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Vegetation Changes and Its Driving Factors in the Three-River Headwaters Region from 1990 to 2022

文献类型：期刊论文

作者Wang, Chen1; Wang, Junbang2; Dong, Zhiwen1; Wang, Shaoqiang1,2; Jiao, Xiaoyu1
刊名REMOTE SENSING
出版日期2025-12-06
卷号17期号:24页码:3947
关键词Three-River Headwaters region fractional vegetation coverage geographic detector land cover active layer thickness deep learning
DOI10.3390/rs17243947
产权排序2
文献子类Article
英文摘要Highlights What are the main findings? Vegetation coverage in Three-River Headwaters rose, with high coverage areas up 10.3%. Bare land down-shifted to grassland and shrubs, forests, and grassland significantly upshifted. What are the implications of the main findings? This study offers a scientific foundation for monitoring and ecological conservation. We reveal the dynamic changes of vegetation and environmental driving mechanisms.Highlights What are the main findings? Vegetation coverage in Three-River Headwaters rose, with high coverage areas up 10.3%. Bare land down-shifted to grassland and shrubs, forests, and grassland significantly upshifted. What are the implications of the main findings? This study offers a scientific foundation for monitoring and ecological conservation. We reveal the dynamic changes of vegetation and environmental driving mechanisms.Abstract Changes in vegetation coverage reflect the status and dynamic processes of ecosystems and serve as a crucial foundation for regional ecological protection. Using Landsat-5 and Sentinel-2 data, this study calculated the vegetation coverage in the Three-River Headwaters (TRH) region from 1990 to 2022 with the pixel dichotomy model, identified land cover changes over the past three decades via a deep neural network, and analyzed the primary influencing factors behind vegetation coverage dynamics. The results indicate that vegetation coverage in TRH has generally increased, as very high vegetation coverage expanded by 10.3%, while very low and low vegetation coverage decreased by 4.2%. Extensive bare land in the western region decreased and transformed into grassland, while the areas of shrubland and forest in the central and eastern TRH areas increased. The areas of grassland, shrubland, and forest increased by 3.7 x 104 km2, 2.1 x 104 km2, and 4.7 x 103 km2, respectively. Precipitation, elevation, and temperature are the main factors influencing the spatial variation in vegetation coverage. We found that the contributions of the permafrost active layer thickness and precipitation to changes in vegetation coverage are high. Finally, we provide a detailed and timely analysis of recent vegetation distribution and type changes on the Tibetan Plateau, offering a strengthened scientific foundation for monitoring, assessment, and ecological conservation efforts aimed at supporting ecosystem restoration in the region.
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WOS关键词GOOGLE EARTH ENGINE ; COVERAGE
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001647392000001
出版者MDPI
源URL[http://ir.igsnrr.ac.cn/handle/311030/219454]  
专题生态系统网络观测与模拟院重点实验室_外文论文
通讯作者Wang, Junbang
作者单位1.China Univ Geosci Wuhan, Sch Geog & Informat Engn, Hubei Key Lab Reg Ecol & Environm Change, Wuhan 430074, Peoples R China;
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100001, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Chen,Wang, Junbang,Dong, Zhiwen,et al. Vegetation Changes and Its Driving Factors in the Three-River Headwaters Region from 1990 to 2022[J]. REMOTE SENSING,2025,17(24):3947.
APA Wang, Chen,Wang, Junbang,Dong, Zhiwen,Wang, Shaoqiang,&Jiao, Xiaoyu.(2025).Vegetation Changes and Its Driving Factors in the Three-River Headwaters Region from 1990 to 2022.REMOTE SENSING,17(24),3947.
MLA Wang, Chen,et al."Vegetation Changes and Its Driving Factors in the Three-River Headwaters Region from 1990 to 2022".REMOTE SENSING 17.24(2025):3947.

入库方式： OAI收割

来源：地理科学与资源研究所

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