Landslide Event on 24 June in Sichuan Province, China: Preliminary Investigation and Analysis

Meng, Wanlin; Xu, Ye‐Shuang; Cheng, Wen-Chieh; Arulrajah, Arul

doi:10.3390/geosciences8020039

Cited by 18 publications

(11 citation statements)

References 52 publications

(47 reference statements)

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“…Landslide disasters occur frequently in the mountainous southwestern region of China, and often cause severe economic losses and even huge casualties [1][2][3][4][5]. Identifying where landslides could happen is important for landslides hazard mitigation.…”

Section: Introductionmentioning

confidence: 99%

Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR

et al. 2021

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Landslide disasters occur frequently in the mountainous areas in southwest China, which pose serious threats to the local residents. Interferometry Synthetic Aperture Radar (InSAR) provides us the ability to identify active slopes as potential landslides in vast mountainous areas, to help prevent and mitigate the disasters. Quickly and accurately identifying potential landslides based on massive SAR data is of great significance. Taking the national highway near Wenchuan County, China, as study area, this paper used a Stacking-InSAR method to quickly and qualitatively identify potential landslides based on a total of 40 Sentinel SAR images acquired from November 2017 to March 2019. As a result, 72 active slopes were successfully detected as potential landslides. By comparing the results from Stacking-InSAR with the results from the traditional SBAS-InSAR (Small Baselines Subset) time series method, it was found that the two methods had a high consistency, with 81.7% potential landslides identified by both of the two methods. A detailed comparison on the detection differences was performed, revealing that Stacking-InSAR, compared to SBAS-InSAR may miss a few active slopes with small spatial scales, small displacement levels and the ones affected by the atmosphere, while it has good performance on poor-coherence regions, with the advantages of low technical requirements and low computation labor. The Stacking-InSAR method would be a fast and powerful method to qualitatively and effectively identify potential landslides in vast mountainous areas, with a comprehensive understanding of its specialty and limitations.

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Section: Introductionmentioning

confidence: 99%

Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR

et al. 2021

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“…In order to test the capability of SETSM DEMs for change detection and rapid response use, we used the 2017 Xinmo landslide as a case study. At 5:00 a.m. on June 24, 2017 a major landslide occurred in Xinmo Village, Sichuan Province, China, resulting from heavy rainfall, steep topography, and a deep seated slide interface (Meng et al, 2018). This catastrophic event buried the village of Xinmo and resulted in 10 fatalities.…”

Section: Geomorphic Metricsmentioning

confidence: 99%

Evaluation of high‐resolution DEMs from satellite imagery for geomorphic applications: A case study using the SETSM algorithm

Atwood

West

2021

Earth Surf Processes Landf

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High-resolution digital elevation models (DEMs) have revolutionized research in geomorphology by allowing for detailed quantitative analysis of Earth's surface. Satellite stereo images offer the promise of expanding the availability of high-resolution DEMs over broad areas, but rigorous evaluation of the scientific application of these datasets remains limited. In this study, we consider DEMs built using stereo pairs of high-resolution (0.5 m) satellite imagery and the open-source DEM extraction algorithm, Surface Extraction from TIN Space-search Minimization (SETSM). We selected locations across a range of landscapes to evaluate the application of these DEMs to geomorphic problems, with particular attention to hillslope analyses where high spatial resolution has been shown to be important for revealing topographic signatures of tectonic and environmental processes. We compared the quality of SETSM 2 m DEMs to LiDAR-derived DEMs and the widely available SRTM-30 m and ALOS-30 m DEMs by comparing the elevation data and derivative products (e.g., slope, aspect, and curvature). We found that SETSM DEMs performed noticeably better than SRTM and ALOS DEMs, but with systematic biases relative to LiDAR DEMs in regions with vegetation. Moreover, noise in the initial SETSM elevation data is amplified with every subsequent derivative, significantly decreasing quality. Finally, we evaluated the potential use of SETSM products for change detection. Applying DEM differencing to a major landslide, we found volume and sediment thickness from SETSM DEMs were similar to volumes and thicknesses from other studies. This example illustrates the capabilities of SETSM and other satellite-based stereophotogrammetry for contributing to rapid response after natural disasters. Overall, we conclude that DEMs derived from satellite image stereo-photogrammetry can markedly improve on lower resolution global elevation data for terrain analysis and can open possibilities for change detection, but that care needs to be taken in their application especially in regions with significant vegetation.

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“…The 275 total volume of the rock mass deposits is about 4.5×10 6 m 3 , about 210 m long and 300 widths, and the fastest traveling velocity of the massive loose landslide deposits is about 74.6 m (Fig. 8) Fang, 2017;Meng, 2018). Massive collapse-sliding is one the catastrophic disasters that pose threats to the people's lives in the 280 earthquake area.…”

Section: Collapse-slidementioning

confidence: 99%

Failure modes of loose landslide deposits in 2008 Wenchuan earthquake area in China

Gan

Zhang

2019

Preprint

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Abstract. In this study, a geological investigation and statistical analysis of the post-earthquake slope deposit failures in a meizoseismal area were presented, with a selected example from the 2008 Ms 8.0 Wenchuan earthquake occurred in Sichuan Province in China. The typical slope deposit failures were surveyed in three meizoseismal areas, namely Qingchuan county in Guangyuan city, Beichuan county in Mianyang city, and the epicenter area, Wenchuan county in Aba Tibetan Autonomous Prefecture. According to the movement, material and deformation mechanism of rock or soil, the failures of the post-earthquake landslide deposit could be subdivided into four categories, i.e. slide, collapse, erosion and flow. This classification of failures of landslide deposit considers the topographic and failure after the earthquake. Besides, some other important factors such as topography, lithology and hydrogeology are also considered. The above mentioned four failure categories are further split into 12 sub-classification. The complicated deformation mechanism and different failure patterns of the slope deposits are analyzed in typical deposits. This classification provides a good reference for the prediction of geological hazards, whereas mitigation of the landslide or debris flows caused by loose deposits in the meizoseismal area is still a difficult task.

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Landslide Event on 24 June in Sichuan Province, China: Preliminary Investigation and Analysis

Cited by 18 publications

References 52 publications

Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR

Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR

Evaluation of high‐resolution DEMs from satellite imagery for geomorphic applications: A case study using the SETSM algorithm

Failure modes of loose landslide deposits in 2008 Wenchuan earthquake area in China

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