Application of information value model based on symmetrical factors classification method in landslide hazard assessment

doi:10.6046/gtzyyg.2020203

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Abstract

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.

Keywords information value model (IVM) landslide triggered by earthquake landslide susceptibility analysis factor classification methods symmetrical classification method

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Corresponding Authors: LIU Jiamei E-mail: LinGX0527@163.com;ljm19870918@126.com

Issue Date: 21 July 2021

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	Xiao LING
	Jiamei LIU
	Tao WANG
	Yueqin ZHU
	Lingling YUAN
	Yangyang CHEN

Cite this article:

Xiao LING,Jiamei LIU,Tao WANG, et al. Application of information value model based on symmetrical factors classification method in landslide hazard assessment[J]. Remote Sensing for Land & Resources, 2021, 33(2): 172-181.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020203 OR https://www.gtzyyg.com/EN/Y2021/V33/I2/172

Fig.1 Workflow of landslide hazardness analysis in Wenchuan area using information value model

Fig.2 Schematic diagram of the symmetrical classification method (e.g. standard normal distribution)

Fig.3 Original geographical data of study area in Wenchuan

Tab.1 Selection principles and original data resources of hazardness factors

Fig.4 Statistical analysis results between landslide and slope angle

Fig.5 Statistical analysis results between landslide and aspect

Fig.6 Statistical analysis results between landslide and height

Fig.7 Statistical analysis results between landslide and distance to fault

Fig.8 Statistical analysis results between landslide and curvature, curvature ranges from -0.05 to 0.05

Tab.2 Classification result of lithology and examples matching each group

Fig.9 Statistical analysis results between landslide and lithology

Fig.10 Statistical analysis results between landslide and distance to river

Fig.11 Statistical analysis results between landslide and topographic wetness index

Fig.12 Statistical analysis results between landslide and intensity

Fig.13-1 Different classification results of topographic wetness index using 6 factor classification methods

Fig.13-2 Different classification results of topographic wetness index using 6 factor classification methods

Fig.14-1 Different results of Wenchuan landslide hazard map based on 6 factor classification methods

Fig.14-2 Different results of Wenchuan landslide hazard map based on 6 factor classification methods

Tab.3 Comparison of the proportion of actual landslide area in high-risk and extremely high-risk areas(%)

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