Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China

Abstract

The Lushan earthquake with magnitude M s 7.0 (M w 6.6, USGS) in Sichuan Province, China, triggered a large number of landslides, which seriously aggravated the earthquake's destructive consequences. This paper mainly focuses on the methodology of the urgent landslide susceptibility assessment right after the earthquake. The detailed landslide inventory (including 5,688 landslides) is prepared by means of urgent postearthquake landslide field survey, landslide remote sensing interpretation of multi-source remote sensing images including high-resolution unmanned aerial vehicle images and historical landslide archives. Ten remarkable causative factors for landslide occurrence have been selected to conduct the landslide susceptibility assessment, including earthquake intensity, landslide density and slope gradient. An integration assessment approach is developed to facilitate the effective urgent post-earthquake landslide susceptibility assessment using three methods: factor sensitivity analysis, analytical hierarchy process and factor-weighted overlay. Such integration can effectively reduce the subjectivity and uncertainty resulting from using single method. The validation evaluation using the area under curve suggests the landslide susceptibility assessment results have satisfactory accuracy, and the suggested methodology is effective for the urgent post-earthquake landslide susceptibility assessment. The study results reveal that earthquake intensity and slope gradient are the two most important causative factors for post-earthquake landslide occurrence in the Lushan earthquake-impacted area. The dominant slope gradient and slope aspect with relatively higher landslide frequency are 45°-50°and south-east direction, respectively. The intense earthquake impact increased the dominant slope gradient of 123Nat Hazards (2015) 75:2467-2487 DOI 10.1007/s11069-014-1441 landslide spatial distribution, and the thrust campaign of seismogenic fault with strike NE-SW made south-east direction as the dominant slope aspect of the landslide spatial distribution. The locations with very high and high landslide susceptibility are mainly distributed in the regions with higher earthquake intensity and adverse terrain conditions, such as Shuangshi town and Longmen town of Lushan county and Muping town of Baoxing county. The study results are expected to provide a beneficial reference for the landslide prevention and infrastructure reconstruction after the Lushan earthquake.

Prediction of highway blockage caused by earthquake-induced landslides for improving earthquake emergency response

“…This indicates the likelihood of a landslide occurring at a particular cell under specific background conditions, that is, the ELS. Through correlation analysis between each of the factors and the ELD, it was found that the intensity and the slope gradient are significantly correlated to the ELD and are the main factors affecting the ELS; this is consistent with the research results of (Yang et al 2015) on landslide susceptibility in the 2013 Ms 7.0 Lushan earthquake. The correlation between the rock and soil status factor and the ELD varied depending on the range of the slope gradient.…”

Effect of the Slope Angle and Its Classification on Landslide

“…In their study, Tanoli et al (2017) determined that 76% of landslides before earthquakes occurred at a slope angle between 20 and 50°, while 78% of landslides after earthquakes occurred at a slope angle between 30 and 80°. Yang et al (2015) reported that the pressure slope for the slides caused by the Lushan earthquake was greater than that of the landslides triggered with precipitation before the earthquake.…”

Morphological parameters causing landslides: a case study of elevation

“…Fault: Elevation does not directly contribute to the formation of a landslide but can cause landslides with other parameters like tectonic, and this affects the entire system (Zolotarev, 1976;Koukis and Ziourkas, 1991; Nagarajan et al, 2000;Görüm, 2006;Rozos et al, 2008;Rozos et al, 2010;Rozos et al, 2011;Yang et al, 2015; Dölek and Avcı, 2016;Ilia and Tsangaratos, 2016). Researchers have reported that a relationship of relative elevation with landslides must emerge by considering its detailed study and definition and the seismic effects of these (Vivas, 1992;Nagarajan, 2000;Gökçeoğlu and Ercanoğlu, 2001;Görüm, 2006;Özdemir, 2009;Jaafari et al, 2015;Avci, 2016a, b, c;Dölek and Avcı, 2016).…”