{"data":{"id":"10.6084/m9.figshare.23542860","type":"dois","attributes":{"doi":"10.6084/m9.figshare.23542860","prefix":"10.6084","suffix":"m9.figshare.23542860","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Zhang, Tianyuan","givenName":"Tianyuan","familyName":"Zhang","nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2337-6209","nameIdentifierScheme":"ORCID"}],"affiliation":[]},{"name":"Cheng, Changxiu","givenName":"Changxiu","familyName":"Cheng","affiliation":[],"nameIdentifiers":[]},{"name":"Wu, Xudong","givenName":"Xudong","familyName":"Wu","nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0752-0282","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"Global LULC projection dataset from 2020 to 2100 at a 1km resolution"}],"publisher":"figshare","container":{},"publicationYear":2023,"subjects":[{"subject":"Land use and environmental planning","schemeUri":"http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E","subjectScheme":"ANZSRC Fields of Research","classificationCode":"330404"}],"contributors":[],"dates":[{"date":"2023-09-26","dateType":"Created"},{"date":"2023-09-27","dateType":"Updated"},{"date":"2023","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["1992765424 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The dataset is on a global scale with a resolution of 1 km grid and encompasses a timespan from 2020 to 2100. These data are projected in the world-Mercator projection coordinate system and are provided in single-band GeoTIFF format, which can be easily utilized by various mainstream GIS and RS platforms such as ArcGIS, QGIS, ENVI, as well as programming languages such as Python and MATLAB. The simulated data files follow a standardized naming convention “sspx_pp_yyyy.tif”, where x represents the simulated SSP scenario (1 to 5), pp represents the simulated RCP scenario; and yyyy represents the simulated year. For example, the data file named “ssp1_26_2030.tif” corresponds to the LULC simulation data for the year 2030 under the SSP1-2.6 scenario. Each GeoTIFF data file includes integer raster attribute values ranging from 1 to 6, which represent the following land use types: cropland, forest, grassland, urban, barren, and water.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://figshare.com/articles/dataset/Global_LULC_projection_dataset_from_2020_to_2100_at_a_1km_resolution/23542860","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"viewsOverTime":[],"downloadCount":0,"downloadsOverTime":[],"referenceCount":0,"citationCount":0,"citationsOverTime":[],"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2023-06-20T03:16:22.000Z","registered":"2023-09-26T12:47:37.000Z","published":"2023","updated":"2023-09-27T12:26:02.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.23542860","type":"media"}},"references":{"data":[]},"citations":{"data":[]},"parts":{"data":[]},"partOf":{"data":[]},"versions":{"data":[]},"versionOf":{"data":[]}}}}