Spatio-temporal evolution and driving factors of eco-environmental quality based on RSEI in Chang-Zhu-Tan metropolitan circle, central China

Yi Zhang; Jiyun She; Xiangren Long; Meng Zhang

Ecological Indicators (Nov 2022)

Spatio-temporal evolution and driving factors of eco-environmental quality based on RSEI in Chang-Zhu-Tan metropolitan circle, central China

Yi Zhang,
Jiyun She,
Xiangren Long,
Meng Zhang

Affiliations

Yi Zhang: Forestry College, Central South University of Forestry and Technology, Changsha 410004, China
Jiyun She: Forestry College, Central South University of Forestry and Technology, Changsha 410004, China
Xiangren Long: Forestry College, Central South University of Forestry and Technology, Changsha 410004, China; Research Center of Forestry Remote Sensing & Information Engineering Central South University & Technology, Changsha 410004, China; Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China; Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China
Meng Zhang: Forestry College, Central South University of Forestry and Technology, Changsha 410004, China; Research Center of Forestry Remote Sensing & Information Engineering Central South University & Technology, Changsha 410004, China; Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China; Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China; Corresponding author.

Journal volume & issue: Vol. 144
p. 109436

Abstract

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Accurately analyzing the spatial and temporal evolution of regional eco-environmental quality and exploring the response of eco-environmental quality to natural environment and human factors are essential to protect the regional ecological environment. This study analyzed the ecological environmental quality of Chang-Zhu-Tan metropolitan circle, central China from 2000 to 2020 based on Google Earth Engine (GEE) and Remote Sensing Ecological Index (RSEI). Subsequently, we introduced the Partial Least Squares Structural Equation Model (PLS-SEM) to explore the response of RSEI to the direct and indirect effects of natural and anthropogenic factors, and assessed the spatial autocorrelation of regional ecological environmental quality. The results showed that the mean value of RSEI in the study area was showing an increasing trend, with the lowest mean value of RSEI in 2010 (0.6508) and the highest mean value of RSEI in 2020 (0.6948). The eco-environmental quality level was mainly good and excellent, and the average area accounted for more than 70% of the total area, and showed an upward trend during 2000–2020. Climate, soil, terrain, and urbanization had different effects on the ecological environment, with climate, soil, and terrain had positive effects on the ecological environment, while urbanization had negative effects on it. The positive effect of climate on ecological environment was gradually weakened, while the negative effect of urbanization on ecological environment was gradually strengthened. Climate and urbanization weakened the positive effect of soil and terrain in different degrees. This study provides a method for rapid and accurate assessment of regional eco-environmental quality and exploration of complex interaction pathways of influencing factors, which is essential for balancing the relationship between regional development and nature.

Published in Ecological Indicators

ISSN: 1470-160X (Print); 1872-7034 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General): Ecology
Website: https://www.sciencedirect.com/journal/ecological-indicators

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