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Vegetation Cover Change and Its Attribution in China from 2001 to 2018
by
Wang, Haoyu
, Zhou, Qian
, Du, Xiaozheng
, Wu, Donghai
, Zhao, Xiang
, Mu, Baohui
, Liu, Naijing
, Zhao, Jiacheng
, Wang, Xinyan
in
Aeronautics
/ Carbon dioxide
/ China
/ climate change
/ Computer centers
/ Correlation analysis
/ ecological restoration
/ Ecosystem services
/ Environmental restoration
/ Forests
/ fractional vegetation cover
/ Generalized linear models
/ Grasslands
/ Greening
/ Laboratories
/ Land cover
/ land cover change
/ Precipitation
/ Remote sensing
/ satellites
/ Short wave radiation
/ shortwave radiation
/ Standard deviation
/ Statistical models
/ temperature
/ terrestrial ecosystems
/ Trends
/ Vegetation
/ vegetation change
/ Vegetation changes
/ Vegetation cover
/ Vegetation growth
2021
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Vegetation Cover Change and Its Attribution in China from 2001 to 2018
by
Wang, Haoyu
, Zhou, Qian
, Du, Xiaozheng
, Wu, Donghai
, Zhao, Xiang
, Mu, Baohui
, Liu, Naijing
, Zhao, Jiacheng
, Wang, Xinyan
in
Aeronautics
/ Carbon dioxide
/ China
/ climate change
/ Computer centers
/ Correlation analysis
/ ecological restoration
/ Ecosystem services
/ Environmental restoration
/ Forests
/ fractional vegetation cover
/ Generalized linear models
/ Grasslands
/ Greening
/ Laboratories
/ Land cover
/ land cover change
/ Precipitation
/ Remote sensing
/ satellites
/ Short wave radiation
/ shortwave radiation
/ Standard deviation
/ Statistical models
/ temperature
/ terrestrial ecosystems
/ Trends
/ Vegetation
/ vegetation change
/ Vegetation changes
/ Vegetation cover
/ Vegetation growth
2021
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Do you wish to request the book?
Vegetation Cover Change and Its Attribution in China from 2001 to 2018
by
Wang, Haoyu
, Zhou, Qian
, Du, Xiaozheng
, Wu, Donghai
, Zhao, Xiang
, Mu, Baohui
, Liu, Naijing
, Zhao, Jiacheng
, Wang, Xinyan
in
Aeronautics
/ Carbon dioxide
/ China
/ climate change
/ Computer centers
/ Correlation analysis
/ ecological restoration
/ Ecosystem services
/ Environmental restoration
/ Forests
/ fractional vegetation cover
/ Generalized linear models
/ Grasslands
/ Greening
/ Laboratories
/ Land cover
/ land cover change
/ Precipitation
/ Remote sensing
/ satellites
/ Short wave radiation
/ shortwave radiation
/ Standard deviation
/ Statistical models
/ temperature
/ terrestrial ecosystems
/ Trends
/ Vegetation
/ vegetation change
/ Vegetation changes
/ Vegetation cover
/ Vegetation growth
2021
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Vegetation Cover Change and Its Attribution in China from 2001 to 2018
Journal Article
Vegetation Cover Change and Its Attribution in China from 2001 to 2018
2021
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Overview
It is confirmed that China has been greening over the last two decades. Such greening and its driving factors are therefore significant for understanding the relationship between vegetation and environments. However, studies on vegetation changes and attribution analyses at the national scale are limited in China after 2000. In this study, fractional vegetation cover (FVC) data from Global Land Surface Satellite (GLASS) was used to detect vegetation change trends from 2001 to 2018, and the effects of CO2, temperature, shortwave radiation, precipitation, and land cover change (LCC) on FVC changes were quantified using generalized linear models (GLM). The results showed that (1) FVC in China increased by 14% from 2001 to 2018 with a greening rate of approximately 0.0019/year (p < 0.01), which showed an apparent greening trend. (2) On the whole, CO2, climate-related factors, and LCC accounted for 88% of FVC changes in China, and the drivers explained 82%, 89%, 90%, and 89% of the FVC changes in the Qinghai–Tibet region, northwest region, northern region, and southern region, respectively. CO2 was the major driving factor for FVC changes, accounting for 31% of FVC changes in China, indicating that CO2 was an essential factor in vegetation growth research. (3) The statistical results of pixels with land cover changes showed that LCC explained 12% of FVC changes, LCC has played a relatively important role and this phenomenon may be related to the ecological restoration projects. This study enriches the study of vegetation changes and its driving factors, and quantitatively describes the response relationship between vegetation and its driving factors. The results have an important significance for adjusting terrestrial ecosystem services.
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