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Geoscience ›› 2018, Vol. 32 ›› Issue (03): 602-610.DOI: 10.19657/j.geoscience.1000-8527.2018.03.18

• Hydrogeology and Environmental Geology • Previous Articles     Next Articles

Comparative Study of Geological Hazards Susceptibility Assessment: Constraints from the Information Value+Logistic Regression Model and the CF+Logistic Regression Model

ZHANG Xiaodong1,2(), LIU Xiangnan1(), ZHAO Zhipeng2, WU Wenzhong2, LIU Haiyan2, ZHANG Yong2, GAO Yuliang3   

  1. 1. School of Information Engineering, China University of Geosciences, Beijing 100083, China
    2. Ningxia Geological Survey Institute,Yinchuan, Ningxia 750021, China
    3. College of Earth Science and Engineering,Shandong University of Science and Technology,Qingdao, Shandong 266590, China
  • Received:2017-08-06 Revised:2018-04-20 Online:2018-06-10 Published:2023-09-22
  • Contact: LIU Xiangnan

Abstract:

Susceptibility assessment constitutes an important part of geological hazard research. This paper discussed two integrated approaches, namely the Information Value+Logistic Regression model (I+LR) and CF+Logistic Regression model (CF+LR), to evaluate the geological hazard susceptibility of Yanchi County, Ningxia Hui Autonomous Region. 462 samples (231 hazardous samples and 231 non-hazardous samples) were divided into two groups: 75% and 25% of the samples were used for model training and validation, respectively. Nine influencing factors, including slope dip angle and direction, slope height, elevation, strata, distance to rivers and roads, and the normalized difference vegetation index (NDVI) were considered in this evaluation. Based on such information, the information value and CF of the training samples were calculated, which were then fed into the SPSS for analysis via logistic regression. After collinearity diagnostics and correlation analysis, six factors were incorporated into the model eventually. Regression equation was determined using the obtained constants and coefficients, and the Receiver Operating Characteristic (ROC) curve was used to assess the accuracy of the two models. The results show that: (1)Susceptibility maps reveal four susceptibility classes, i.e., very low, low, moderate and high. The area percentage of the (I+LR) model for the four class accounts for 60.79%, 23.44%, 11.34% and 4.43%, respectively, with that of the (CF+LR) model being 54.49%, 22.89%, 10.30% and 12.32%. This indicates that the areas of the low and moderate classes are basically the same. The high-class area of the (CF+LR) model has increased for 533.6 km2 more than the (I+LR) model, but the very low-class area has dropped by as much as 6%. (2) The area under the curve for the successful rates are 0.868 and 0.829, respectively, and asymptotic Sig.b is lower than 0.05 for the two models. Both integrated approaches can produce reasonable accuracy. (3) The ROC accuracy and the geological hazard development conditions at Yanchi both indicate that the (I+LR) model has higher accuracy over the (CF+LR) model.

Key words: geological hazard, susceptibility, CF model, logistic regression model, Yanchi of Ningxia

CLC Number: