Estimating volume of deep-seated landslides and mass transport in Basihlan river basin, Taiwan

Lin, Meei-Ling; Chen, Te-Wei

doi:10.1016/j.enggeo.2020.105825

Cited by 9 publications

(4 citation statements)

References 39 publications

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“…The DTMH provides detailed topographic variations for mapping of such lineaments. In this study, the shaded relief from DTMH obtained at eight different azimuth angles was used to locate the lineaments of geological structure of the terrain following the method by Lin et al [26,29]. The azimuth angle was measured from north in the clockwise direction.…”

Section: Mapping Of Deep-seated Landslide and Lineamentmentioning

confidence: 99%

Investigation of Geological Structures Using UAV Lidar and Its Effects on the Failure Mechanism of Deep-Seated Landslide in Lantai Area, Taiwan

et al. 2021

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The deep-seated landslide in the Lantai area, Taiwan, has a long history of landslide activity and often damages the sole access road to the Tai-Ping Mountain National Forest Recreation Area. This study adopted the high-resolution digital terrain model (DTMH) derived from UAV mounted LiDAR point cloud data for mapping geological structures and verified through field investigation. A slope model was proposed with mapped geological structures and shear zone, and numerical analysis was conducted using finite difference analysis. The failure mechanism was found to be significantly affected by the shear zone bounded by geological structures, which would not have been uncovered without the high-resolution DTM (DTMH). The resulting landslide behavior consisted well with mapped scarp, borehole data, and conformed with the event records. These results provided vital information supporting hazard mitigation strategy.

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Section: Mapping Of Deep-seated Landslide and Lineamentmentioning

confidence: 99%

Investigation of Geological Structures Using UAV Lidar and Its Effects on the Failure Mechanism of Deep-Seated Landslide in Lantai Area, Taiwan

et al. 2021

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“…A study by Lin et al (2020) made use of LiDAR DTMs to obtain possible landslide volume at the critical surface of a pre-landslide event in Basihlan River Basin, Taiwan, by determining topographic variations between pre-and post-landslide event and computing the remaining volume of deep-seated landslides that may be transported in the future.…”

Section: Lidar Dtm For Landslide Applicationsmentioning

confidence: 99%

“…Remaining landslide volume along the slope of deep-seated landslides may pose hazards on the area when triggered by heavy rainfall and other natural or anthropogenic causes (Lin et. al, 2020).…”

Section: Introduction 11 Backgroundmentioning

confidence: 99%

Gis-Based Landslide Volume Estimation Using Digital Terrain Models Derived From Lidar and Radar Systems: Case of Pidigan, Abra

Dalagan

Principe

2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Southwest Monsoon (Habagat) and Typhoon Luis caused a deep-seated landslide that struck Sitio Kayang, Brgy. Immuli, Pidigan, Abra on August 15, 2018. Rainfall-induced deep-seated landslides displace partially at a time which necessitates the determination of remaining landslide volume along the slope. In this study, the potential landslide volume and mass transport were estimated using several remote sensing products, including SAR (Synthetic Aperture Radar) data and LiDAR-DTM (Light Detection and Ranging-Digital Terrain Model). The post-landslide DTM was generated using Sentinel-1 SAR data. The potential landslide volume and landslide failure surfaces were ascertained through the stability analysis using Scoops3D, while the mass transport volume was obtained from the pre- and post-landslide DTM. Results showed that the estimated total volume in all the landslide areas was 135,962 m3. Meanwhile, the remaining landslide volume (i.e., difference between potential volume from pre-landslide event and volume of transported mass) yielded illogical values due to the derived large mass transport values. This blunder may be attributed to the generalization of the transported volume (due to Sentinel-1 DTM coarse resolution), and decorrelation due to vegetation cover. Overall, the LiDAR-DTM data delivered a high-resolution estimation of the potential landslide volume and proved to be useful for landslide application studies. Future studies may incorporate field data (e.g., geotechnical parameters, groundwater, landslide actual measurements) for more accurate performance of stability analysis and may best to utilize LiDAR-DTM in post-landslide volume computation for a more reliable estimation of mass transport and potentially remaining landslide volume.

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“…Estimating the volume of displaced materials in a landslide is a crucial index for understanding the significance of the event and planning post-disaster activities. A difference of elevation between pre-and post-event DEMs (DEMs of difference: DoD) has been used to identify the location of the affected areas and quantify the displaced soil volume [9][10][11][12]. Among various remote sensing data sources, the light detection and ranging (LiDAR) technique can produce a reliable estimate of morphological change [13].…”

Section: Introductionmentioning

confidence: 99%

Volumetric Analysis of the Landslide in Abe Barek, Afghanistan Based on Nonlinear Mapping of Stereo Satellite Imagery-Derived DEMs

Atefi

Miura

2021

Remote Sensing

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On 2 May 2014, a large-scale landslide in Abe Barek, Badakhshan, Afghanistan, produced extensive damage to the buildings and killed hundreds of people. Evaluations of the extent and the volume of the displaced materials are vital for post-disaster management activities. In this study, we present the applicability of a nonlinear geometric correction technique for decreasing the undesired registration errors between pre- and post-event digital elevation models (DEMs) generated from high-resolution stereo pair satellite imagery, identifying landslide affected areas, and quantifying the landslide volume from DEMs of difference (DoD) analysis. The nonlinear mapping method consists of shifting vector generation in subareas of the DEMs, consensus operations, and interpolation of the shifting vectors. The quality assessment confirmed that the method outperformed the simple DoD technique by eliminating a large-scale of geometric errors in an unaffected area. We estimated the volume of the landslide as 1.05 × 106 m3 from the DoD corrected by the nonlinear method, and discussed the relationship between the area and volume compared to those of the previous studies.

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Estimating volume of deep-seated landslides and mass transport in Basihlan river basin, Taiwan

Cited by 9 publications

References 39 publications

Investigation of Geological Structures Using UAV Lidar and Its Effects on the Failure Mechanism of Deep-Seated Landslide in Lantai Area, Taiwan

Investigation of Geological Structures Using UAV Lidar and Its Effects on the Failure Mechanism of Deep-Seated Landslide in Lantai Area, Taiwan

Gis-Based Landslide Volume Estimation Using Digital Terrain Models Derived From Lidar and Radar Systems: Case of Pidigan, Abra

Volumetric Analysis of the Landslide in Abe Barek, Afghanistan Based on Nonlinear Mapping of Stereo Satellite Imagery-Derived DEMs

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