Change and driving factors of vegetation coverage in the Yellow River Basin
WANG Xiao-lei1,2, SHI Shou-hai1, CHEN jiang-zhao-xia1
1. School of Geoscience and Technology, Zhengzhou University, Zhengzhou 450000, China; 2. Joint Laboratory of Eco-Meteorology, Zhengzhou University, Chinese Academy of Meteorological Sciences, Zhengzhou University, Zhengzhou 450000, China
Abstract：The pixel binary model was used to inverse the fractional vegetation cover (FVC) from 1999 to 2019 based on the Google Earth Engine platform, and the unary linear regression analysis and the coefficient of variance method were used to study the changes in the FVC trend characteristics and stability. The geographic detector was used to analyze the driving force of vegetation change. The results showed that: (1) The FVC of the Yellow River Basin was generally low in the northwest and high in the Southeast; the medium-high and high-covered areas accounted for 21.74% and 17.87% of the study area, respectively; the FVC of the Yellow River Basin had improved well in the past two decades. The improvement of vegetation in the middle reaches of the basin was the most obvious, and the improvement area accounted for 48.52% of the total area in our study area; the stability of FVC was mainly stable. (2) The three driving factors of precipitation, sunshine duration, and relative humidity had the strongest influence on FVC in the Yellow River Basin. (3) Each driving factor had an interaction effect on the FVC. The two-factor enhancement or nonlinear enhancement was the main factor. The two-factor interaction enhanced the impact of the single factor. This study also revealed the most suitable range of factors that promoted vegetation growth. These results help to better understand the impact of natural and social factors on vegetation cover changes and their driving mechanisms.
王晓蕾, 石守海, 陈江朝霞. 黄河流域植被覆盖度变化及驱动因素[J]. 中国环境科学, 2022, 42(11): 5358-5368.
WANG Xiao-lei, SHI Shou-hai, CHEN jiang-zhao-xia. Change and driving factors of vegetation coverage in the Yellow River Basin. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(11): 5358-5368.
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