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Annual 30-m maps of global grassland class and extent (2000-2022) based on spatiotemporal Machine Learning.

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第一作者： Leandro,Parente

第一单位： OpenGeoHub Foundation, Doorwerth, The Netherlands. leandro.parente@opengeohub.org.

作者： Leandro,Parente ^[1] ; Lindsey,Sloat ^[2] ; Vinicius,Mesquita ^[3] ; Davide,Consoli ^[4] ; Radost,Stanimirova ^[2] ; Tomislav,Hengl ^[4] ; Carmelo,Bonannella ^[5] ; Nathália,Teles ^[3] ; Ichsani,Wheeler ^[4] ; Maria,Hunter ^[3] ; Steffen,Ehrmann ^[6] ; Laerte,Ferreira ^[3] ; Ana Paula,Mattos ^[3] ; Bernard,Oliveira ^[3] ; Carsten,Meyer ^[7] ; Murat,Şahin ^[4] ; Martijn,Witjes ^[5] ; Steffen,Fritz ^[8] ; Ziga,Malek ^[8] ; Fred,Stolle ^[2]

作者单位： OpenGeoHub Foundation, Doorwerth, The Netherlands. leandro.parente@opengeohub.org. ^[1] Land & Carbon Lab, World Resources Institute, Washington, DC, USA. ^[2] Remote Sensing and GIS Laboratory (LAPIG/UFG), Goiânia, Brazil. ^[3] OpenGeoHub Foundation, Doorwerth, The Netherlands. ^[4] OpenGeoHub Foundation, Doorwerth, The Netherlands.;Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Wageningen, The Netherlands. ^[5] International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.;German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.;Institute of Biology, Leipzig University, Leipzig, Germany. ^[6] German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.;Institute of Biology, Leipzig University, Leipzig, Germany.;Institute of Geosciences and Geography, Martin Luther University Halle-Wittenberg, Halle, Saale, Germany. ^[7] International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria. ^[8]

DOI 10.1038/s41597-024-04139-6

PMID 39663386

发布时间 2024-12-14

基金项目

202548816/Deutsche Forschungsgemeinschaft (German Research Foundation)

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2024年11卷1期

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Annual 30-m maps of global grassland class and extent (2000-2022) based on spatiotemporal Machine Learning.

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Annual 30-m maps of global grassland class and extent (2000-2022) based on spatiotemporal Machine Learning.

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