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Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential.

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第一作者： Tomislav,Hengl

第一单位： Envirometrix Ltd, Wageningen, Netherlands.

作者： Tomislav,Hengl ^[1] ; Markus G,Walsh ^[2] ; Jonathan,Sanderman ^[3] ; Ichsani,Wheeler ^[1] ; Sandy P,Harrison ^[4] ; Iain C,Prentice ^[5]

作者单位： Envirometrix Ltd, Wageningen, Netherlands. ^[1] The Earth Institute, Columbia University, New York, NY, USA.;Selian Agricultural Research Institute, Arusha, Tanzania. ^[2] Woods Hole Research Center, Falmouth, MA, USA. ^[3] School of Archeology, Geography and Environmental Science, University of Reading, Reading, UK. ^[4] Department of Life Sciences and Grantham Institute-Climate Change and the Environment, Imperial College London, London, UK. ^[5]

关键词 Biome FAPAR Forest species Global Land potential Machine learning Natural vegetation Random forest

DOI 10.7717/peerj.5457

PMID 30155360

发布时间 2020-09-29

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