Application of information value model based on symmetrical factors classification method in landslide hazard assessment
LING Xiao1(), LIU Jiamei2,3(), WANG Tao2,3, ZHU Yueqin4, YUAN Lingling4, CHEN Yangyang1
1. School of Information Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, China 2. Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing, 100081, China 3. Key Laboratory of Neotectonics Movement and Geohazard, Beijing, 100081, China 4. Development and Research Center, China Geological Survey, Beijing, 100037, China
The information value model (IVM) is a statistical prediction method derived from information theory, which is widely used in natural hazard risk assessment. The problem as to how to formulate a suitable factor classification method to maximize the advantages of pre- single factor statistical analysis remains a key issue. In order to solve this problem, the authors processed a method of factor classification by combining symmetrical intervals. Statistical knowledge related to normal distribution was referred, the factors was pre-segmented by 1/2 standard deviation, and the intervals were merged symmetrically from outside to inside. After that, factors approximately fitting normal distribution, such as slope angel and topographic wetness index (TWI), were classified based on this method, and IVM was built, which was later used in landslide hazard susceptibility analysis in Wenchuan area. Meanwhile, 5 standard classification methods were selected and tested as comparative experiments for rationality verification, namely equal quantile (EQ) classification method, natural break (NB) classification method, geometric break (GB) classification method and standard deviation (SD) classification method. The results show that the IVM using symmetrical method as factor classification method stands out among the rests. The actual landslide area ratio in the high and extremely high-risk areas in the susceptibility map reached 80.87%, higher than that obtained by other standard classification methods. This proves that the symmetrical classification method performs well.
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LING Xiao, LIU Jiamei, WANG Tao, ZHU Yueqin, YUAN Lingling, CHEN Yangyang. Application of information value model based on symmetrical factors classification method in landslide hazard assessment. Remote Sensing for Land & Resources, 2021, 33(2): 172-181.
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2021, Vol. 33 
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