Spatiotemporal Distribution of Nonseismic Landslides during the Last 22 Years in Shaanxi Province, China

Haijun Qiu, Yifei Cui, Dongdong Yang, Yanqian Pei, Sheng Hu, Shuyue Ma, Junqing Hao, Zijing Liu
2019 ISPRS International Journal of Geo-Information  
The spatiotemporal distribution of landslides provides valuable insight for the understanding of disastrous processes and landslide risk assessment. In this work, we compiled a catalog of landslides from 1996 to 2017 based on existing records, yearbooks, archives, and fieldwork in Shaanxi Province, China. The statistical analyses demonstrated that the cumulative frequency distribution of the annual landslide number was empirically described by a power-law regression. Most landslides occurred
more » ... dslides occurred from July to October. The relationship between landslide time interval and their cumulative frequency could be fitted using an exponential regression. The cumulative frequency of the landslide number could be approximated using the power-law function. Moreover, many landslides caused fatalities, and the number of fatalities was related to the number of landslides each month. Moreover, the cumulative frequency was significantly correlated with the number of fatalities and exhibited a power-law relationship. Furthermore, obvious differences were observed in the type and density of landslides between the Loess Plateau and the Qinba Mountains. Most landslides were close to stream channels and faults, and were concentrated in cropland at elevations from 600–900 m and on slope gradients from 30–40°. In addition, the landslide frequency increased as the annual rainfall levels increased over a large spatial scale, and the monthly distribution of landslides presented a significant association with the precipitation level. This study provides a powerful method for understanding the spatiotemporal distribution of landslides via a rare landslide catalog, which is important for engineering design and planning and risk management.
doi:10.3390/ijgi8110505 fatcat:tjpr7kswnne67ikzq6fkcjyk3y