期刊
INTERNATIONAL JOURNAL OF DIGITAL EARTH
卷 16, 期 1, 页码 2168-2188出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/17538947.2023.2220612
关键词
oil palm subclass; oil palm map; spatial mapping; Planet & NICFI; Sentinel-1; 2; deforestation; SDG 15
Accurate high-resolution maps of oil palm plantations are essential for effective management of their environmental and socio-economic impacts. However, current statistics and maps do not include young industrial and small-holder plantations. In this study, global oil palm plantations in 2020 were classified into four subclasses using satellite data and an image-oriented classification algorithm. The results provide valuable information for future planning and monitoring of oil palm-related development in major palm-growing countries.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据