Coupling coordination analysis of urbanization and eco-environment in Yanqi Basin based on multi-source remote sensing data
While multi-source remote sensing technology has the advantage of accurate and objective quantification, an understanding of the coupling and coordination between regional urbanization and ecological environment is the basis for achieving regional sustainable development. This paper builds the Remote Sensing Ecological Index (RSEI) based on Landsat data and Tiangong-2 WIS, using multi-source remote sensing data to comprehensively evaluate the coupling and coordination relationship between urbanization and ecological environment with a coupling coordination degree model in China's typical arid area of Yanqin Basin during 2000–2018. The results show the RSEI index has a certain rationality and superiority in assessing the ecological environment. In 2000–2018, the ecological environment of the Yanqi Basin was optimized, the RSEI index increased by 23.06%, and the overall ecological environment was at a good level (0.6–0.8). At the same time, the urbanization level of each town had been significantly improved in Yanqi Basin. Through the urban center of gravity transfer model, it was found that direction of urban development shifted to the southwest direction by 7.49 km, which is basically consistent with the position of poor ecological environment. Finally the current urbanization and ecological environment coupling relationship in urban areas of Yanqi Basin was found to exhibit a sluggish rate of urbanization with a moderate imbalance between urbanization with ecological environment. Therefore, when making decisions for planning the regional economic development, the concept of ecological relationships should be integrated to effectively protect and achieve a healthy and sustainable development of the region.
Ariken, M., Zhang, F., Liu, K., Fang, C., & Kung, H. (2020). Coupling coordination analysis of urbanization and eco-environment in Yanqi Basin based on multi-source remote sensing data. Ecological Indicators, 114 https://doi.org/10.1016/j.ecolind.2020.106331