Radiant MLHub
agriculture
arc
attribution benchmark
building footprints
cloud
crop type
drone
era5
flood detection
goes
image classification
land cover
landsat 8
live fuel moisture
marine debris
maxar
naip
nlcd
object detection
off-nadir
perspective images
planetscope
regression
road network
sar
segmentation
sentinel-1
sentinel-2
synthetic data
tamsat
tropical storm
wildfire
worldview-2
worldview-3
xai

BigEarthNet

BigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe were initially selected. All the tiles read more...
image classification
land cover
sentinel-2

Chesapeake Land Cover

This dataset contains high-resolution aerial imagery from the USDA NAIP program, high-resolution land cover labels from the Chesapeake Conservancy, low-resolution land cover labels from the USGS NLCD 2011 dataset, low-resolution multi-spectral imagery from Landsat 8, and high-resolution building footprint masks from Microsoft Bing, formatted to accelerate machine learning research read more...
building footprints
land cover
landsat 8
naip
nlcd
segmentation

LandCoverNet Africa

LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Africa contains data across Africa, which accounts for ~1/5 of the global dataset. Each pixel is identified as one of the seven land read more...
land cover
landsat 8
segmentation
sentinel-1
sentinel-2

LandCoverNet Asia

LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Asia contains data across Asia, which accounts for ~31% of the global dataset. Each pixel is identified as one of the seven land read more...
land cover
landsat 8
segmentation
sentinel-1
sentinel-2

LandCoverNet Australia

LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Australia contains data across Australia, which accounts for ~7% of the global dataset. Each pixel is identified as one of the seven land read more...
land cover
landsat 8
segmentation
sentinel-1
sentinel-2

LandCoverNet Europe

LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Europe contains data across Europe, which accounts for ~9.5% of the global dataset. Each pixel is identified as one of the seven land read more...
land cover
landsat 8
segmentation
sentinel-1
sentinel-2

LandCoverNet North America

LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet North America contains data across North America, which accounts for ~13% of the global dataset. Each pixel is identified as one of the read more...
land cover
landsat 8
segmentation
sentinel-1
sentinel-2

LandCoverNet South America

LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet South America contains data across South America, which accounts for ~13% of the global dataset. Each pixel is identified as one of the read more...
land cover
landsat 8
segmentation
sentinel-1
sentinel-2

SEN12TS: A SAR and Multispectral Dataset for Land Cover Classification

The SEN12TS dataset contains Sentinel-1, Sentinel-2, and labeled land cover image triplets over six agro-ecologically diverse areas of interest: California, Iowa, Catalonia, Ethiopia, Uganda, and Sumatra. Using the Descartes Labs geospatial analytics platform, 246,400 triplets are produced at 10m resolution over 31,398 256-by-256-pixel unique spatial tiles for a total read more...
land cover
segmentation
sentinel-1
sentinel-2

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