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Remote Sensing
Volume 14
Issue 19
10.3390/rs14194900
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Article

Analysis of Spatiotemporal Variation and Drivers of Ecological Quality in Fuzhou Based on RSEI

by
Jianwei Geng
1,2,
Kunyong Yu
2,3,
Zhen Xie
1,2,
Gejin Zhao
2,3,
Jingwen Ai
1,2,
Liuqing Yang
1,2,
Honghui Yang
1 and
Jian Liu
1,2,3,*
1
College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou 350000, China
2
University Key Lab for Geomatics Technology and Optimize Resource Utilization in Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350000, China
3
College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2022, 14(19), 4900; https://doi.org/10.3390/rs14194900
Submission received: 18 August 2022 / Revised: 20 September 2022 / Accepted: 28 September 2022 / Published: 30 September 2022
(This article belongs to the Special Issue Application of Satellite Remote Sensing in Solving Urban Geo-Environmental Issues)
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Abstract

Background: High-speed urbanization has brought about a number of ecological and environmental problems, as well as the use of remote sensing to monitor the urban ecological environment and explore the main factors affecting its changes. It is important to promote the sustainable development of cities. Methods: In this study, we quantify the ecological quality of the study area from 2000 to 2020 based on the remote sensing ecological index (RSEI) and analyze its drivers through Geodetector and geographically weighted regression. Results: The RSEI of Fuzhou City from 2000 to 2020 showed an increasing followed by a decreasing trend, with obvious spatial autocorrelation. The main driving factors causing the spatial divergence of the RSEI were elevation (q = 0.48–0.63), slope (0.42–0.59), and GDP (0.3–0.42), and the driving effect and range of each factor changed with time. Conclusion: In this paper, we explore changes in the ecological environment in Fuzhou City over the past 20 years, as well as the scope and magnitude of the drivers, providing an important reference basis to improve the ecological environment quality of the city.
Keywords: remote sensing ecological indices; spatial autocorrelation; driving force analysis; Fuzhou City remote sensing ecological indices; spatial autocorrelation; driving force analysis; Fuzhou City

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MDPI and ACS Style

Geng, J.; Yu, K.; Xie, Z.; Zhao, G.; Ai, J.; Yang, L.; Yang, H.; Liu, J. Analysis of Spatiotemporal Variation and Drivers of Ecological Quality in Fuzhou Based on RSEI. Remote Sens. 2022, 14, 4900. https://doi.org/10.3390/rs14194900

AMA Style

Geng J, Yu K, Xie Z, Zhao G, Ai J, Yang L, Yang H, Liu J. Analysis of Spatiotemporal Variation and Drivers of Ecological Quality in Fuzhou Based on RSEI. Remote Sensing. 2022; 14(19):4900. https://doi.org/10.3390/rs14194900

Chicago/Turabian Style

Geng, Jianwei, Kunyong Yu, Zhen Xie, Gejin Zhao, Jingwen Ai, Liuqing Yang, Honghui Yang, and Jian Liu. 2022. "Analysis of Spatiotemporal Variation and Drivers of Ecological Quality in Fuzhou Based on RSEI" Remote Sensing 14, no. 19: 4900. https://doi.org/10.3390/rs14194900

APA Style

Geng, J., Yu, K., Xie, Z., Zhao, G., Ai, J., Yang, L., Yang, H., & Liu, J. (2022). Analysis of Spatiotemporal Variation and Drivers of Ecological Quality in Fuzhou Based on RSEI. Remote Sensing, 14(19), 4900. https://doi.org/10.3390/rs14194900

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