Monitoring Spatial-Temporal Variability of Vegetation Coverage and Its Influencing Factors in the Yellow River Source Region from 2000 to 2020

被引:1
作者
Wang, Boyang [1 ,2 ]
Si, Jianhua [1 ]
Jia, Bing [1 ,2 ]
He, Xiaohui [1 ,2 ,3 ]
Zhou, Dongmeng [1 ,2 ]
Zhu, Xinglin [1 ,2 ]
Liu, Zijin [1 ,2 ]
Ndayambaza, Boniface [1 ,2 ]
Bai, Xue [1 ,2 ]
机构
[1] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Ecohydrol Inland River Basin, Lanzhou 730000, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Inner Mongolia Univ Sci & Technol, Baotou Teachers Coll, Fac Resources & Environm, Baotou 014030, Peoples R China
基金
中国国家自然科学基金;
关键词
vegetation coverage; spatial-temporal variation; geographic detector; FLUS model; Yellow River Source Region; CLIMATE-CHANGE; SPATIOTEMPORAL CHANGES; PLATEAU; IMPACTS; CHINA; BASIN; NDVI;
D O I
10.3390/rs16244772
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As a vital conservation area for water sources in the Yellow River Basin, understanding the spatial-temporal dynamics of vegetation coverage is crucial, along with the factors that affect it, to ensure ecological preservation and sustainable development of the Yellow River Source Region (YRSR). In this paper, we utilized Landsat surface reflectance data from 2000 to 2020 using de-clouding and masking methods implementing the Google Earth Engine (GEE) cloud platform. We investigated spatial-temporal changes in vegetation coverage by combining the maximum value composite (MVC), the dimidiate pixel model (DPM), the Theil-Sen median slope, and the Mann-Kendall test. The influencing factors on vegetation coverage were quantitatively analyzed using a geographic detector, and future tendencies in vegetation coverage were predicted utilizing the Future Land Use Simulation (FLUS) model. The outcomes suggested the following: (1) On the temporal scale, vegetation coverage exhibited a general upward trend between 2000 and 2020, with the YRSR showing a yearly growth rate of 0.23% (p < 0.001). In comparison to 2000, the area designated as having extremely high vegetation coverage increased by 19.3% in 2020. (2) Spatially, the central and southeast regions have higher values of vegetation coverage, whereas the northwest has lower values. In the study area, 75.5% of the region demonstrated a significant improvement trend, primarily in Xinghai County, Zeku County, and Dari County in the south and the northern portion of the YRSR; conversely, a notable tendency of degradation was identified in 11.8% of the area, mostly in the southeastern areas of Qumalai County, Chenduo County, Shiqu County, and scattered areas in the southeastern region. (3) With an explanatory power of exceeding 45%, the three influencing factors that had the biggest effects on vegetation coverage were mean annual temperature, elevation, and mean annual precipitation. Mean annual precipitation has been shown to have a major impact on vegetation covering; the interconnections involving these factors have increased the explanatory power of vegetation coverage's regional distribution. (4) Predictions for 2030 show that the vegetation coverage is trending upward in the YRSR, with a notable recovery trend in the northwestern region. This study supplies a theoretical foundation to formulate strategies to promote sustainable development and ecological environmental preservation in the YRSR.
引用
收藏
页数:22
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