Citation

Chen J, Wang Z, Chen W, Wan C, Liu Y, Huang J. Environ. Sci. Pollut. Res. Int. 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s11356-023-25454-2

PMID

36697985

Abstract

The reasonable selection of non-geological disaster samples is of great significance to improve the accuracy of geological disaster assessment, reduce the cost of disaster management, and maintain the sustainable development of ecological environment. Liulin County was selected as the study area. This paper creatively divided non-geological disaster sampling areas by macro-geomorphology, and carried out susceptibility mapping based on random forest (RF) and frequency ratio-random forest (FR-RF) models. The accuracy of each model was evaluated by receiver operating characteristic curve (ROC) combined with the distribution characteristics of geological disasters and the actual urban construction in the study area. The results show that the FR-RF model constructed by selecting non-geological disaster samples in hilly area is most suitable for the susceptibility mapping of this study area. The different results in different sampling areas are mainly due to the great changes in the representativeness of non-geological disaster samples. The distance from the roads is the most important factor affecting the occurrence of disasters in the study area. The statistical results of disaster management cost estimation and gross domestic product (GDP) value show that the disaster management cost of HFR-RF model decreases by 13.45% on average compared with other models, and the ratio of GDP to disaster management cost is relatively high. These research results promote the progress of geological disaster prevention technology, maintain the stability of geological environment, and are of great significance to the stable and sustainable development of local economy.

Language: en

Keywords

Sustainable development; Frequency ratio; Non-geological disaster; Random forest; ROC; Susceptibility