{"id":"io-lulc-9-class","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/collections/io-lulc-9-class/items"},{"rel":"parent","type":"application/json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/"},{"rel":"root","type":"application/json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/"},{"rel":"self","type":"application/json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/collections/io-lulc-9-class"},{"rel":"related","href":"https://livingatlas.arcgis.com/landcover/"},{"rel":"license","href":"https://creativecommons.org/licenses/by/4.0/","type":"text/html","title":"CC BY 4.0"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://planetarycomputer.microsoft.com/api/stac/v1/collections/io-lulc-9-class/queryables"},{"rel":"describedby","href":"https://planetarycomputer.microsoft.com/dataset/io-lulc-9-class","title":"Human readable dataset overview and reference","type":"text/html"}],"title":"10m Annual Land Use Land Cover (9-class) V1","assets":{"thumbnail":{"href":"https://ai4edatasetspublicassets.blob.core.windows.net/assets/pc_thumbnails/io-lulc-9-class.png","title":"10m Annual Land Use Land Cover (9-class)","media_type":"image/png"},"geoparquet-items":{"href":"abfs://items/io-lulc-9-class.parquet","type":"application/x-parquet","roles":["stac-items"],"title":"GeoParquet STAC items","description":"Snapshot of the collection's STAC items exported to GeoParquet format.","msft:partition_info":{"is_partitioned":false},"table:storage_options":{"account_name":"pcstacitems"}}},"extent":{"spatial":{"bbox":[[-180,-90,180,90]]},"temporal":{"interval":[["2017-01-01T00:00:00Z","2023-01-01T00:00:00Z"]]}},"license":"CC-BY-4.0","keywords":["Global","Land Cover","Land Use","Sentinel"],"providers":[{"url":"https://www.esri.com/","name":"Esri","roles":["licensor"]},{"url":"https://www.impactobservatory.com/","name":"Impact Observatory","roles":["processor","producer","licensor"]},{"url":"https://planetarycomputer.microsoft.com","name":"Microsoft","roles":["host"]}],"summaries":{"raster:bands":[{"nodata":0,"spatial_resolution":10}]},"description":"__Note__: _A new version of this item is available for your use. This mature version of the map remains available for use in existing applications. This item will be retired in December 2024. There is 2023 data available in the newer [9-class v2 dataset](https://planetarycomputer.microsoft.com/dataset/io-lulc-annual-v02)._\n\nTime series of annual global maps of land use and land cover (LULC). It currently has data from 2017-2022. The maps are derived from ESA Sentinel-2 imagery at 10m resolution. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year.\n\nThis dataset was generated by [Impact Observatory](http://impactobservatory.com/), who used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. The global map was produced by applying this model to the Sentinel-2 annual scene collections on the Planetary Computer. Each of the maps has an assessed average accuracy of over 75%.\n\nThis map uses an updated model from the [10-class model](https://planetarycomputer.microsoft.com/dataset/io-lulc) and combines Grass(formerly class 3) and Scrub (formerly class 6) into a single Rangeland class (class 11). The original Esri 2020 Land Cover collection uses 10 classes (Grass and Scrub separate) and an older version of the underlying deep learning model.  The Esri 2020 Land Cover map was also produced by Impact Observatory.  The map remains available for use in existing applications. New applications should use the updated version of 2020 once it is available in this collection, especially when using data from multiple years of this time series, to ensure consistent classification.\n\nAll years are available under a Creative Commons BY-4.0.","item_assets":{"data":{"type":"image/tiff; application=geotiff; profile=cloud-optimized","roles":["data"],"title":"Global land cover data","file:values":[{"values":[0],"summary":"No Data"},{"values":[1],"summary":"Water"},{"values":[2],"summary":"Trees"},{"values":[4],"summary":"Flooded vegetation"},{"values":[5],"summary":"Crops"},{"values":[7],"summary":"Built area"},{"values":[8],"summary":"Bare ground"},{"values":[9],"summary":"Snow/ice"},{"values":[10],"summary":"Clouds"},{"values":[11],"summary":"Rangeland"}]}},"msft:region":"westeurope","stac_version":"1.0.0","msft:group_id":"io-land-cover","msft:container":"io-lulc","stac_extensions":["https://stac-extensions.github.io/item-assets/v1.0.0/schema.json","https://stac-extensions.github.io/raster/v1.0.0/schema.json","https://stac-extensions.github.io/label/v1.0.0/schema.json","https://stac-extensions.github.io/file/v2.1.0/schema.json","https://stac-extensions.github.io/table/v1.2.0/schema.json"],"msft:storage_account":"ai4edataeuwest","msft:short_description":"Global land cover information with 9 classes for 2017-2022 at 10m resolution"}