Research on an Ecological Sensitivity Evaluation of Mountain-Type National Parks Under Multi-Modal Optimization: A Case Study of Shennongjia, China

As ecologically sensitive zones within natural ecosystems, national parks demand more precise evaluation models for ecological sensitivity assessment. This study takes Shennongjia Forestry District, a pioneer among China’s first-batch national parks, as an study object to optimize the ecological sensitivity evaluation framework. In this study, we developed an integrated methodology incorporating high-precision ASTER GDEM elevation data, Landsat8 TM vegetation density inversion, SWAT-based flash flood simulation, and SVM-LSM landslide prediction while introducing dynamic protection elements including species migration corridors and human activity risks. The results demonstrate that the refined data structure enhances terrain coupling accuracy by transitioning from “Vegetation Type—Runoff Coefficient” to “Vegetation Density—Runoff Coefficient” conversions, with the optimized model exhibiting superior sensitivity in spatial element identification. This approach provides scientifically grounded technical support for balancing ecological conservation and visitor management in protected areas.