Abstract: The extreme rainstorm in July 2023 triggered widespread debris flows on both sides of Jiulong Mountain in Mentougou District, Beijing, causing severe losses. Accurate identification of post-rainstorm debris and analysis of their formation mechanisms are urgently needed to support post-disaster reconstruction and hazard prevention in the area. Taking the areas on both sides of Jiulong Mountain as the study area, 12.5 m resolution ALOS PALSAR DEM data and 0.3 m resolution Maxar WorldView pre- and post-rainstorm imagery were used. River network vectors were extracted via ArcGIS, and the Visible Atmospherically Resistant Index (VARI) was applied to detect vegetation changes. Manual visual interpretation was supplemented to identify debris flow gullies. Topographic parameters of gullies were extracted, and regional geological data were integrated to analyze debris flow controlling factors. A total of 8 debris flow gullies were identified, with catchment areas of 1.20 to 5.54 km², main channel lengths of 1646.8 to 3838.0 m, and average longitudinal gradients of 204.3‰ to 339.9‰. The distribution of debris flows is controlled by the Jiulong Mountain compound syncline and the northern fault zone. The Yaopo Formation coal-bearing strata and coal mining waste provide abyndant loose materials. Post-rainstorm vegetation cover decreased significantly, with exposed soil and rock widely distributed. Combining high-resolution DEM-derived gully boundaries with VARI change maps derived from high-resolution images before and after the rainstorm improves the efficiency and accuracy of debris flow gully identification. The overall accuracy and precision reach 80%, with a recall rate is 100%. This method reduces misjudgments from DEM-only river network extraction and has strong application value.