Linking the Random Forests Model and GIS to Assess Geo-Hazards Risk: A Case Study in Shifang County, China

Abstract

This study proposes an objective and accurate geo-hazards risk assessment method to address the challenge of increasingly severe hazards around the world. Previous studies mostly began from the perspectives of hazard and vulnerability, ignoring the role of survey data at disaster sites during risk assessments. The random forests (RF) model was applied in this study. Combined with detailed data from hazard sites, a geo-hazards risk assessment model was constructed, with the two dimensions of disaster hazard and vulnerability, was constructed. We analyzed the spatial pattern characteristics and the internal patterns of disaster risk and discussed the risk controlling factors and their contributions. The results showed the following. (1) The RF model, when combined with hazard, vulnerability conditions, and detailed data from disaster sites, can be used to zone and verify regional geo-hazards risks, providing a method for point-to-surface disaster risk mapping. (2) The RF-based geo-hazards risk assessment results were relatively consistent with the evaluation results from the support vector machine (SVM) model, but the accuracy and stability of the RF model were higher. (3) This method can be used to avoid the subjectivity in determining the weights and threshold values for indexes and can calculate the contribution of each index to geo-hazards risks.

Keywords

• Geo-hazards
• random forests model
• risk assessment
• Shifang county
• support vector machine model