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• Simulate future land use under various scenarios. • Analyze urban expansion, Ecological Security Patterns, and ecological health dynamics. • Integrate the dynamic ESP and EH to optimize the current ecological security configuration. Urbanisation affects the health and stability of ecosystem significantly. Constructing a scientific ecological security pattern (ESP) is of paramount importance for safeguarding the health of ecosystems within a region, optimising ecological spaces, and ensuring sustainability. To investigate the effect of urbanisation on the ESP, we utilised the Vigour–Organisation–Resilience-Services (VORS) model to analyse the changes in ecosystem health (EH) and identify degraded areas in the city of Chengdu. In this case study. We used the Patch-generating Land Use Simulation (PLUS) Model to predict the urban expansion trends in 2035 and evaluate the changing ESP. Additionally, we used the minimum cumulative resistance (MCR) model and circuit theory to construct an ecological network to facilitate multilayer planning of ESP. We identified an ecological source area of approximately 4484.29 km2 and a recovery zone of 1608.35 km2 for managing EH degradation within the ecological source. An ecological conservation zone of 987.48 km2 with restricted development outside the ecological source, and a restoration zone of 71.66 km2 to mitigate the impact of urban expansion on ecological security were also identified. Seven stable corridors with consistent spatial patterns and pressure levels and six potential corridors await restoration. Based on the analysis of changes in ecosystem health and dynamic ESPs, different scenarios were simulated for 2035. The findings suggested significant variations in EH and ESP around 2010 despite rapid expansion in Chengdu. The ecological environment was partially restored by increasing the land area and controlling its contraction. Therefore, scientific planning of ESPs, limiting the boundaries of urban expansion, and accurately assessing the health of ecosystems are crucial for ensuring ecological security. [ABSTRACT FROM AUTHOR]

• The study area is typical, and has instructive and significant. • Compared with RSEI, the useful data of IRSEI for analysis increased by 3.26%. • We use GDP sub-industry spatialization model to represent the urbanization process. • Our study is important to know how urbanization affects the environment. 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. [ABSTRACT FROM AUTHOR]