Print Email Facebook Twitter Understanding spatial patterns in the drivers of greenness trends in the Sahel-Sudano-Guinean region Title Understanding spatial patterns in the drivers of greenness trends in the Sahel-Sudano-Guinean region Author Jiang, Min (Chinese Academy of Sciences) Jia, Li (Chinese Academy of Sciences) Menenti, M. (TU Delft Optical and Laser Remote Sensing; Chinese Academy of Sciences) Zeng, Yelong (University of Chinese Academy of Sciences; Chinese Academy of Sciences) Date 2022 Abstract 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. Subject driving factorsprincipal component regressionSahel-Sudano-GuineanVegetation greenness To reference this document use: http://resolver.tudelft.nl/uuid:a8c23f6b-f7e4-42d6-970b-7d04365c1b98 DOI https://doi.org/10.1080/20964471.2022.2146632 ISSN 2096-4471 Source Big Earth Data, 7 (2), 298-317 Part of collection Institutional Repository Document type journal article Rights © 2022 Min Jiang, Li Jia, M. Menenti, Yelong Zeng Files PDF Understanding_spatial_pat ... region.pdf 11.96 MB Close viewer /islandora/object/uuid:a8c23f6b-f7e4-42d6-970b-7d04365c1b98/datastream/OBJ/view