Weile Li

Co-seismic landslide inventory and susceptibility mapping in the 2008 Wenchuan earthquake disaster area, China

The Ms 8.0 May 12, 2008 Wenchuan earthquake triggered tens of thousands of landslides. The widespread landslides have caused serious casualties and property losses, and posed a great threat to post-earthquake reconstruction. A spatial database, inventoried 43,842 landslides with a total area of 632 km2, was developed by interpretation of multi-resolution remote sensing images. The landslides can be classified into three categories: swallow, disrupted slides and falls; deep-seated slides and falls, and rock avalanches. The correlation between landslides distribution and the influencing parameters including distance from co-seismic fault, lithology, slope gradient, elevation, peak ground acceleration (PGA) and distance from drainage were analyzed. The distance from co-seismic fault was the most significant parameter followed by slope gradient and PGA was the least significant one. A logistic regression model combined with bivariate statistical analysis (BSA) was adopted for landslide susceptibility mapping. The study area was classified into five categories of landslide susceptibility: very low, low, medium, high and very high. 92.0% of the study area belongs to low and very low categories with corresponding 9.0% of the total inventoried landslides. Medium susceptible zones make up 4.2% of the area with 17.7% of the total landslides. The rest of the area was classified into high and very high categories, which makes up 3.9% of the area with corresponding 73.3% of the total landslides. Although the susceptibility map can reveal the likelihood of future landslides and debris flows, and it is helpful for the rebuilding process and future zoning issues.

Rapid Susceptibility Mapping of Co-seismic Landslides Triggered by the 2013 Lushan Earthquake Using the Regression Model Developed for the 2008 Wenchuan Earthquake

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas. The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability. Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone, with similar topographical and geological conditions. The two earthquakes are both featured by thrust fault and similar seismic mechanism. This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake. Six influencing parameters were taken into consideration: distance from the seismic fault, slope gradient, lithology, distance from drainage, elevation and Peak Ground Acceleration (PGA). The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan, Baoxing and Tianquan counties. The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work. The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area. The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.

Historical Co-seismic Landslides Inventory and Analysis Using Google Earth: A Case Study of 1920 M8.5 Haiyuan Earthquake, China

1000 landslides triggered by the 1920 Ms 8.5 Haiyuan Earthquake were mapped as polygons with remote sensing images provided by Google Earth. Although it was more than 90 years ago, the boundary of medium and large scale landslide triggered by the earthquake is still clear on the images. The landslides were mainly distributed in the west part of Xiji County and the southeast of Haiyuan County, which could be attributed to the difference of loess thickness. The statistical analysis results indicated that the landslide distribution was not mainly controlled by the earthquake parameters (the distance to the epicenter, the seismic intensity and the distance to the seismogenic fault rupture), but by the topographical parameters (elevation, slope height, slope gradient and slope aspect). The field surveys found that most of the landslides occurring on concave slopes of gentler than 20° with long run-out and high speed may be due to the loess liquefaction.

Simultaneous Debris Flows of 13 August 2010 in the Mianyuan River Basin, China

The Wenchuan Earthquake triggered tens of thousands of landslides and many areas became susceptible to debris flow. From 12th to 14th, August 2010, heavy rain dropped in Wenchuan Earthquake disaster area, Sichuan province, China. The heavy rain triggered simultaneous occurrence of many debris flows in Qingping town in Mianzhu city, resulting in heavy casualty and property loss. Within the range of 4 km in Qingping Segment of Mianyuan River, 11 debris flows occurred simultaneously and the total runout deposits were about 600 × 104 m3 mainly from Wenjia and Zoumaling gully. Field investigation indicated that the sediment supply was mainly derived from landslide deposits. The debris flows could be classified into three types, including gully erosion starting, branch gully starting and source area starting. It is suggested that Wenchuan earthquake areas are still prone to debris flows. Therefore it is important to regulate and restrict use of hazard areas as well as to arrange relocation of people currently living in areas susceptible to debris flows.

Failure mechanisms and characteristics of the 2016 catastrophic rockslide at Su village, Lishui, China

This paper describes a recent large rockslide, which occurred at Su village in Lishui, Zhejiang Province, China, on September 28, 2016. In the past decade, a vegetation-free deformed surface was clearly visible and frequent rockfalls were noticed. Due to strong sustained rainfall, approximately 0.4 million m3 of granite blocks rapidly descended from the upper part of the hillside. The mass rushed into the V-shaped valley resulting in the formation of a barrier dam and dammed lake. The catastrophic rockslide caused 27 deaths and more than 20 houses were destroyed. The evolutionary process before the rockslide is clearly captured by high-resolution remote sensing images and photos. Video of the rockslide and field investigations show entrainment of superficial material in the middle and lower parts of the slope.

Information Management System of Landslides Triggered by Wenchuan Earthquake on 12th May, 2008: --Based on WebGIS and Database Technology

Wenchuan Earthquake triggered more than thousands of landslides, which seriously threatened the lives and properties of local people in the disaster areas. Even though emergency investigation and monitoring have been carried on after the earthquake in order to make sure the reconstruction work well, there is still need an effective way to manage the considerable disaster information immediately. This paper presents a preliminary study of a WebGIS-based approach to the representation, organization and access of geohazard information-including map & data query, statistic, spatial analysis and early warning. The system is not only to assist in the decision-making process for administrator to prevention disaster, but also to provide a platform for the more end-users with limited GIS knowledge to understand the geohazard and a cost-saving solution to access up-to-date spatial datasets customized for a specific topic.

Multi-Source Information Management System of Railway Geological Environment Based on GIS Technology

The selection of rural railway route requires the utilization of multi-source data such as topography, geology, environment and remote-sensing data, etc.. Based on the data capture, integrative management and spatial analysis of ARCGIS, the multi-source information management system on railway geological environment has been designed. In this system, multi-source data of different data type, scale and coordination are integrated to the same software platform, improving the utilization efficiency and share of data. Besides, the spatial analysis and 3D visualization functions of the system make the railway route selection become more visual and intelligent, and thus greatly raise the work efficiency.