In view of the uncertainty of landslide disasters affected areas in mountain cities, the typical landslides in the central urban area of Chongqing are selected as the research objects. and the spatial distribution characteristics of historical landslide disaster points are analyzed using the nearest neighbor index, spatial hotspot detection and kernel density estimation methods; A landslide factor database was established with 12 influencing factors includes elevation, slope, aspect, landform type, geological lithology, soil type, soil erosion, rainfall, water system, land use, Normalized Difference Vegetation Index (NDVI), and population density. A neural network model was used to quantitatively analyze the contribution weight of each influencing factor, and the model was accurate using Receiver Operating Characteristic (ROC) curve assessment. The research results show that the historical landslide disaster points in the study area are clustered, and Yuzhong District, Shapingba District, and northern Banan District are the areas where the landslides are most concentrated. Among all the factors, population density, land use and rainfall occupy the highest weight, while the aspect and road are the lowest. The area value under the ROC curve (AUC) was 0.917, indicating that the model can accurately reflect the impact of landslide impact factors in the area.