混沌序列 犠犃  犞犗犔犜 犈犚犚犃耦合 模型在月降水量预测中的应用

黄, 发明

doi:10.3799/dqkx.2014.035

Eart. Scie.

2014

DOI: 10.3799/dqkx.2014.035

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混沌序列犠犃  犞犗犔犜犈犚犚犃耦合模型在月降水量预测中的应用

发明黄¹

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Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

Huang

Zhou

et al. 2020

IOP Conf. Ser.: Earth Environ. Sci.

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The landslide susceptibility prediction (LSP) is generally implemented using certain types of single models; however, certain drawbacks exist in the single models; e.g., it is difficult to clearly reflect the weights of landslide-related environmental factors if only the information value (IV) model is adopted. To overcome these limitations, this study proposes an IV-logistic regression (IV-LR) model for LSP. The landslides that occurred in the southern part of Chongyi County, China, are used as study cases. Nine environmental factors—elevation, slope, plane curvature, profile curvature, relief amplitude, distance to river, lithology, normalized difference vegetable index, and normalized difference built-up index—are adopted based on remote sensing and geographic information system. Certain landslide grid units and the same number of non-landslide grid units are used as the output variables of these models. The IV, LR, and IV-LR models are used to implement the LSP in the southern part of Chongyi County. The predicted landslides susceptibility in Chongyi County mostly occurred in areas with low elevations, close distance to rivers, carbonate lithology, low vegetation coverage rate, and densely populated areas. The results show that the prediction rate of the IV-LR model (80.4%) is higher than that of the LR model (76.8%), followed by the IV model (72.8%); they further demonstrate that the IV-LR model has its unique superiority and rationality compared with the IV and LR models.

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Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

Huang

Zhou

et al. 2020

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

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混沌序列犠犃  犞犗犔犜犈犚犚犃耦合模型在月降水量预测中的应用

Cited by 1 publication

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Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

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混沌序列 犠犃  犞犗犔犜 犈犚犚犃耦合 模型在月降水量预测中的应用

Cited by 1 publication

References 0 publications

Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

Contact Info

Product

Resources

About

混沌序列犠犃  犞犗犔犜犈犚犚犃耦合模型在月降水量预测中的应用