Spatiotemporal Distribution of Nonseismic Landslides during the Last 22 Years in Shaanxi Province, China
by
Haijun Qiu 1,2,3,*
, Yifei Cui 4, Dongdong Yang 3, Yanqian Pei 3, Sheng Hu 3, Shuyue Ma 3, Junqing Hao 5 and Zijing Liu 3
Haijun Qiu 1,2,3,*, Yifei Cui 4, Dongdong Yang 3, Yanqian Pei 3, Sheng Hu 3, Shuyue Ma 3, Junqing Hao 5 and Zijing Liu 3
1
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an 710127, China
2
Institute of Earth Surface System and Hazards, Northwest University, Xi’an 710127, China
3
College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
4
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
5
School of Business, Xi’an University of Finance and Economics, Xi’an 710061, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(11), 505; https://doi.org/10.3390/ijgi8110505
Received: 10 September 2019 / Revised: 25 October 2019 / Accepted: 6 November 2019 / Published: 9 November 2019
(This article belongs to the Special Issue Geospatial Approaches to Landslide Mapping and Monitoring)
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 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.
View Full-Text
Keywords:
landslides; hazard; time series; temporal distributions; Shaanxi Province
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Qiu, H.; Cui, Y.; Yang, D.; Pei, Y.; Hu, S.; Ma, S.; Hao, J.; Liu, Z. Spatiotemporal Distribution of Nonseismic Landslides during the Last 22 Years in Shaanxi Province, China. ISPRS Int. J. Geo-Inf. 2019, 8, 505.
Show more citation formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
