The strategic delineation of ecological corridors and establishment of robust ecological security frameworks constitute fundamental prerequisites for advancing ecologically balanced growth and premium development within the Pinglu Canal Economic Belt. In this study, a comprehensive framework integrating ecological sources, resistance surfaces, and ecological corridors was developed using the InVEST model combined with circuit theory. The framework was then applied to assess the spatial and temporal dynamics of four major ecosystem services over the period from 2000 to 2020. The main findings are as follows: (1) From 2000 to 2020, the values of the four ecosystem services showed an overall declining trend. Spatially, areas with high ecosystem service importance were mainly concentrated in woodland and grassland areas in the southwest and northwest of the region. (2) The resistance values of the study area’s resistance surface ranged from 1 to 4.83. High-resistance areas were primarily located in the central region, corresponding to areas of intense human activity, while low-resistance areas were distributed around the periphery and largely overlapped with ecological source areas, presenting a spatial pattern of “high in the center, low at the edges”. (3) In total, 119 ecological barriers, 28 corridors, 8 critical pinch points, and 16 habitat source areas were identified. Building on these results, an enhanced ecological security layout—defined by the ‘three belts and three zones’ strategy—was formulated to guide restoration efforts and inform ecological management across the Pinglu Canal Economic Region.

This study investigates the spatio-temporal characteristics and driving mechanisms of ecological quality in the mountain–river–sea regional system using the Remote Sensing Ecological Index (RSEI) model, moderate-resolution imaging spectroradiometer (MODIS) data, and the Google Earth Engine (GEE) platform. The analysis, conducted at both the grid and county scales using spatial autocorrelation and geodetector, showed a notable improvement in ecological quality, with the average RSEI value rising from 0.549 in 2000 to 0.627 in 2022. The distribution pattern reveals superior quality in the northwest and inferior quality in central urban cores and coastal zones. Ecological quality exhibited significant spatial clustering, with high–high clusters in karst mountains and low–low clusters in urban and industrial zones. Geodetector analysis identified GDP and population density as dominant factors at the grid scale, and GDP and elevation at the county scale. By quantifying spatio-temporal variations and driving mechanisms of ecological quality across scales, this study provides a solid scientific foundation for regional ecological conservation and sustainable development.