Citation

Ma S, Xu C, Shao X. Int. J. Disaster Risk Reduct. 2020; 43: e101362.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2019.101362

PMID

unavailable

Abstract

To enhance the timeliness and accuracy of spatial prediction of co-seismic landslides, this paper proposes a prediction strategy in three phases: emergency response, mid-term resettlement and later reconstruction in the affected area. Taking the Lushan Ms 7.0 earthquake of 2013 as an example, it is stated as follows: In the emergency response phase, combining with topographic and geological data of the study area, the rapid assessment is conducted by the Newmark method without co-seismic landslide data. In the temporary resettlement phase with partial landslide data available, considering 10 factors including elevation, slope gradient, slope direction, topographic wetness index (TWI), peak ground acceleration (PGA), distances to the epicenter, distances to rivers, distances to roads, lithology and annual precipitation, a logistic regression (LR) model is established, and the spatial prediction of landslides is made. In the reconstruction phase with a complete landslide inventory, the incomplete data is replaced and the latest assessment is conducted based on the LR model. The accuracies of three phases are tested by using complete landslide data. The results show that the area under curve (AUC) values of the three stages is 0.59, 0.84 and 0.87, respectively. Such results can meet the requirement of spatial prediction of seismic landslides in each stage of disaster reduction.

Language: en

Keywords

Co-seismic landslide; Logistic regression (LR) model; Lushan earthquake; Newmark model