Spatial assessment of ecological sensitivity for sustainable planning in Lijiang city using GIS and AHP

Introduction In response to the increasingly prominent problem of ecological environmental vulnerability. Method This study comprehensively applies the Geographic Information System combined with Analytic Hierarchy Process to objectively quantify and comprehensively assess the ecological sensitivity of Lijiang City, Yunnan Province, in southwestern China. Six key evaluation indicators will be selected: elevation, slope, slope orientation, water buffer zones, fractional vegetation cover, and land use. The weights of these factors are determined through expert evaluation, and a sensitivity distribution map is generated using weighted overlay technology. This achieves a multidimensional quantitative assessment and spatial visualization of ecological sensitivity across the entire region of Lijiang City. Result The results indicate that ecologically sensitive regions in Lijiang City display significant spatial heterogeneity, with areas classified as extremely and highly sensitivity comprising 49.91% of the total area. Method Based on the assessment results, the study uses the Global and Anselin Local Moran’s I, and Getis-Ord General G to conduct spatial autocorrelation and hotspot analysis of the comprehensive Ecological Sensitivity Index. The two datas show high consistency, revealing a complex spatial pattern of ecological sensitivity in Lijiang City, characterized by large clusters and small anomalies. Furthermore, sensitivity analysis is incorporated to demonstrate the robustness of the results. Result and discussion Finally, the study proposes recommendations for the delineation of ecological protection redlines and zoning control strategies, providing a scientific basis for the sustainable development of the Lijiang World Heritage Site. It also establishes a technical framework for ecological sensitivity assessment applicable to plateau and mountainous areas, which is valuable for building ecological security patterns in similar regions.