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

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

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 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

NASA Flood Extent Detection

This dataset contains synthetic aperture radar (SAR) raster imagery for various flood events acquired from the European Space Agencys Sentinel-1A and Sentinel-1B missions, providing C-Band dual-polarized imagery that spans geographical areas of interest in the United States and Bangladesh. The main emphasis was on the labeling of open water read more...

flood detection

sar

segmentation

sentinel-1

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

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

SEN12-FLOOD : A SAR and Multispectral Dataset for Flood Detection

These last decades, Earth Observation brought quantities of new perspectives from geosciences to human activity monitoring. As more data became available, artificial intelligence techniques led to very successful results for understanding remote sensing data. Moreover, various acquisition techniques such as Synthetic Aperture Radar (SAR) can also be used for read more...

flood detection

image classification

sar

sentinel-1

sentinel-2

South Africa Crop Type Competition

This dataset was produced as part of the Radiant Earth Spot the Crop Challenge. The objective of the competition was to create a machine learning model to classify fields by crop type from images collected during the growing season by the Sentinel-2 and Sentinel-1 read more...

agriculture

crop type

segmentation

sentinel-1

sentinel-2

Western USA Live Fuel Moisture

This data contains manually collected live fuel moisture measurements in the western United States and remotely-sensed variables. Live fuel moisture represents the mass of water in live vegetation elements like leaves, needles, and twigs divided by its oven-dried mass. It is represented in percentages. Higher the live fuel moisture, read more...

landsat 8

live fuel moisture

sar

sentinel-1

wildfire