Datasets #
EuroSAT#
Eurosat is a dataset and deep learning benchmark for land use and land cover classification. The dataset is based on Sentinel-2 satellite images covering 13 spectral bands and consisting out of 10 classes with in total 27,000 labeled and geo-referenced images.
Labels: [’AnnualCrop’, ‘Forest’, ‘HerbaceousVegetation’, ‘Highway’, ‘Industrial’, ‘Pasture’, ‘PermanentCrop’, ‘Residential’, ‘River’, ‘SeaLake’]
RESISC45#
RESISC45 dataset is a dataset for Remote Sensing Image Scene Classification (RESISC). It contains 31,500 RGB images of size 256×256 divided into 45 scene classes, each class containing 700 images. Among its notable features, RESISC45 contains varying spatial resolution ranging from 20cm to more than 30m/px.
Labels: [’airplane’, ‘airport’, ‘baseball_diamond’, ‘basketball_court’, ‘beach’, ‘bridge’, ‘chaparral’, ‘church’, ‘circular_farmland’, ‘cloud’, ‘commercial_area’, ‘dense_residential’, ‘desert’, ‘forest’, ‘freeway’, ‘golf_course’, ‘ground_track_field’, ‘harbor’, ‘industrial_area’, ‘intersection’, ‘island’, ‘lake’, ‘meadow’, ‘medium_residential’, ‘mobile_home_park’, ‘mountain’, ‘overpass’, ‘palace’, ‘parking_lot’, ‘railway’, ‘railway_station’, ‘rectangular_farmland’, ‘river’, ‘roundabout’, ‘runway’, ‘sea_ice’, ‘ship’, ‘snowberg’, ‘sparse_residential’, ‘stadium’, ‘storage_tank’, ‘tennis_court’, ‘terrace’, ‘thermal_power_station’, ‘wetland’]