A comparative study on the landslide susceptibility mapping using logistic regression and statistical index models
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ORIGINAL PAPER
A comparative study on the landslide susceptibility mapping using logistic regression and statistical index models Zhiyong Wu 1,2 & Yanli Wu 1,3 & Yitian Yang 2 & Fuwei Chen 4 & Na Zhang 2 & Yutian Ke 5 & Wenping Li 1
Received: 18 April 2016 / Accepted: 17 March 2017 # Saudi Society for Geosciences 2017
Abstract The logistic regression and statistical index models are applied and verified for landslide susceptibility mapping in Daguan County, Yunnan Province, China, by means of the geographic information system (GIS). A detailed landslide inventory map was prepared by literatures, aerial photographs, and supported by field works. Fifteen landslide-conditioning factors were considered: slope angle, slope aspect, curvature, plan curvature, profile curvature, altitude, STI, SPI, and TWI were derived from digital elevation model; NDVI was extracted from Landsat ETM7; rainfall was obtained from local rainfall data; distance to faults, distance to roads, and distance to rivers were created from a 1:25,000 scale topographic map; the lithology was extracted from geological map. Using these factors, the landslide susceptibility maps were prepared by LR and SI models. The accuracy of the results was verified by using existing landslide locations. The statistical index model had a predictive rate of 81.02%, which is more accurate prediction in comparison
* Yanli Wu [email protected]
1
School of Resources and Geoscience, China University of Mining and Technology, Xuzhou 221116, China
2
College of Resource and Environmental Sciences, Hebei Normal University for Nationalities, Chengde 067000, China
3
Exploration & Surveying Division, Northwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Xi’an 710075, China
4
Science Research Department, Hebei Normal University for Nationalities, Chengde 067000, China
5
School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China
with logistic regression model (80.29%). The models can be used to land-use planning in the study area. Keywords Landslide . Susceptibility . Logistic regression . Statistical index . China
Introduction In China, the annual loss of lives and property due to natural hazards (e.g., earthquakes and landslides) are significantly high, especially in mountainous regions. In Southwest of China, most of the areas are located in mountainous area, and Daguan County has been recognized as one of the most prone to landslides areas in Yunan province, Southwest of China. In recent years, the occurrence frequency of geological disasters has increased, causing local economic development restricted, which has also caused plenty of casualties and property damage every year. Landslide is considered as one of the most damaging natural disasters that usually occur in mountainous regions (Yalcin et al. 2011). In order to decrease the possible damage caused by landslides, the present study aimed to assess or predict landslides for mountainous regions and Daguan County was selected as a suitable ca
