Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (3): 259-374.doi: 10.1007/s11442-018-1471-3

• Research Articles •     Next Articles

Spatial pattern and influencing factors of landslide casualty events

Ying WANG1,2(), Qigen LIN1,2, Peijun SHI1,2   

  1. 1. Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China
    2. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China
  • Received:2017-06-14 Accepted:2017-07-20 Online:2018-03-10 Published:2018-03-10
  • About author:

    Author: Wang Ying, Professor, specialized in disaster risk assessment and post-disaster recovery research. E-mail:

  • Supported by:
    National Key Research and Development Program Project, No.2017YFC1502505, No.2016YFA0602403;National Natural Science Foundation of China, No.41271544


Analysis of casualties due to landslides from 2000 to 2012 revealed that their spatial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area, and Tianshan and Qilian Mountains. However, local distribution patterns indicated that landslide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China (LCEC) was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by landslides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories: poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk.

Key words: landslide, casualty event, spatial pattern, influencing factors, counties, China