Mapping Rainfall-Triggered Slidequakes and Seismic Landslide-Volume Estimation at Heumoes Slope

2011 ◽  
Vol 10 (2) ◽  
pp. 487-495 ◽  
Author(s):  
M. Walter ◽  
M. Walser ◽  
M. Joswig
Keyword(s):  
Volume Estimation ◽  
Landslide Volume ◽  
Seismic Landslide

scholarly journals Topographic Evolution Involving Co-Seismic Landslide, Deformation, Long-Term Folding and Isostatic Rebound: A Case Study on the 2004 Chuetsu Earthquake

2021 ◽  
Vol 13 (6) ◽  
pp. 1073
Author(s):  
Jinghao Lei ◽  
Zhikun Ren ◽  
Takashi Oguchi ◽  
Peizhen Zhang ◽  
Shoichiro Uchiyama
Keyword(s):  
Hanging Wall ◽  
Volume Estimation ◽  
Catchment Scale ◽  
Epicentral Area ◽  
Landslide Volume ◽  
Digital Elevation ◽  
Geological Evolution ◽  
Seismically Induced Landslides ◽  
Seismic Landslide

Co-seismic landslide volume information is critical to understanding the role of strong earthquakes in topographic and geological evolution. The availability of both pre- and post-earthquake high-resolution digital elevation models (DEMs) provides us with the opportunity to develop a new approach to obtain robust landslide volume information. Here, we propose a method for landslide volume estimation and test it in the Chuetsu region, where a Mw 6.6 earthquake occurred in 2004. First, we align the DEMs by reconstructing the horizontal difference. Then, we quantitatively obtain the landslide volume in the epicentral area by differencing the pre- and post-earthquake DEMs. We convert the landslide volume into the distribution of average catchment-scale denudation and the resulting long-term crustal rebound. Our findings reveal that the Chuetsu earthquake mainly roughens the topography in the low-elevation Chuetsu region. Our results indicate that the preserved topography not only is due to the uplift caused by fault-related folding on the hanging wall of the Muikamachi fault but also undergoes erosion caused by seismically induced landslides and crustal rebound also modifies the topography in the long term. This study confirms that the differential DEM method is a valuable approach for quantitative analysis of topographic and geological evolution.

scholarly journals Topographic changes due to the 2004 Chuetsu thrusting earthquake in low mountain region

2019 ◽  
Author(s):  
Zhikun Ren ◽  
Takashi Oguchi ◽  
Peizhen Zhang ◽  
Shoichiro Uchiyama
Keyword(s):  
Scaling Laws ◽  
Catchment Scale ◽  
Volume Estimate ◽  
Epicentral Area ◽  
Quantitative Studies ◽  
Landslide Volume ◽  
Seismically Induced Landslides ◽  
Seismic Landslide ◽  
Topographic Evolution

Abstract. The co-seismic landslide volume information is critical to understanding the role of strong earthquake in topographic evolution. However, the co-seismic landslide volumes are mainly obtained using statistical scaling laws, which are not accurate enough for quantitative studies of the spatial pattern of co-seismically induced erosion and the topographic changes caused by the earthquakes. The availability of both pre- and post- earthquake high-resolution DEMs provide us the opportunity to try new approach to get robust landslide volume information. Here, we propose a new method in landslide volume estimate and tested it in Chuetsu region, where a Mw 6.6 earthquake occurred in 2004. Firstly, we align the DEMs by reconstructing the horizontal difference, then we quantitatively obtained the landslide volume in the epicentral area by differencing the pre- and post-earthquake DEMs. We convert the landslide volume into the distribution of average catchment-scale seismically induced denudation. Our results indicate the preserved topography is not only due to the uplifting caused by fault-related folding on the hangwall of Muikamachi fault, but also undergone erosion caused by the seismically induced landslides. Our findings reveal that Chuetsu earthquake mainly roughens the topography in the Chuetsu region of low elevation. This study also reveal that the differential DEM method is a valuable approach in analyzing landslide volume, as well as quantitative geomorphic analysis.

scholarly journals Beyond 2D inventories : synoptic 3D landslide volume calculation from repeat LiDAR data

2020 ◽  
Author(s):  
Thomas G. Bernard ◽  
Dimitri Lague ◽  
Philippe Steer
Keyword(s):  
Point Cloud ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Aerial Images ◽  
3D Point Cloud ◽  
Volume Calculation ◽  
Landslide Volume ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Areal Mapping

Abstract. Efficient and robust landslide mapping and volume estimation is essential to rapidly infer landslide spatial distribution, to quantify the role of triggering events on landscape changes and to assess direct and secondary landslide-related geomorphic hazards. Many efforts have been made during the last decades to develop landslide areal mapping methods, based on 2D satellite or aerial images, and to constrain empirical volume-area (V-A) allowing in turn to offer indirect estimates of landslide volume. Despite these efforts, some major issues remain including the uncertainty of the V-A scaling, landslide amalgamation and the under-detection of reactivated landslides. To address these issues, we propose a new semi-automatic 3D point cloud differencing method to detect geomorphic changes, obtain robust landslide inventories and directly measure the volume and geometric properties of landslides. This method is based on the M3C2 algorithm and was applied to a multi-temporal airborne LiDAR dataset of the Kaikoura region, New Zealand, following the Mw 7.8 earthquake of 14 November 2016. We demonstrate that 3D point cloud differencing offers a greater sensitivity to detect small changes than a classical difference of DEMs (digital elevation models). In a small 5 km2 area, prone to landslide reactivation and amalgamation, where a previous study identified 27 landslides, our method is able to detect 1431 landslide sources and 853 deposits with a total volume of 908,055 ± 215,640 m3 and 1,008,626 ± 172,745 m3, respectively. This high number of landslides is set by the ability of our method to detect subtle changes and therefore small landslides with a carefully constrained lower limit of 20 m2 (90 % with A 

scholarly journals GIS-BASED LANDSLIDE VOLUME ESTIMATION USING DIGITAL TERRAIN MODELS DERIVED FROM LIDAR AND RADAR SYSTEMS: CASE OF PIDIGAN, ABRA

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 109-115
Author(s):  
A. C. Dalagan ◽  
J. A. Principe
Keyword(s):  
Stability Analysis ◽  
Mass Transport ◽  
Digital Terrain Model ◽  
Large Mass ◽  
Southwest Monsoon ◽  
Volume Estimation ◽  
Synthetic Aperture Radar Data ◽  
Digital Terrain ◽  
Landslide Volume ◽  
Landslide Event

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.

scholarly journals Assessment of Landslide-Induced Geomorphological Changes in Hítardalur Valley, Iceland, Using Sentinel-1 and Sentinel-2 Data

2020 ◽  
Vol 10 (17) ◽  
pp. 5848
Author(s):  
Zahra Dabiri ◽  
Daniel Hölbling ◽  
Lorena Abad ◽  
Jón Kristinn Helgason ◽  
Þorsteinn Sæmundsson ◽  
...  
Keyword(s):  
Significant Risk ◽  
Radar Data ◽  
Volume Estimation ◽  
Lake Area ◽  
Synthetic Aperture Radar Data ◽  
Landslide Volume ◽  
Digital Elevation ◽  
Hazard And Risk ◽  
Geomorphological Changes ◽  
Sentinel 2

Landslide mapping and analysis are essential aspects of hazard and risk analysis. Landslides can block rivers and create landslide-dammed lakes, which pose a significant risk for downstream areas. In this research, we used an object-based image analysis approach to map geomorphological features and related changes and assess the applicability of Sentinel-1 data for the fast creation of post-event digital elevation models (DEMs) for landslide volume estimation. We investigated the Hítardalur landslide, which occurred on the 7 July 2018 in western Iceland, along with the geomorphological changes induced by this landslide, using optical and synthetic aperture radar data from Sentinel-2 and Sentinel-1. The results show that there were no considerable changes in the landslide area between 2018 and 2019. However, the landslide-dammed lake area shrunk between 2018 and 2019. Moreover, the Hítará river diverted its course as a result of the landslide. The DEMs, generated by ascending and descending flight directions and three orbits, and the subsequent volume estimation revealed that—without further post-processing—the results need to be interpreted with care since several factors influence the DEM generation from Sentinel-1 imagery.

Application of a multi-temporal, LiDAR-derived, digital terrain model in a landslide-volume estimation

2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Chih-Ming Tseng ◽  
Ching-Weei Lin ◽  
Colin P. Stark ◽  
Jin-Kin Liu ◽  
Li-Yuan Fei ◽  
...  
Keyword(s):  
Digital Terrain Model ◽  
Volume Estimation ◽  
Terrain Model ◽  
Digital Terrain ◽  
Landslide Volume ◽  
Multi Temporal

scholarly journals Modeling of landslide volume estimation

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Abolghasem Amirahmadi ◽  
Sima Pourhashemi ◽  
Mokhtar Karami ◽  
Elahe Akbari
Keyword(s):  
Regression Model ◽  
Small Area ◽  
Volume Estimation ◽  
P Value ◽  
Average Depth ◽  
Suggested Model ◽  
Agricultural Lands ◽  
Large Area ◽  
Landslide Volume ◽  
Mass Displacement

AbstractMass displacement of materials such as landslide is considered among problematic phenomena in Baqi Basin located at southern slopes of Binaloud, Iran; since, it destroys agricultural lands and pastures and also increases deposits at the basin exit. Therefore, it is necessary to identify areas which are sensitive to landslide and estimate the significant volume. In the present study, in order to estimate the volume of landslide, information about depth and area of slides was collected; then, considering regression assumptions, a power regression model was given which was compared with 17 suggested models in various regions in different countries. The results showed that values of estimated mass obtained from the suggested model were consistent with observed data (P value= 0.000 and R = 0.692) and some of the existing relations which implies on efficiency of the suggested model. Also, relations that were created in small-area landslides were more suitable rather than the ones created in large-area landslides for using in Baqi Basin. According to the suggested relation, average depth value of landslides was estimated 3.314 meters in Baqi Basin which was close to the observed value, 4.609 m.

scholarly journals Supplemental Material: Extreme event-driven sediment aggradation and erosional buffering along a tectonic gradient in southern Taiwan

2021 ◽  
Author(s):  
Clarke DeLisle ◽  
et al.
Keyword(s):  
Sediment Transport ◽  
Extreme Event ◽  
Volume Estimation ◽  
Transport Modeling ◽  
Landslide Volume ◽  
Event Driven ◽  
Southern Taiwan ◽  
Channel Aggradation

Methods for landslide volume estimation, channel aggradation mapping, sediment transport modeling, and recurrence estimate.<br>

scholarly journals Volume Estimation of Landslide Affected Soil Moisture Using TRIGRS: A Case Study of Longxi River Small Watershed in Wenchuan Earthquake Zone, China

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 71
Author(s):  
Tong Sun ◽  
Zhiyuan Deng ◽  
Zexing Xu ◽  
Xiekang Wang
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Wenchuan Earthquake ◽  
Slope Angle ◽  
Volume Estimation ◽  
Sediment Supply ◽  
Method Of Calculation ◽  
Landslide Volume ◽  
Mountainous Watershed ◽  
The Impact

After the 2008 Mw 7.9 Wenchuan earthquake, geological hazards occurred frequently in the southwest mountainous watershed. Frequent landslide disasters provide abundant sediment supply for mountain torrent disasters. The estimation of the potential landslide volume is essential for the risk assessment of mountain torrent disasters. In this study, a method of calculation that combines TRIGRS and the slope-units for estimating the landslide volume of a small mountainous watershed has been established. TRIGRS analyzes the watershed landslide safety factor under rainfall conditions based on grid-cells. The slope-units extract the results and combine the empirical power law formula to calculate the potential landslide volume. In this paper, we use this method to assess the landslide volume of the Longxi river basin. The results show that the area and volume estimates of the landslides are consistent with the results observed from satellite images and field surveys. This method can be used to study the impact of sediment transport on mountain torrent disasters in the basin. With different moisture content conditions, the results show that the soil moisture content and slope angle significantly affect the distribution and volume of potential landslides in the watershed, giving rise to the uncertainty of the landslide estimation.

scholarly journals Supplemental Material: Extreme event-driven sediment aggradation and erosional buffering along a tectonic gradient in southern Taiwan

2021 ◽  
Author(s):  
Clarke DeLisle ◽  
et al.
Keyword(s):  
Sediment Transport ◽  
Extreme Event ◽  
Volume Estimation ◽  
Transport Modeling ◽  
Landslide Volume ◽  
Event Driven ◽  
Southern Taiwan ◽  
Channel Aggradation

Methods for landslide volume estimation, channel aggradation mapping, sediment transport modeling, and recurrence estimate.<br>

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