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Time-series satellite images reveal abrupt changes in vegetation dynamics and possible determinants in the Yellow River Basin
Agricultural and Forest Meteorology ( IF 5.6 ) Pub Date : 2024-06-19 , DOI: 10.1016/j.agrformet.2024.110124 Xinyuan Jiang , Xiuqin Fang , Qiuan Zhu , Jiaxin Jin , Liliang Ren , Shanhu Jiang , Yiqi Yan , Shanshui Yuan , Meiyu Liao
Agricultural and Forest Meteorology ( IF 5.6 ) Pub Date : 2024-06-19 , DOI: 10.1016/j.agrformet.2024.110124 Xinyuan Jiang , Xiuqin Fang , Qiuan Zhu , Jiaxin Jin , Liliang Ren , Shanhu Jiang , Yiqi Yan , Shanshui Yuan , Meiyu Liao
A comprehensive understanding of vegetation dynamics over long term periods is crucial for protecting regional ecosystems. The Yellow River Basin in China has experienced vegetation greening over recent decades, but detailed documentation of abrupt vegetation changes during this process is limited. Here, based on the Global Inventory Modeling and Mapping Studies (GIMMS) dataset, we applied the Breaks for Additive Seasonal and Trend (BFAST) to the normalized difference vegetation index (NDVI) from 1982 to 2020, in order to investigate the spatiotemporal patterns of abrupt and gradual vegetation changes in the Yellow River Basin. During the target period, 67 % of the basin areas experienced at least one abrupt change. Abrupt changes occurred frequently in most areas of the upper reaches, but were relatively rare in the source region. Abrupt greening events were widespread in the middle and upper reaches, with over 90 % following the large-scale implementation of ecological restoration projects. Abrupt browning events were mainly concentrated in areas with intensive agricultural and urban lands. 74 % of the areas that experienced abrupt changes maintained their previous gradual trends after the abrupt changes. Compared to vegetation in the upper reaches, vegetation in the middle reaches was more prone to gradually greening after disturbances. Through residual analysis, we identified both climate change and human activities as drivers of greening in most parts of the basin, with human activities dominating over climate change in driving greening after 2000. Our findings suggest that non-linear analysis methods that consider abrupt changes can reveal more details of long-term vegetation dynamics and provide scientific guidance for regional ecological restoration.
更新日期：2024-06-19
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