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Understanding spatial patterns in the drivers of greenness trends in the sahel-sudano-guinean region

Big Earth Data 2023年第2期7卷 298-317页

作者： Min Jiang Li Jia Massimo Menenti Yelong Zeng State Key Laboratory of Remote Sensing Sciences Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina Department of Geoscience and Remote Sensing Delft University of TechnologyDelftThe Netherlands University of Chinese Academy of Sciences BeijingChina

The region-wide spatial pattern of the drivers of vegetation trends in the African sahel-sudano-guinean region, one of the main drylands of the world, has not been fully investigated. Time-series satellite earth observation datasets were used to investigate spatiotemporal patterns of the vegetation greenness changes in the region and then a principal component regression method was applied to identify the region-wide spatial pattern of driving factors. Results find that vegetation greening is widespread in the region, while vegetation browning is more clustered in central West Africa. The dominant drivers of vegetation greenness have a distinct spatial pattern. Climatic factors are the primary drivers, but the impacts of precipitation decrease from north to south, while the impacts of temperature are contrariwise. Coupled with climatic drivers, land cover changes lead to greening trends in the arid zone, especially in the western sahelian belt. However, the cluster of browning trends in central West Africa can primarily be attributed to the human-induced land cover changes, including an increasing fractional abundance of agriculture. The results highlight the spatial pattern of climatic and anthropic factors driving vegetation greenness changes, which helps natural resources sustainable use and mitigation of climate change and human activities in global dryland ecosystems.

关键词： Vegetation greenness driving factors sahel-sudano-guinean principal component regression

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