摘要
Accurate high-resolution maps of oil palm plantations underpin effective management of environmental and socio-economic impacts at global,regional,and national levels.However,young industrial and highly irregular small-holder plantations are mostly unmapped and not included in official FAO statistics.This issue is addressed here by discriminating global oil palm plantation in 2020 into four subclasses:Industrial Mature Oil Palm(IMOP);Industrial Young Oil Palm(IYOP);Smallholder Mature Oil Palm(SMOP);and Smallholder Young Oil Palm(SYOP).Data,resolved to 4.77 m,from Planet&NICFI,Sentinel-1/2,were combined with other layers using the image-oriented classification and regression tree(CART)algorithm which performed best in classification tests.Results show that SMOP dominates distributional extent,but it was also the most accurately mapped subclass typically found at 500–1000 m altitude.IMOP had the most extensive altitude range of 500–1300 m,while IYOP and SYOP were found at similar altitudes of 500–800 m and 500–900 m respectively.Recent developments in South East Asia show oil palm plantations expanding into new areas with a slope of 24 degrees.Results provide data to support Sustainable Development Goal by assisting future oil palm-related development planning and monitoring in the world’s major oil palm-growing countries.
基金
supported by the National Key Research and Development Program of China(No.2022YFC3103103)
the Strategic Priority Research Program of Chinese Academy of Sciences(grant number XDA19060304).