops ^^^^^^^^^ .. autoclass:: EuroCrops GBIF ^^^^ .. autoclass:: GBIF GlobBiomass ^^^^^^^^^^^ .. autoclass:: GlobBiomass iNaturalist ^^^^^^^^^^^ .. autoclass:: INaturalist I/O Bench ^^^^^^^^^ .. autoclass:: IOBench L7 Irish ^^^^^^^^ .. autoclass:: L7Irish L8 Biome ^^^^^^^^ .. autoclass:: L8Biome LandCover.ai Geo ^^^^^^^^^^^^^^^^ .. autoclass:: LandCoverAIBase .. autoclass:: LandCoverAIGeo Landsat ^^^^^^^ .. autoclass:: Landsat .. autoclass:: Landsat9 .. autoclass:: Landsat8 .. autoclass:: Landsat7 .. autoclass:: Landsat5TM .. autoclass:: Landsat5MSS .. autoclass:: Landsat4TM .. autoclass:: Landsat4MSS .. autoclass:: Landsat3 .. autoclass:: Landsat2 .. autoclass:: Landsat1 MMFlood ^^^^^^^ .. autoclass:: MMFlood NAIP ^^^^ .. autoclass:: NAIP NCCM ^^^^ .. autoclass:: NCCM NLCD ^^^^ .. autoclass:: NLCD Open Buildings ^^^^^^^^^^^^^^ .. autoclass:: OpenBuildings PRISMA ^^^^^^ .. autoclass:: PRISMA Sentinel ^^^^^^^^ .. autoclass:: Sentinel .. autoclass:: Sentinel1 .. autoclass:: Sentinel2 South Africa Crop Type ^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: SouthAfricaCropType South America Soybean ^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: SouthAmericaSoybean .. _Non-geospatial Datasets: Non-geospatial Datasets ----------------------- :class:`NonGeoDataset` is designed for datasets that lack geospatial information. These datasets can still be combined using :class:`ConcatDataset `. .. csv-table:: C = classification, R = regression, S = semantic segmentation, I = instance segmentation, T = time series, CD = change detection, OD = object detection, IC = image captioning :widths: 15 7 15 20 12 11 12 15 13 :header-rows: 1 :align: center :file: datasets/non_geo_datasets.csv ADVANCE ^^^^^^^ .. autoclass:: ADVANCE Benin Cashew Plantations ^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: BeninSmallHolderCashews BigEarthNet ^^^^^^^^^^^ .. autoclass:: BigEarthNet .. autoclass:: BigEarthNetV2 BioMassters ^^^^^^^^^^^ .. autoclass:: BioMassters BRIGHT ^^^^^^ .. autoclass:: BRIGHTDFC2025 CaBuAr ^^^^^^ .. autoclass:: CaBuAr CaFFe ^^^^^ .. autoclass:: CaFFe ChaBuD ^^^^^^ .. autoclass:: ChaBuD Cloud Cover Detection ^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: CloudCoverDetection Copernicus-Pretrain ^^^^^^^^^^^^^^^^^^^ .. autoclass:: CopernicusPretrain COWC ^^^^ .. autoclass:: COWC .. autoclass:: COWCCounting .. autoclass:: COWCDetection CropHarvest ^^^^^^^^^^^ .. autoclass:: CropHarvest Kenya Crop Type ^^^^^^^^^^^^^^^ .. autoclass:: CV4AKenyaCropType DeepGlobe Land Cover ^^^^^^^^^^^^^^^^^^^^ .. autoclass:: DeepGlobeLandCover DFC2022 ^^^^^^^ .. autoclass:: DFC2022 DIOR ^^^^ .. autoclass:: DIOR Digital Typhoon ^^^^^^^^^^^^^^^ .. autoclass:: DigitalTyphoon DL4GAM ^^^^^^ .. autoclass:: DL4GAMAlps DOTA ^^^^ .. autoclass:: DOTA ETCI2021 Flood Detection ^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: ETCI2021 EuroSAT ^^^^^^^ .. autoclass:: EuroSAT .. autoclass:: EuroSATSpatial .. autoclass:: EuroSAT100 EverWatch ^^^^^^^^^ .. autoclass:: EverWatch FAIR1M ^^^^^^ .. autoclass:: FAIR1M Fields Of The World ^^^^^^^^^^^^^^^^^^^ .. autoclass:: FieldsOfTheWorld FireRisk ^^^^^^^^ .. autoclass:: FireRisk Forest Damage ^^^^^^^^^^^^^ .. autoclass:: ForestDamage GeoNRW ^^^^^^^ .. autoclass:: GeoNRW GID-15 ^^^^^^ .. autoclass:: GID15 HySpecNet-11k ^^^^^^^^^^^^^ .. autoclass:: HySpecNet11k IDTReeS ^^^^^^^ .. autoclass:: IDTReeS Inria Aerial Image Labeling ^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: InriaAerialImageLabeling LandCover.ai ^^^^^^^^^^^^ .. autoclass:: LandCoverAI .. autoclass:: LandCoverAI100 LEVIR-CD ^^^^^^^^ .. autoclass:: LEVIRCDBase .. autoclass:: LEVIRCD LEVIR-CD+ ^^^^^^^^^ .. autoclass:: LEVIRCDPlus LoveDA ^^^^^^ .. autoclass:: LoveDA MapInWild ^^^^^^^^^ .. autoclass:: MapInWild MDAS ^^^^ .. autoclass:: MDAS Million-AID ^^^^^^^^^^^ .. autoclass:: MillionAID MMEarth ^^^^^^^^ .. autoclass:: MMEarth NASA Marine Debris ^^^^^^^^^^^^^^^^^^ .. autoclass:: NASAMarineDebris OSCD ^^^^ .. autoclass:: OSCD PASTIS ^^^^^^ .. autoclass:: PASTIS PatternNet ^^^^^^^^^^ .. autoclass:: PatternNet Potsdam ^^^^^^^ .. autoclass:: Potsdam2D QuakeSet ^^^^^^^^ .. autoclass:: QuakeSet ReforesTree ^^^^^^^^^^^ .. autoclass:: ReforesTree RESISC45 ^^^^^^^^ .. autoclass:: RESISC45 Rwanda Field Boundary ^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: RwandaFieldBoundary SatlasPretrain ^^^^^^^^^^^^^^ .. autoclass:: SatlasPretrain Seasonal Contrast ^^^^^^^^^^^^^^^^^ .. autoclass:: SeasonalContrastS2 SeasoNet ^^^^^^^^ .. autoclass:: SeasoNet SEN12MS ^^^^^^^ .. autoclass:: SEN12MS SKIPP'D ^^^^^^^ .. autoclass:: SKIPPD SkyScript ^^^^^^^^^ .. autoclass:: SkyScript So2Sat ^^^^^^ .. autoclass:: So2Sat Solar Plants Brazil ^^^^^^^^^^^^^^^^^^^ .. autoclass:: SolarPlantsBrazil SODA ^^^^ .. autoclass:: SODAA SSL4EO ^^^^^^ .. autoclass:: SSL4EO .. autoclass:: SSL4EOL .. autoclass:: SSL4EOS12 SSL4EO-L Benchmark ^^^^^^^^^^^^^^^^^^ .. autoclass:: SSL4EOLBenchmark Substation ^^^^^^^^^^ .. autoclass:: Substation SustainBench Crop Yield ^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: SustainBenchCropYield TreeSatAI ^^^^^^^^^ .. autoclass:: TreeSatAI Tropical Cyclone ^^^^^^^^^^^^^^^^ .. autoclass:: TropicalCyclone UC Merced ^^^^^^^^^ .. autoclass:: UCMerced USAVars ^^^^^^^ .. autoclass:: USAVars Vaihingen ^^^^^^^^^ .. autoclass:: Vaihingen2D VHR-10 ^^^^^^ .. autoclass:: VHR10 Western USA Live Fuel Moisture ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: WesternUSALiveFuelMoisture xView2 ^^^^^^ .. autoclass:: XView2 ZueriCrop ^^^^^^^^^ .. autoclass:: ZueriCrop .. _Base Classes: Copernicus-Bench ---------------- Copernicus-Bench is a comprehensive evaluation benchmark with 15 downstream tasks hierarchically organized across preprocessing (e.g., cloud removal), base applications (e.g., land cover classification), and specialized applications (e.g., air quality estimation). This benchmark enables systematic assessment of foundation model performances across various Sentinel missions on different levels of practical applications. .. csv-table:: C = classification, R = regression, S = semantic segmentation, T = time series, CD = change detection :widths: 5 15 7 15 20 12 11 12 15 13 :header-rows: 1 :align: center :file: datasets/copernicus_bench.csv .. autoclass:: CopernicusBench .. autoclass:: CopernicusBenchBase .. autoclass:: CopernicusBenchCloudS2 .. autoclass:: CopernicusBenchCloudS3 .. autoclass:: CopernicusBenchEuroSATS1 .. autoclass:: CopernicusBenchEuroSATS2 .. autoclass:: CopernicusBenchBigEarthNetS1 .. autoclass:: CopernicusBenchBigEarthNetS2 .. autoclass:: CopernicusBenchLC100ClsS3 .. autoclass:: CopernicusBenchLC100SegS3 .. autoclass:: CopernicusBenchDFC2020S1 .. autoclass:: CopernicusBenchDFC2020S2 .. autoclass:: CopernicusBenchFloodS1 .. autoclass:: CopernicusBenchLCZS2 .. autoclass:: CopernicusBenchBiomassS3 .. autoclass:: CopernicusBenchAQNO2S5P .. autoclass:: CopernicusBenchAQO3S5P SpaceNet -------- The `SpaceNet Dataset `_ is hosted as an Amazon Web Services (AWS) `Public Dataset `_. It contains ~67,000 square km of very high-resolution imagery, >11M building footprints, and ~20,000 km of road labels to ensure that there is adequate open source data available for geospatial machine learning research. SpaceNet Challenge Dataset's have a combination of very high resolution satellite imagery and high quality corresponding labels for foundational mapping features such as building footprints or road networks. .. csv-table:: I = instance segmentation :widths: 15 7 15 20 12 11 12 15 13 :header-rows: 1 :align: center :file: datasets/spacenet.csv .. autoclass:: SpaceNet .. autoclass:: SpaceNet1 .. autoclass:: SpaceNet2 .. autoclass:: SpaceNet3 .. autoclass:: SpaceNet4 .. autoclass:: SpaceNet5 .. autoclass:: SpaceNet6 .. autoclass:: SpaceNet7 .. autoclass:: SpaceNet8 Base Classes ------------ If you want to write your own custom dataset, you can extend one of these abstract base classes. GeoDataset ^^^^^^^^^^ .. autoclass:: GeoDataset RasterDataset ^^^^^^^^^^^^^ .. autoclass:: RasterDataset VectorDataset ^^^^^^^^^^^^^ .. autoclass:: VectorDataset NonGeoDataset ^^^^^^^^^^^^^ .. autoclass:: NonGeoDataset NonGeoClassificationDataset ^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: NonGeoClassificationDataset IntersectionDataset ^^^^^^^^^^^^^^^^^^^ .. autoclass:: IntersectionDataset UnionDataset ^^^^^^^^^^^^ .. autoclass:: UnionDataset Utilities --------- Collation Functions ^^^^^^^^^^^^^^^^^^^ .. autofunction:: stack_samples .. autofunction:: concat_samples .. autofunction:: merge_samples .. autofunction:: unbind_samples Splitting Functions ^^^^^^^^^^^^^^^^^^^ .. autofunction:: random_bbox_assignment .. autofunction:: random_bbox_splitting .. autofunction:: random_grid_cell_assignment .. autofunction:: roi_split .. autofunction:: time_series_split Errors ------ .. autoclass:: DatasetNotFoundError .. autoclass:: DependencyNotFoundError .. autoclass:: RGBBandsMissingError