Radiant MLHub
satellite
agriculture
building footprints
crop type
drone
flood detection
goes
image classification
land cover
landsat 8
live fuel moisture
marine debris
naip
nlcd
off-nadir
planetscope
regression
road network
sar
segmentation
sentinel-1
sentinel-2
tropical storm
wildfire
worldview-2
worldview-3

A Fusion Dataset for Crop Type Classification in Germany

A Fusion Dataset for Crop Type Classification in Germany
This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Brandenburg, Germany. There are nine crop types in this dataset from years 2018 and 2019: Wheat, Rye, Barley, Oats, Corn, Oil Seeds, Root Crops, read more...
agriculture
crop type
planetscope
sar
segmentation
sentinel-1
sentinel-2

A Fusion Dataset for Crop Type Classification in Western Cape, South Africa

A Fusion Dataset for Crop Type Classification in Western Cape, South Africa
This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Western Cape, South Africa. There are five crop types from the year 2017: Wheat, Barely, Canola, Lucerne/Medics, Small grain grazing. The AOI is split read more...
agriculture
crop type
planetscope
sar
segmentation
sentinel-1
sentinel-2

Marine Debris Dataset for Object Detection in Planetscope Imagery

Marine Debris Dataset for Object Detection in Planetscope Imagery
Floating marine debris is a global pollution problem which leads to the loss of marine and terrestrial biodiversity. Large swaths of marine debris are also navigational hazards to ocean vessels. The use of Earth observation data and artificial intelligence techniques can revolutionize the detection of floating marine debris read more...
marine debris
planetscope
segmentation

Semantic Segmentation of Crop Type in Ghana

Semantic Segmentation of Crop Type in Ghana
Automatic, accurate crop type maps can provide unprecedented information for understanding food systems, especially in developing countries where ground surveys are infrequent. However, little work has applied existing methods to these data scarce environments, which also have unique challenges of irregularly shaped fields, frequent cloud coverage, small plots, and read more...
agriculture
crop type
planetscope
sar
segmentation
sentinel-1
sentinel-2

Semantic Segmentation of Crop Type in South Sudan

Semantic Segmentation of Crop Type in South Sudan
Automatic, accurate crop type maps can provide unprecedented information for understanding food systems, especially in developing countries where ground surveys are infrequent. However, little work has applied existing methods to these data scarce environments, which also have unique challenges of irregularly shaped fields, frequent cloud coverage, small plots, and read more...
agriculture
crop type
planetscope
sar
segmentation
sentinel-1
sentinel-2

SpaceNet 7

SpaceNet 7
The SpaceNet 7 Multi-Temporal Urban Development Challenge aims to help address this deficit and develop novel computer vision methods for non-video time series data. In this challenge, participants will identify and track buildings in satellite imagery time series collected over rapidly urbanizing areas. The competition centers around a new read more...
building footprints
planetscope
segmentation