Spatial Relations of Earthquake Induced Landslides Triggered by 2015 Gorkha Earthquake Mw = 7.8

Gnyawali, Kaushal Raj; Adhikari, Basanta Raj

doi:10.1007/978-3-319-53485-5_10

Cited by 40 publications

(40 citation statements)

References 23 publications

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“…Individual researchers, governmental organizations, and universities volunteered to collect data for mapping landslides after the Gorkha disaster, either on-site or from satellite images [15,22]. For our research purposes, we compiled all of the available open-source landslide data from Durham University/British Geological Survey [15], the International Center for Integrated Mountain Development (ICIMOD), NGA, and the United Nations Institute for Training and Research (UNITAR-UNISAT) [41].…”

Section: Study Area and Data Collection/processingmentioning

confidence: 99%

Framework for improving the resilience and recovery of transportation networks under geohazard risks

Aydin¹,

Düzgün

Heinimann³

et al. 2018

International Journal of Disaster Risk Reduction

107

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A B S T R A C TRural transportation networks are highly susceptible to geohazards such as earthquakes and landslides. Indirect losses can be severe because the breakdown of a transportation network aggravates rescue, supply, and other recovery activities. The operations and logistics of rural networks that are under seismic risks must be managed using the limited resources specifically in developing countries. We propose a methodology to evaluate road recovery strategies for restoring connectivity after blockages due to earthquakes and earthquake-triggered landslides. This paper gives insight into the recovery process, which can be used by decision-makers for enhancing resilience and supplying immediate relief to rural areas. The proposed framework has four steps: 1) identification of strategies for increasing recovery performance, 2) determination of graph-based metrics to represent network connectivity, 3) applying topology-based and Monte Carlo simulations to each strategy, and 4) analysis of recovery times to compare these resilience-enhancement strategies. The methodology was tested using a case study from Sindhupalchok District, Nepal, a region that was severely affected by the Gorkha earthquake in 2015. The closed road segments and recovery times were determined through field surveys with locals and governmental authorities, and by investigating the intensity of earthquake-triggered landslides. Our results showed that the proposed approach provides information about the recovery behavior of road networks and simplifies the evaluation process. It is robust enough to extend and assess decision-makers' preferences for improving resilience.

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Section: Study Area and Data Collection/processingmentioning

confidence: 99%

Framework for improving the resilience and recovery of transportation networks under geohazard risks

Aydin¹,

Düzgün

Heinimann³

et al. 2018

International Journal of Disaster Risk Reduction

107

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“…The studies on inventory, mechanism, spatial distribution, and assessment of coseismic landslides are of great importance to mitigation of the potential subsequent hazards in the affected area (Harp et al 2011;Xu et al 2014a;Xu et al 2014b;Xu et al 2014c;Xu 2015;Xu et al 2018). This work presents a new inventory of the landslides induced by the 2015 Gorkha event based on visual interpretation of high-resolution satellite images before and after the earthquake as well as verification at selected sites in the field, which is much more detailed and complete than previous work (Kargel et al 2016;Gnyawali and Adhikari 2017;Martha et al 2017;Roback et al 2017). Our results show that the earthquake triggered at least 47,200 landslides, with a total occupation area of about 110km 2 .…”

Section: Introductionmentioning

confidence: 99%

Landslides Triggered by the 2015 Gorkha, Nepal Earthquake

2018

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

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ABSTRACT:The 25 April 2015 Gorkha Mw 7.8 earthquake in central Nepal caused a large number of casualties and serious property losses, and also induced numerous landslides. Based on visual interpretation of high-resolution optical satellite images pre-and post-earthquake and field reconnaissance, we delineated 47,200 coseismic landslides with a total distribution extent more than 35,000 km 2 , which occupy a total area about 110 km 2 . On the basis of a scale relationship between landslide area (A) and volume (V), V = 1.3147 × A 1.2085 , the total volume of the coseismic landslides is estimated to be about 9.64 × 10 8 m 3 . Calculation yields that the landslide number density, area density, and volume density are 1.32km -2 , 0.31%, and 0.027m, respectively. The spatial distribution of these landslides is consistent with that of the mainshock and aftershocks and the inferred causative fault, indicating the effect of the earthquake energy release on the pattern on coseismic landslides. This study provides a new, more detailed and objective inventory of the landslides triggered by the Gorkha earthquake, which would be significant for further study of genesis of coseismic landslides, hazard assessment and the long-term impact of the slope failure on the geological environment in the earthquake-scarred region.

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“…The morphometric topographic classification had a smaller CV value compared with the generic topographic classification. The CV in the generic topographic classification was 23.11 (mammal) and 43.88 (amphibian), but the CV in the morphometric topographic classification was 21.33 (mammal) and 28.64 (amphibian). The ratio of the potential habitat of mammals and amphibians in the morphometric topographic classification was quite similar to their habitat preference and movement ability.…”

Section: Spatial Relationship With the Potential Habitat Of Mammals Amentioning

confidence: 90%

“…We used the topographic classification tools provided by the '6-category slope position parameters' tool in the Land Facet Corridor extension of ArcGIS 9.3 (Environmental Systems Research Institute Inc.(ESRI), Redlands, CL, USA) ( Table 1). Threshold values and topographic class name were based on the previous analysis [41] that has been applied in many other regions having different topographic features [42][43][44][45]. Table 1.…”

Section: Topographical Classification: Morphometric and Genericmentioning

confidence: 99%

Applying Topographic Classification, Based on the Hydrological Process, to Design Habitat Linkages for Climate Change

Lee

Song

et al. 2017

Forests

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Abstract:The use of biodiversity surrogates has been discussed in the context of designing habitat linkages to support the migration of species affected by climate change. Topography has been proposed as a useful surrogate in the coarse-filter approach, as the hydrological process caused by topography such as erosion and accumulation is the basis of ecological processes. However, some studies that have designed topographic linkages as habitat linkages, so far have focused much on the shape of the topography (morphometric topographic classification) with little emphasis on the hydrological processes (generic topographic classification) to find such topographic linkages. We aimed to understand whether generic classification was valid for designing these linkages. First, we evaluated whether topographic classification is more appropriate for describing actual (coniferous and deciduous) and potential (mammals and amphibians) habitat distributions. Second, we analyzed the difference in the linkages between the morphometric and generic topographic classifications. The results showed that the generic classification represented the actual distribution of the trees, but neither the morphometric nor the generic classification could represent the potential animal distributions adequately. Our study demonstrated that the topographic classes, according to the generic classification, were arranged successively according to the flow of water, nutrients, and sediment; therefore, it would be advantageous to secure linkages with a width of 1 km or more. In addition, the edge effect would be smaller than with the morphometric classification. Accordingly, we suggest that topographic characteristics, based on the hydrological process, are required to design topographic linkages for climate change.

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Spatial Relations of Earthquake Induced Landslides Triggered by 2015 Gorkha Earthquake Mw = 7.8

Cited by 40 publications

References 23 publications

Framework for improving the resilience and recovery of transportation networks under geohazard risks

Framework for improving the resilience and recovery of transportation networks under geohazard risks

Landslides Triggered by the 2015 Gorkha, Nepal Earthquake

Applying Topographic Classification, Based on the Hydrological Process, to Design Habitat Linkages for Climate Change

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