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Article

Spatio-Temporal Analysis of Ecological Vulnerability and Driving Factor Analysis in the Dongjiang River Basin, China, in the Recent 20 Years

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Xining Center of Natural Resources Comprehensive Survey, China Geological Survey, Xining 810000, China
3
Ministry of Education Key Laboratory of Geological Survey and Evaluation, China University of Geosciences (Wuhan), Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(22), 4636; https://doi.org/10.3390/rs13224636
Submission received: 11 October 2021 / Revised: 11 November 2021 / Accepted: 15 November 2021 / Published: 17 November 2021
(This article belongs to the Special Issue Temporal Resolution, a Key Factor in Environmental Risk Assessment)

Abstract

The global ecological environment faces many challenges. Landsat thematic mapper time-series, digital elevation models, meteorology, soil types, net primary production data, socio-economic data, and auxiliary data were collected in order to construct a comprehensive evaluation system for ecological vulnerability (EV) using multi-source remote sensing data. EV was divided into five vulnerability levels: potential I, slight II, mild III, moderate IV, and severe V. Then, we analyzed and explored the spatio-temporal patterns and driving mechanisms of EV in the region over the past 20 years. Our research results showed that, from 2001 to 2019, the DRB was generally characterized as being in the severe vulnerability class, with higher upstream and downstream EV classes and a certain amount of reduction in the midstream EV classes. Moreover, EV in the DRB continues to decrease. The spatio-temporal EV patterns in the DRB were significantly influenced by the relative humidity, average annual temperature, and vegetation cover over the past 20 years. Our work can provide a basis for decision-making and technical support for ecosystem protection, ecological restoration, and ecological management in the DRB.
Keywords: ecological vulnerability; driving mechanisms; remote sensing; Dongjiang River Basin ecological vulnerability; driving mechanisms; remote sensing; Dongjiang River Basin
Graphical Abstract

Share and Cite

MDPI and ACS Style

Wu, J.; Zhang, Z.; He, Q.; Ma, G. Spatio-Temporal Analysis of Ecological Vulnerability and Driving Factor Analysis in the Dongjiang River Basin, China, in the Recent 20 Years. Remote Sens. 2021, 13, 4636. https://doi.org/10.3390/rs13224636

AMA Style

Wu J, Zhang Z, He Q, Ma G. Spatio-Temporal Analysis of Ecological Vulnerability and Driving Factor Analysis in the Dongjiang River Basin, China, in the Recent 20 Years. Remote Sensing. 2021; 13(22):4636. https://doi.org/10.3390/rs13224636

Chicago/Turabian Style

Wu, Jiao, Zhijun Zhang, Qinjie He, and Guorui Ma. 2021. "Spatio-Temporal Analysis of Ecological Vulnerability and Driving Factor Analysis in the Dongjiang River Basin, China, in the Recent 20 Years" Remote Sensing 13, no. 22: 4636. https://doi.org/10.3390/rs13224636

APA Style

Wu, J., Zhang, Z., He, Q., & Ma, G. (2021). Spatio-Temporal Analysis of Ecological Vulnerability and Driving Factor Analysis in the Dongjiang River Basin, China, in the Recent 20 Years. Remote Sensing, 13(22), 4636. https://doi.org/10.3390/rs13224636

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