Three (nearly) complete inventories of landslides triggered by the May 12, 2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis

Xu, Chong; Xu, Xiwei; Yao, Xia; Dai, Fuchu

doi:10.1007/s10346-013-0404-6

Cited by 464 publications

(217 citation statements)

References 77 publications

(94 reference statements)

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“…We note that for some earthquakes such as the Wenchuan and Haiti events, several inventories are available. For the Wenchuan earthquake the inventory by Xu et al (2014c) seems the most comprehensive and robust, compared to earlier mapping. For Haiti we analyse and compare the inventories of Gorum et al (2013) and Harp et al (2016), which have different interpretations in some areas, likely due to differences in the preand post-earthquake imagery used.…”

Section: Landslide Maps and Compilations Of Landslide Distribution Areamentioning

confidence: 97%

“…Commonly, the landslide distribution area is estimated by locating all landslides caused by an earthquake as accurately and comprehensively as possible, and drawing a single, smooth envelope containing all landslides, regardless of possible variations of landslide density within it (Keefer, 1984;Hancox et al, 1997;Rodriguez et al, 1999 (Xu et al, 2014c). It is also likely that for large earthquakes with widespread landsliding, there is a tendency to focus on the most intensely affected areas, while for smaller earthquakes, the extent over which small rockfalls occur may be investigated in greater detail through field investigations Harp, 2012, 2016).…”

Section: An Objective Definition Of the Landslide Distribution Areamentioning

confidence: 99%

“…These include different A d reported when considering only the area affected by intense landsliding, or including more distant, sparse landsliding (e.g. Hancox et al, 1997;Xu et al, 2014c). This is not an adequate quantification of the uncertainties in the dataset as a whole, but serves to illustrate how estimates of A d may vary or be biased (Fig.…”

Section: An Objective Definition Of the Landslide Distribution Areamentioning

confidence: 99%

See 2 more Smart Citations

Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

Marc

Meunier

Hovius

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. We present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95 % of the total landslide area. Without any empirical calibration the model explains 56 % of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor of 2, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95 % of the total landslide area. Aspects ignored by the model that could explain the residuals include local variations of the threshold of acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop, and rupture directivity. Nevertheless, its simplicity and first-order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines.

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Section: Landslide Maps and Compilations Of Landslide Distribution Areamentioning

confidence: 97%

Section: An Objective Definition Of the Landslide Distribution Areamentioning

confidence: 99%

Section: An Objective Definition Of the Landslide Distribution Areamentioning

confidence: 99%

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Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

Marc

Meunier

Hovius

2017

Nat. Hazards Earth Syst. Sci.

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“…The richest data set has probably been produced for the Mw = 7.9 2008 Wenchuan earthquake in Sichuan Province, China, because this event had triggered an unprecedented number of landslides (N50,000, see, e.g. Gorum et al, 2011; and even about 200,000 landslides have been identified by Xu et al, 2014a). Coseismic landslides were estimated to have caused about 20,000 deaths, near one-third of the official estimate of 69,227 fatalities (Yin et al, 2009, with updated number of fatalities provided by Xu et al, 2014a).…”

Section: Introductionmentioning

confidence: 99%

Tien Shan Geohazards Database: Earthquakes and landslides

Havenith

Strom

Torgoev³

et al. 2015

Geomorphology

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“…Cloud cover was often concentrated around high elevation topography, leaving valley bottoms visible. Mapping of individual landslides therefore focused in areas proximal to the channel network and lower elevation slopes to survey for landslide dams, similar to those triggered by the 2008 Wenchuan earthquake (Cui et al, 2009;Xu et al, 2014). In order to rapidly map as large an area as possible, and due to cloud cover on higher ground, each landslide was initially marked as a single point at the toe, where the risk to infrastructure and likelihood of valley blocking was greatest.…”

Section: After 2 May: Landslide Assessment Using Optical Imagerymentioning

confidence: 99%

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

Williams

Rosser

Kincey

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides triggered by large earthquakes in mountainous regions contribute significantly to overall earthquake losses and pose a major secondary hazard that can persist for months or years. While scientific investigations of coseismic landsliding are increasingly common, there is no protocol for rapid (hours-to-days) humanitarian-facing landslide assessment and no published recognition of what is possible and what is useful to compile immediately after the event. Drawing on the 2015 M w 7.8 Gorkha earthquake in Nepal, we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated. We find that, at present, many forms of landslide assessment are too slow to generate relative to the speed of a humanitarian response, despite increasingly rapid access to high-quality imagery. Importantly, the value of information on landslides evolves rapidly as a disaster response develops, so identifying the purpose, timescales, and end users of a post-earthquake landslide assessment is essential to inform the approach taken. It is clear that discussions are needed on the form and timing of landslide assessments, and how best to present and share this information, before rather than after an earthquake strikes. In this paper, we share the lessons learned from the Gorkha earthquake, with the aim of informing the approach taken by scientists to understand the evolving landslide hazard in future events and the expectations of the humanitarian community involved in disaster response.

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Three (nearly) complete inventories of landslides triggered by the May 12, 2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis

Cited by 464 publications

References 77 publications

Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

Tien Shan Geohazards Database: Earthquakes and landslides

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

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