Landslides of China's Qinling

Liye Feng,Chong Xu, Yingying Tian,Lei Li, Jingjing Sun, Yuandong Huang, Peng Wang, Xuewei Zhang, Tao Li,Wentao Yang, Siyuan Ma,Xiaoyi Shao, Jixiang Xu, Jingyu Chen

GEOSCIENCE DATA JOURNAL(2024)

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摘要
The Qinling Mountains in China frequently experience geological disasters, with large-scale landslides being particularly prominent, causing severe economic losses to the local area. To gain a comprehensive understanding of the geological disaters distribution in the region, we conducted extensive research on the entire Qinling Mountains, covering an area of approximately 380,000 km2. By employing methods such as literature review, data collection, and interpretation of remote sensing images, we have successfully created a database of landslides. The inventory of landslides includes a total of 169,888 large-scale landslides, covering a combined area of approximately 1575 km2. The average size of these landslides is approximately 92,734 m2. The scale of these landslides varies widely, with the smallest individual landslide covering an area of 166.25 m2 and the largest reaching 12.9 km2. Upon examining areas with frequent landslides, it was observed that landslides are usually densely distributed along riverbanks or within valleys. Landslide development is also dense in areas prone to frequent historical earthquakes. This comprehensive database provides essential data to support the analysis of spatial distribution patterns of large-scale landslides in the Qinling Mountains. It also facilitates landslide assessments and serves as a reference for the prevention and control of landslide disasters in the area. The inventory of landslides includes a total of 169,888 large-scale landslides, covering a combined area of approximately 1575 km2. The average size of these landslides is approximately 92,734 m2. The scale of these landslides varies widely, with the smallest individual landslide covering an area of 166.25 m2 and the largest reaching 12.9 km2.image
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landslide inventory,Qinling Mountains,visual interpretation
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