Coupling coordination analysis of urbanization and ecological environment in Chengdu-Chongqing urban agglomeration

As the fourth pole of China's economic growth, the Chengdu-Chongqing urban agglomeration plays a significant role in reinforcing the ecological barrier in the upper reaches of the Yangtze River, and is crucial for ecological and environmental protection strategies. In this paper, Google Earth Engine (GEE) and the MODIS images from 2000, 2005, 2010, 2015, and 2022 were utilized to construct the Improved Remote Sensing Ecological Index (IRSEI) to characterize the ecological quality more accurately than RSEI. Additionally, combined with nighttime light remote sensing data, land use data and socio-economic data, the GDP sub-industry spatialization model was utilized to analyze the urbanization process in depth. To dynamically monitor and evaluate the interaction between urbanization and ecological environment quality, a coupling coordination model incorporating the above methods was developed. The results show that (1) The effective information of the IRSEI in ecological quality analysis increased by 3.26% compared to RSEI, and the correlation with each ecological index was higher; (2) The ecological environment quality of the Chengdu-Chongqing urban agglomeration peaked in 2005 and has been declining since then, with the rate of decline gradually slowing down from 2005 to 2022; (3) The GDP sub-industry spatialization model is more suitable for characterizing the scattered villages, and can effectively exhibit the urbanization process. From 2000 to 2022, urbanization was rapidly developed, and the level of core cities such as Chengdu and Chongqing far exceeded those of neighboring cities; (4) The coupling coordination level between IRSEI and GDP spatialization model generally increased, indicating ongoing improvements in the synergy between ecological environment and urbanization in the Chengdu-Chongqing urban agglomeration. This study developed a method for quickly monitoring and assessing the relationship between ecological environment quality and urbanization by using IRSEI and GDP sub-industry spatialization model, and provides scientific analytical methods and data support for monitoring and governing the ecological environment in emerging urban agglomerations.