Using PLE-SEM to Quantify the Impacts of Natural and Human Factors on Vegetation Change: A Case Study of the Jialing River Basin

Xingyue Guo, Tian Wang (), Zhanbin Li, Shengdong Cheng, Peng Li, Hongtao Li, Naichang Zhang, Xiaoping Liu and Ziyao Miao
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Xingyue Guo: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710054, China
Tian Wang: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710054, China
Zhanbin Li: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710054, China
Shengdong Cheng: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710054, China
Peng Li: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710054, China
Hongtao Li: Northwest Surveying, Planning Institute of National Forestry and Grassland Administration, Xi′an 710048, China
Naichang Zhang: Northwest Engineering Corporation Limited, Xi’an 710065, China
Xiaoping Liu: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710054, China
Ziyao Miao: Yulin High-Tech Zone Yuheng No. 1 Industrial Sewage Treatment Company, Yulin Coal Chemical Waste Resource Utilization and Low Carbon Environmental Protection Engineering Technology Research Center, Yulin 719000, China

Sustainability, 2023, vol. 15, issue 17, 1-16

Abstract: Vegetation cover is an important indicator reflecting changes in terrestrial ecosystems and plays an important role in regulating and maintaining ecosystem stability. To investigate the spatial and temporal variations in the NDVI (normalized difference vegetation index) and their intrinsic driving influences, this paper uses trend analysis and a barycentric model to study the temporal and spatial variation characteristics of vegetation in the Jialing River Basin from 2000 to 2020, constructs PLS-SEMs (partial least squares structural equation models), analyzes the indirect and direct effects of latent and observable variables of surface, human activities, and climate on vegetation growth, and explores the driving processes of different levels of NDVI. The vegetation center gradually migrates northwards. The impact of surface factors on the NDVI is mainly direct and positive. The impact of human activities on the NDVI is mainly direct and negative. The impact of climate factors on the NDVI is mainly positive. The driving mechanisms of low and medium NDVI are relatively similar but tend to be opposite to those of high NDVI. Medium and high NDVI values are more influenced by observable variables. The research on vegetation change and its driving factors, through indirect and direct paths, illustrates the driving processes of different latent and observable variables of the NDVI in more detail and provides a theoretical basis for the implementation of ecological restoration projects and construction of ecological civilizations in the future.

Keywords: NDVI; PLS-SEM; driver analysis; Jialing River Basin; vegetation cover; driver (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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