In this study, we used high-resolution optical satellite images on the Google Earth platform to map large-scale landslides in Xianyang City, Shaanxi Province, China. After mapping, a comprehensive and detailed large-s...In this study, we used high-resolution optical satellite images on the Google Earth platform to map large-scale landslides in Xianyang City, Shaanxi Province, China. After mapping, a comprehensive and detailed large-scale landslide inventory that contains 2 924 large-scale landslides was obtained. We analyzed the spatial distribu-tion of landslides with seven influencing factors, including elevation, slope angle, aspect, curvature, lithology, distance to a river, and distance to the fault. Landslide Number, Landslide Area, Landslide Number Density(LND), and Landslide Area Percentage(LAP) were selected as indexes for the spatial distribution analysis. The results show that the number and area of landslides in the elevation range of 1 000–1 200 m is the highest. The highest number of landslides was observed in the slope angle of 25°–30°. North-facing slopes are prone to sliding. The area and number of landslides are the largest when the slope curvature ranges from-1.28 to 0. The LND and LAP reach their maxima when the slope curvature is less than-2.56. Areas covered by the Tertiary stratum with weakened fine-grained sandstone and siltstone show the highest LND and LAP values. Regarding distance to a river, the LAP peaks in the range of 300–600 m, whereas the LND peaks in an area larger than 2100 m. The values of LND and LNP rise as the distance from the faults increases, except for the locations 30 km away from active faults. This phenomenon is because active faults in this area pass through the plain areas, while landslides mostly occur in mountainous areas. The cataloging of landslide development in Xianyang City provides a significant scientific foundation for future research on landslides. In addition, the spatial distribution results are useful for landslide hazard prevention decisions and provide valuable references in this area.展开更多
基金This study was supported by the National Institute of Natural Hazards,Ministry of Emergency Management of China(ZDJ 2021-12)the National Key Research and Development Program of China(2021YFB3901205).
文摘In this study, we used high-resolution optical satellite images on the Google Earth platform to map large-scale landslides in Xianyang City, Shaanxi Province, China. After mapping, a comprehensive and detailed large-scale landslide inventory that contains 2 924 large-scale landslides was obtained. We analyzed the spatial distribu-tion of landslides with seven influencing factors, including elevation, slope angle, aspect, curvature, lithology, distance to a river, and distance to the fault. Landslide Number, Landslide Area, Landslide Number Density(LND), and Landslide Area Percentage(LAP) were selected as indexes for the spatial distribution analysis. The results show that the number and area of landslides in the elevation range of 1 000–1 200 m is the highest. The highest number of landslides was observed in the slope angle of 25°–30°. North-facing slopes are prone to sliding. The area and number of landslides are the largest when the slope curvature ranges from-1.28 to 0. The LND and LAP reach their maxima when the slope curvature is less than-2.56. Areas covered by the Tertiary stratum with weakened fine-grained sandstone and siltstone show the highest LND and LAP values. Regarding distance to a river, the LAP peaks in the range of 300–600 m, whereas the LND peaks in an area larger than 2100 m. The values of LND and LNP rise as the distance from the faults increases, except for the locations 30 km away from active faults. This phenomenon is because active faults in this area pass through the plain areas, while landslides mostly occur in mountainous areas. The cataloging of landslide development in Xianyang City provides a significant scientific foundation for future research on landslides. In addition, the spatial distribution results are useful for landslide hazard prevention decisions and provide valuable references in this area.
