Landslide hazard assessment in the Himalayas (Nepal and Bhutan) based on Earth-Observation data

Ambrosi, Christian; Strozzi, Tazio; Scapozza, Cristian; Wegmüller, U.

doi:10.1016/j.enggeo.2018.02.020

Cited by 62 publications

(34 citation statements)

References 32 publications

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“…SAR sensors have the advantage that they can "see" the land surface during all weather conditions, which is particularly valuable when trying to observe landslide changes during the monsoon season. InSAR techniques have been used to study slow moving landslides (<1-2 cm/year) Tofani et al, 2014;Ambrosi et al, 2018). Time series observation techniques also known as Multi-Temporal InSAR (MT-InSAR) have been developed (Ferretti et al, 2001(Ferretti et al, , 2011Berardino et al, 2002;Hooper et al, 2004;Hooper, 2008) to mitigate unwanted phase contributions by several different sources such as electronic properties of the ground, atmospheric delay, inaccurate orbit, and combined noises (Colesanti and Wasowski, 2006).…”

Section: Landslide Mappingmentioning

confidence: 99%

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

et al. 2019

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Cascading hazard processes refer to a primary trigger such as heavy rainfall, seismic activity, or snow melt, followed by a chain or web of consequences that can cause subsequent hazards influenced by a complex array of preconditions and vulnerabilities. These interact in multiple ways and can have tremendous impacts on populations proximate to or downstream of these initial triggers. High Mountain Asia (HMA) is extremely vulnerable to cascading hazard processes given the tectonic, geomorphologic, and climatic setting of the region, particularly as it relates to glacial lakes. Given the limitations of in situ surveys in steep and often inaccessible terrain, remote sensing data are a valuable resource for better understanding and quantifying these processes. The present work provides a survey of cascading hazard processes impacting HMA and how these can be characterized using remote sensing sources. We discuss how remote sensing products can be used to address these process chains, citing several examples of cascading hazard scenarios across HMA. This work also provides a perspective on the current gaps and challenges, community needs, and view forward toward improved characterization of evolving hazards and risk across HMA.

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Section: Landslide Mappingmentioning

confidence: 99%

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

et al. 2019

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“…Three outburst floods were simulated along the Marsyangdi using a lake volume of 281,051 m 3 and drainage following a triangle hydrograph with times to peak discharge (Qp) of 5, 10, and 20 min. The lake volume corresponded to a 15-m-high simulated dam on the Marsyangdi River (Section 2.4.1), which produced a lake of comparable length (1.1 km) to that reported by [5] following the 2015 Gorkha earthquake.…”

Section: Outburst Floodmentioning

confidence: 99%

“…Elevation models of Himalayan topography are required for investigating a range of earth surface processes, including quantifying landslide and landslide-dammed lake volumes (e.g., [1][2][3][4][5]); glacial lake outburst flood (GLOF) assessments (e.g., [6][7][8]); hydraulic modelling (e.g., [9][10][11][12]); hydrological modelling (e.g., [13]; and calculating glacier mass balance and ablation processes (e.g., [14][15][16][17]). Global digital elevation model (DEM) products, such as the Advanced Land Observing Satellite (ALOS) World 3D DEM (AW3D30), offer near-global land surface coverage at 30 m spatial resolution [18].…”

Section: Introductionmentioning

confidence: 99%

UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products

Watson

Kargel

Tiruwa

2019

Drones

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Topography derived using human-portable unmanned aerial vehicles (UAVs) and structure from motion photogrammetry offers an order of magnitude improvement in spatial resolution and uncertainty over small survey extents, compared to global digital elevation model (DEM) products, which are often the only available choice of DEMs in the high-mountain Himalaya. Access to fine-resolution topography in the high mountain Himalaya is essential to assess where flood and landslide events present a risk to populations and infrastructure. In this study, we compare the topography of UAV-derived DEMs, three open-access global DEM products, and the 8 m High Mountain Asia (HMA) DEMs (released in December 2017) and assess their suitability for landslide- and flood-related hazard assessments. We observed close similarity between UAV and HMA DEMs when comparing terrain elevation, river channel delineation, landside volume, and landslide-dammed lake area and volume. We demonstrate the use of fine-resolution topography in a flood-modelling scenario relating to landslide-dammed lakes that formed on the Marsyangdi River following the 2015 Gorkha earthquake. We outline a workflow for using UAVs in hazard assessments and disaster situations to generate fine-resolution topography and facilitate real-time decision-making capabilities, such as assessing landslide-dammed lakes, mass movement volumes, and flood risk.

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“…For topographic reference (Bamler and Hartl, 1998;Rosen et al, 2000) a DEM was generated from TanDEM-X acquisitions performed along ascending (24.01.2013) and descending (01.10.2013) orbits combined to reduce problems of areas masked by layover and shadow which affect differently opposite slopes along north-south oriented valleys in mountainous regions. The DEM was produced with a posting of 0.0001 decimal degrees, corresponding to about 10 m. TanDEM-X DEMs produced with the same methodology in the past over Mount Etna in Italy (Wegmüller et al, 2014) and the Chomolhari region in Bhutan (Ambrosi et al, 2018), regions with comparable topography as our study area, were validated against ground control points. In comparison to more than 100 GPS benchmarks over Mount Etna and 10 GPS survey points in the Chomolhari region mean differences of the elevations of 0.6 m and 3.6 m, respectively, and standard deviations of 4.3 m and 2.8 m, respectively, were found.…”

Section: Satellite Sar Interferometrymentioning

confidence: 99%

“…Using the available data the landslide hazard can be divided in three classes according to mean annual velocities below 2 cm/a, between 2 and 10 cm/a and above 10 cm/a. For regions without DInSAR data the estimation of the movement activity of the landslides is sometimes possible from the geomorphological analysis, but often other criteria, such as similarity of the landslides to other already classified (Ambrosi et al, 2018) or based on slope stability models (Moon and Blackstock, 2004), need to be adopted. With newest satellite missions providing regular acquisitions over longer time periods (e.g.…”

Section: Landslide Hazard Assessmentmentioning

confidence: 99%

Satellite SAR interferometry for the improved assessment of the state of activity of landslides: A case study from the Cordilleras of Peru

Strozzi

Klimeš

Frey

et al. 2018

Remote Sensing of Environment

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In Peru landslides have been causing damages and casualties annually due to the high mountain relief and distinct seasonal precipitation distribution. Satellite Synthetic Aperture Radar (SAR) interferometry represents one possibility for mapping surface deformation at fine spatial resolution over large areas in order to characterize aspects of terrain motion and potentially hazardous processes. We present land surface motion maps derived from satellite SAR interferometry (InSAR) for a part of the Santa River Basin between the Cordilleras Blanca and Negra around the city of Carhuaz in Peru. Using both Persistent Scatterer Interferometry (PSI) and differential SAR Interferograms (DInSAR) from ALOS-1 PALSAR-1, ENVISAT ASAR, ALOS-2 PALSAR-2 and Sentinel-1 we mapped 42 landslides extending over 17,190,141m² within three classes of activity (i.e. 0-2 cm/a, 2-10 cm/a and>10 cm/a). A geomorphological inventory of landslides was prepared from optical satellite imagery and field experience and compared to the InSAR-based slope-instability inventory. The two approaches provide slightly different information about landslide spatial and temporal activity patterns, but altogether they can be combined for the assessment of the state of activity of landslides and possibly the development of hazard maps, which are not systematically available in this region. We conclude that ALOS PALSAR (1 and 2) and Sentinel-1 data have a high potential to derive high-quality surface deformation information of landslides in many mountainous regions worldwide due to their global and frequent acquisition strategies.

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Landslide hazard assessment in the Himalayas (Nepal and Bhutan) based on Earth-Observation data

Cited by 62 publications

References 32 publications

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products

Satellite SAR interferometry for the improved assessment of the state of activity of landslides: A case study from the Cordilleras of Peru

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