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 to three tiles. Two tiles are provided as training labels, and one tile will be used for scoring in the competition. Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection. The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license. The Western Cape Department of Agriculture (WCDoA) vector data are supplied via Radiant Earth Foundation with limited distribution rights. Data supplied by the WCDoA may not be distributed further or used for commercial purposes. The vector data supplied are intended strictly for use within the scope of this remote sensing competition - for the purpose of academic research to our mutual benefit. The data is intended for research purposes only and the WCDoA cannot be held responsible for any errors or omissions which may occur in the data.

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MLHUB Short Name: A Fusion Dataset for Crop Type Classification in Western Cape, South Africa Version ID: 1 Unique ID: C2781412697-MLHUB

This dataset provides vegetation information for 64 coastal wetland plots and coastal wetland extent maps for three habitat classes in 84 estuaries in South Africa. The vegetation plot data include vegetation species occurrence, percent cover, salinity, representative vegetation heights, porewater salinity, and ground temperature. In situ plot data were collected between October 27 and November 10, 2023, in Swartvlei Estuary, Wilderness Lakes, Knynsa Estuary, and Langebaan Lagoon within lands administered by the South African National Parks. The habitat extent maps were created for 84 estuaries across the Greater Cape Floristic Region. The classification is a single point in time representing the growing season when the plot data were collected (December 2023-January 2024). The habitat extent data were created with PlanetScope satellite classified with a U-Net semantic segmentation algorithm. The habitats classified are salt marsh, submerged aquatic vegetation, and reeds & sedges. Plot and habitat data were collected and created to inform analysis of the imaging spectroscopy and LiDAR data collected as part of the BioSCape field campaign. The data are provided in cloud optimized GeoTIFF, comma separated values, and geopackage formats.

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ORNL_CLOUD Short Name: BioSCape_EstuaryVegHabitats_2441 Version ID: 1 Unique ID: C3868387927-ORNL_CLOUD

The transboundary Pumpqu/Arun River basin spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumpqu River flows. The river is named the Arun River once it enters Nepal. Five large hydropower projects (in total about 3,163 MW) are currently under construction or are planned for the Arun River valley. Rainfall and earthquake-induced landslides, landslide dammed lakes, and landslide-induced glacial lake outburst floods pose major risks to the smooth operation of these projects. This data set is a multitemporal landslide inventory covering the whole Pumpqu/Arun River basin. It was generated in support of the World Bank’s Risk Assessment of Landslides in the Upper Arun Hydropower Project.

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NSIDC_CPRD Short Name: HMA2_MTLI Version ID: 1 Unique ID: C3266794239-NSIDC_CPRD

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 on satellite imagery and pave the way to a global monitoring system for controlling and preventing the accumulation of marine debris in oceans. This dataset consists of images of marine debris which are 256 by 256 pixels in size and labels which are bounding boxes with geographical coordinates. The images were obtained from PlanetScope optical imagery which has a spatial resolution of approximately 3 meters. In this dataset, marine debris consists of floating objects on the ocean surface which can belong to one or more classes namely plastics, algae, sargassum, wood, and other artificial items. Several studies were used for data collection and validation. While a small percentage of the dataset represents the coastlines of Ghana and Greece, most of the observations surround the Bay Islands in Honduras. The marine debris detection models created and the relevant code for using this dataset can be found [here](https://github.com/NASA-IMPACT/marine_debris_ML).

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MLHUB Short Name: Marine Debris Dataset for Object Detection in Planetscope Imagery Version ID: 1 Unique ID: C2781412735-MLHUB

The PlanetScope Level 1B Basic Scene and Level 3B Ortho Scene full archive products are available as part of Planet imagery offer. The Unrectified Asset: PlanetScope Basic Analytic Radiance (TOAR) product is a Scaled Top of Atmosphere Radiance (at sensor) and sensor corrected product, without correction for any geometric distortions inherent in the imaging processes and is not mapped to a cartographic projection. The imagery data is accompanied by Rational Polynomial Coefficients (RPCs) to enable orthorectification by the user. This kind of product is designed for users with advanced image processing and geometric correction capabilities. Basic Scene Product Components and Format Product Components Image File (GeoTIFF format) Metadata File (XML format) Rational Polynomial Coefficients (XML format) Thumbnail File (GeoTIFF format) Unusable Data Mask UDM File (GeoTIFF format) Usable Data Mask UDM2 File (GeoTIFF format) Bands 4-band multispectral image (blue, green, red, near-infrared) or 8-band (coastal-blue, blue, green I, green, yellow, red, Rededge, near-infrared) Ground Sampling Distance Approximate, satellite altitude dependent Dove-C: 3.0 m-4.1 m Dove-R: 3.0 m-4.1 m SuperDove: 3.7 m-4.2 m Accuracy <10 m RMSE The Rectified assets: The PlanetScope Ortho Scene product is radiometrically-, sensor- and geometrically- corrected and is projected to a UTM/WGS84 cartographic map projection. The geometric correction uses fine Digital Elevation Models (DEMs) with a post spacing of between 30 and 90 metres. Ortho Scene Product Components and Format Product Components Image File (GeoTIFF format) Metadata File (XML format) Thumbnail File (GeoTIFF format) Unusable Data Mask UDM File (GeoTIFF format) Usable Data Mask UDM2 File (GeoTIFF format) Bands 3-band natural colour (red, green, blue) or 4-band multispectral image (blue, green, red, near-infrared) or 8-band (coastal-blue, blue, green I, green, yellow, red, RedEdge, near-infrared) Ground Sampling Distance Approximate, satellite altitude dependent Dove-C: 3.0 m-4.1 m Dove-R: 3.0 m-4.1 m SuperDove: 3.7 m-4.2 m Projection UTM WGS84 Accuracy <10 m RMSE PlanetScope Ortho Scene product is available in the following: PlanetScope Visual Ortho Scene product is orthorectified and colour-corrected (using a colour curve) 3-band RGB Imagery. This correction attempts to optimise colours as seen by the human eye providing images as they would look if viewed from the perspective of the satellite. PlanetScope Surface Reflectance product is orthorectified, 4-band BGRN or 8-band Coastal Blue, Blue, Green I, Green, Yellow, Red, RedEdge, NIR Imagery with geometric, radiometric and corrected for surface reflection. This data is optimal for value-added image processing such as land cover classifications. PlanetScope Analytic Ortho Scene Surface Reflectance product is orthorectified, 4-band BGRN or 8-band Coastal Blue, Blue, Green I, Green, Yellow, Red, RedEdge, NIR Imagery with geometric, radiometric and calibrated to top of atmosphere radiance. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

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ESA Short Name: PlanetScope.Full.Archive Version ID: 8.0 Unique ID: C1965336933-ESA