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Quantitative analysis of spatial and temporal variations and drivers of vegetation cover in Qinghai Province, China, based on Geodetector
  • +8
  • Shuwei Wang,
  • Wenwu Zhou,
  • Jinge Yu,
  • Shaolong Luo,
  • Li Xu,
  • Yingqun Gao,
  • Chaosheng Guo,
  • Zhengdao Yang,
  • Huanfen Yang,
  • Zaikun Wu,
  • Qingtai Shu
Shuwei Wang
Southwest Forestry University
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Wenwu Zhou
Southwest Forestry University
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Jinge Yu
Southwest Forestry University
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Shaolong Luo
Southwest Forestry University
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Li Xu
Southwest Forestry University
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Yingqun Gao
Southwest Forestry University
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Chaosheng Guo
Southwest Forestry University
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Zhengdao Yang
Southwest Forestry University
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Huanfen Yang
Southwest Forestry University
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Zaikun Wu
Southwest Forestry University
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Qingtai Shu
Southwest Forestry University

Corresponding Author:[email protected]

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Abstract

Qinghai Province is an important part of the ‘ Third Pole of the World ’ Tibetan Plateau. Under the background of global warming, the climate and ecological environment of the Tibetan Plateau have undergone dramatic changes. Assessing the response of vegetation cover change to climate change in Qinghai Province in the 21st century and driving force analysis will help to understand the trend of climate change in the Tibetan Plateau and its impact on the ecological environment. It is of great significance to promote the ecological protection and high-quality development of the Tibetan Plateau. Based on Google Earth Engine cloud computing platform, MODIS MOD13Q1 data, land use type data, meteorological data, digital elevation model data and population density data, this paper uses pixel dichotomy model, trend analysis, coefficient of variation method and other methods to comprehensively analyze the temporal and spatial variation characteristics of vegetation cover in Qinghai Province from 2000 to 2020, and quantitatively analyzes the response characteristics of vegetation cover change to driving factors in the past 21 years through geodetector, and discusses the driving factors affecting vegetation cover change. Explanatory power, interaction type and mechanism of action. The Hurst index was used to predict the future trend of vegetation cover in Qinghai Province.