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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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: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2022
Subjects:
Online Access:https://doi.org/10.3390/rs14040839
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spelling ftmdpi:oai:mdpi.com:/2072-4292/14/4/839/ 2023-08-20T04:10:14+02:00 Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities Baohui Mu Xiang Zhao Jiacheng Zhao Naijing Liu Longping Si Qian Wang Na Sun Mengmeng Sun Yinkun Guo Siqing Zhao agris 2022-02-10 application/pdf https://doi.org/10.3390/rs14040839 EN eng Multidisciplinary Digital Publishing Institute Urban Remote Sensing https://dx.doi.org/10.3390/rs14040839 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 4; Pages: 839 fractional vegetation cover urbanization climate change vegetation change Text 2022 ftmdpi https://doi.org/10.3390/rs14040839 2023-08-01T04:07:16Z 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 CO2 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 CO2, 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 CO2 were the major factors that affected FVC change. The average contributions of climate factors, CO2, 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. Text Tundra MDPI Open Access Publishing Remote Sensing 14 4 839
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic fractional vegetation cover
urbanization
climate change
vegetation change
spellingShingle fractional vegetation cover
urbanization
climate change
vegetation change
Baohui Mu
Xiang Zhao
Jiacheng Zhao
Naijing Liu
Longping Si
Qian Wang
Na Sun
Mengmeng Sun
Yinkun Guo
Siqing Zhao
Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities
topic_facet fractional vegetation cover
urbanization
climate change
vegetation change
description 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 CO2 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 CO2, 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 CO2 were the major factors that affected FVC change. The average contributions of climate factors, CO2, 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.
format Text
author Baohui Mu
Xiang Zhao
Jiacheng Zhao
Naijing Liu
Longping Si
Qian Wang
Na Sun
Mengmeng Sun
Yinkun Guo
Siqing Zhao
author_facet Baohui Mu
Xiang Zhao
Jiacheng Zhao
Naijing Liu
Longping Si
Qian Wang
Na Sun
Mengmeng Sun
Yinkun Guo
Siqing Zhao
author_sort Baohui Mu
title Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities
title_short Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities
title_full Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities
title_fullStr Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities
title_full_unstemmed Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities
title_sort quantitatively assessing the impact of driving factors on vegetation cover change in china’s 32 major cities
publisher Multidisciplinary Digital Publishing Institute
publishDate 2022
url https://doi.org/10.3390/rs14040839
op_coverage agris
genre Tundra
genre_facet Tundra
op_source Remote Sensing; Volume 14; Issue 4; Pages: 839
op_relation Urban Remote Sensing
https://dx.doi.org/10.3390/rs14040839
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs14040839
container_title Remote Sensing
container_volume 14
container_issue 4
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