Assessing landslide volume using two generic models: application to landslides in Whatcom County, Washington, USA

Paulín, Gabriel Legorreta; Mickelson, Katherine A.; Contreras, Trevor A.; Gallin, William; Jacobacci, Kara E.; Bursik, Marcus

doi:10.1007/s10346-021-01825-z

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…The intercomparison of topographic products, also known as DEM differencing, can be used to derive surface elevation and volumetric changes. Information on landslide volumes helps to understand the role of triggering events and landslides on landscape evolution (Bernard et al, 2021;Paulin et al, 2022), such as the river damming potential of landslides (Argentin et al, 2021). DEMs derived from different remote sensing data have been used to estimate landslide volumes.…”

Section: Introductionmentioning

confidence: 99%

“…DEMs derived from different remote sensing data have been used to estimate landslide volumes. These include, for example, historical aerial photographs (Robson et al, 2022;Santangelo et al, 2022), Uncrewed Aerial Vehicle (UAV) imagery (Chang et al, 2020;Turner et al, 2015), optical high-resolution stereo satellite imagery (Atefi and Miura, 2021;Tsutsui et al, 2007), or Light Detection And Ranging (LiDAR) data (Bernard et al, 2021;Paulin et al, 2022;Ventura et al, 2011). However, the applicability of existing DEMs is often limited.…”

Section: Introductionmentioning

confidence: 99%

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An Open-Source-Based Workflow for Dem Generation From Sentinel-1 for Landslide Volume Estimation

Abad

Hölbling²,

Dabiri³

et al. 2022

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

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Abstract. Digital elevation models (DEMs) serve as a basis for various geomorphological applications, such as, landform mapping, natural hazard assessment, and landslide characterisation. The inter-comparison of DEMs can be used to provide estimates of topographic change, for example, volume changes. Sentinel-1 synthetic aperture radar (SAR) data can be used to generate multitemporal topographic datasets using interferometric SAR (InSAR). Such analyses are often conducted using commercial software; however, a well-structured workflow based on free and open-source software (FOSS) increases the applicability and transferability of the DEM generation method and can facilitate the use of multi-temporal topographic analysis within the Earth Sciences. In this study, we aim to develop an open-source-based workflow for the generation of multi-temporal DEMs from Sentinel-1 data, and to explore their potential for landslide volume estimation using FOSS. We implemented this semi-automated and transferable workflow bundled in the open-source Python package “SliDEM”, which relies on SNAP, SNAPHU, and several other open-source software for geospatial and geomorphological applications, all distributed within a Docker image. Two major landslides in Austria and Norway were selected to test, evaluate, and validate the workflow in terms of reliability, performance, reproducibility, and transferability. Even if the quality of the Sentinel-1-based DEMs varies among the study areas, the preliminary results are promising. However, there is a need for improvement and thorough analysis of the causes of elevation errors. A comprehensive evaluation of the influence of the perpendicular and temporal baselines, topography, land use/land cover, and other environmental conditions can be systematically assessed within the “SliDEM” workflow.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Open-Source-Based Workflow for Dem Generation From Sentinel-1 for Landslide Volume Estimation

Abad

Hölbling²,

Dabiri³

et al. 2022

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

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“…Overall, identi cation of the equilibrium line can improve estimating the tsunamigenic volume of a submarine landslide from bathymetric data and therefore this is an advance of previous methods (e.g.,Lastras et al, 2004;McAdoo et al, 2000;Völker, 2010).The tsunamigenic volume estimated with the equilibrium line concept is very sensitive to the pre-failure sea oor reconstruction. This may be challenging for submarine landslides in morphologically complex settings where the pre-failure sea oor reconstruction is prone to large degrees of subjectivity (e.g.,Omira et al, 2022;Paulin et al, 2022;van Kreveld et al, 2021;Völker, 2010). It results from the equilibrium line concept that Va can never exceed Ve, so that Va serves as the lower bound of Ve.…”

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confidence: 99%

Bathymetry-based submarine landslide volume assessments

Sager

Urlaub

Berndt

2022

Preprint

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Submarine landslides can cause devastating tsunamis. The size of such tsunamis depends on water depth, acceleration, maximum velocity, and initial volume of the landslide. In the past, submarine landslide volume as the most important of these parameters has often been estimated by seismic data. It is well-established that this can lead to a significant over-estimation of the tsunamigenic landslide volume because the seismic data do not allow to distinguish the initially moving volume from material that has been deformed in-situ or incorporated at great water depth. Here, the volume of evacuated material from the source area derived from seafloor morphology is a good measure for the total tsunamigenic landslide volume. The analysis of high-resolution 3D reflection seismic data that cover the same submarine landslide also shows that a much greater volume of the seismically imaged landslide deposit has remained largely in-situ and could thus not have contributed to an associated tsunami. This distinction could not have been made with lower resolution 3D reflection seismic data or with high-resolution 2D reflection seismic data. These findings imply that under circumstances that tend to be fulfilled for small landslides, the bathymetrically derived volume of the source area can be a much better measure for the tsunamigenic volume of submarine landslides than individual seismic profiles.

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An integrated framework for wide-area active landslide detection with InSAR observations and SAR pixel offsets

Zhang

et al. 2022

Landslides

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Assessing landslide volume using two generic models: application to landslides in Whatcom County, Washington, USA

Cited by 5 publications

References 27 publications

An Open-Source-Based Workflow for Dem Generation From Sentinel-1 for Landslide Volume Estimation

An Open-Source-Based Workflow for Dem Generation From Sentinel-1 for Landslide Volume Estimation

Bathymetry-based submarine landslide volume assessments

An integrated framework for wide-area active landslide detection with InSAR observations and SAR pixel offsets

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