Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities

After 2000, China’s vegetation underwent great changes associated with climate change and urbanization. Although many studies have been conducted to quantify the contributions of climate and human activities to vegetation, few studies have quantitatively examined the comprehensive contributions of c...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Baohui Mu, Xiang Zhao, Jiacheng Zhao, Naijing Liu, Longping Si, Qian Wang, Na Sun, Mengmeng Sun, Yinkun Guo, Siqing Zhao
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2022
Subjects:
Q
Online Access:https://doi.org/10.3390/rs14040839
https://doaj.org/article/59d92e30cc8049d9a1b9704ba7fcd23d
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Summary:After 2000, China’s vegetation underwent great changes associated with climate change and urbanization. Although many studies have been conducted to quantify the contributions of climate and human activities to vegetation, few studies have quantitatively examined the comprehensive contributions of climate, urbanization, and CO 2 to vegetation in China’s 32 major cities. In this study, using Global Land Surface Satellite (GLASS) fractional vegetation cover (FVC) between 2001 and 2018, we investigated the trend of FVC in China’s 32 major cities and quantified the effects of CO 2 , urbanization, and climate by using generalized linear models (GLMs). We found the following: (1) From 2001 to 2018, the FVC in China generally illustrated an increasing trend, although it decreased in 23 and 21 cities in the core area and expansion area, respectively. (2) Night light data showed that the urban expansion increased to varying degrees, with an average increasing ratio of approximately 168%. The artificial surface area increased significantly, mainly from cropland, forest, grassland, and tundra. (3) Climate factors and CO 2 were the major factors that affected FVC change. The average contributions of climate factors, CO 2 , and urbanization were 40.6%, 39.2%, and 10.6%, respectively. This study enriched the understanding of vegetation cover change and its influencing factors, helped to explain the complex biophysical mechanism between vegetation and environment, and guided sustainable urban development.