Assessing the Blockage Risk of Disaster-Relief Road for a Large-Scale Earthquake

Lo, I-Tien; Lin, Ching‐Yuan; Yang, Cheng-Tao; Chuang, Ying-Ji; Lin, Cheng

doi:10.1007/s12205-020-0340-7

Cited by 10 publications

(19 citation statements)

References 27 publications

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“…Improving modeling approaches for assessing the potential impacts of earthquakes and landslides on critical infrastructure is an important area of current research. This work joins a growing body of literature (Aghababaei et al, 2020b; Emberson et al, 2020; Koks et al, 2019; Lo et al, 2020; Ono and Hibi, 2020; Robinson et al, 2018) that integrates hazard-modeling and road network data to better understand a variety of risks posed to road networks. Yet, to our knowledge, no previous studies have translated a global near-real-time landslide model into estimates of infrastructure impacts.…”

Section: Discussionmentioning

confidence: 94%

A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides

2021

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Coseismic landslides are a major source of transportation disruption in mountainous areas, but few approaches exist for rapidly estimating impacts to road networks. We develop a model that links the U.S. Geological Survey (USGS) near-real-time earthquake-triggered landslide hazard model with Open Street Map (OSM) road network data to rapidly estimate segment-level obstruction risk following major earthquake activity worldwide. To train and validate the model, we process OSM data for 15 historical earthquakes and calculate the average segment-level landslide hazard from the USGS model for each event. We then fit a multivariate adaptive regression spline model for the probability of road obstruction as a function of road segment length and landslide hazard, using a training and validation dataset derived from the intersections of road networks with earthquake-triggered landslide inventories. The resulting probabilistic model is well calibrated across a range of earthquake events, with estimated obstruction probabilities matching the relative frequency of potential road obstructions. The model runs quickly and is capable of producing road segment-level obstruction estimates within minutes to hours of a major earthquake. However, in near-real-time application, the accuracy of the obstruction estimates will be dependent on the quality of the ShakeMap shaking estimates, which often improves with time as more information becomes available after the earthquake. By providing a rapid first-order translation of landslide hazard into potential infrastructure impacts, this model helps provide emergency responders with tangible information on initial areas of concern.

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Section: Discussionmentioning

confidence: 94%

A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides

2021

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“…The concept of a seismic hazard factor is based on the study of elements common to both BE and OS, i.e., the seismological and seismogenic characteristics [23,24] and the geological characteristics of the soils [25].…”

Section: Towards a Seismic Risk Assessment Of Open Spacesmentioning

confidence: 99%

“…Others recognize the role of the OS width for the estimation of the potential pedestrian evacuation flow [51,58,62], sometimes also considering the interfering obstacles (e.g., urban furniture), that could limit the effective width of the paths and consequently the evacuation speed [29,39,54] (see also Section 3.2.2), or the sudden narrowing of the OS [45,57]. The literature shows how the OS's length has a relation to the access and smooth movement of the emergency services, evaluating both the ante-and post-event scenarios [24,46], and with the time required for pedestrian evacuees to reach a safe destination [12,29,50]. Moreover, it is also possible to use the overall OS length to compare different urban areas, using the street network density index, defined as the ratio between the total length of streets within a sector and the sector's overall area [55].…”

Section: Morpho-typological Characteristicsmentioning

confidence: 99%

“…The maintenance (e.g., cracked roads) affects the safety of the evacuation [38], influencing people's speed [55] and the potential of pedestrian injuries during the escape [29]. After the event, the condition of the pavements can change due to the fall of elements related to the context [54,55] and the soil liquefaction phenomena, which can cause a permanent ground deformation [24,44,56]. These events can damage the pavements, resulting in a slowdown of the emergency operations and/or an interruption of a part of the OS network [59].…”

Section: Constructive Characteristicsmentioning

confidence: 99%

“…The seismicity is among the pivotal factors that influence the seismic local vulnerability of the BE and the OSs [38,45,53], primarily important for a complete evaluation of the vulnerability of LSs identified as evacuation paths [9] or ASs as safe areas [61]. A seismic hazard could be evaluated qualitatively by adopting the values of the seismic zonation, if available, or quantitatively using the peak ground acceleration [22][23][24]29,40,43,48,63].…”

Section: Characteristics Of Contextmentioning

confidence: 99%

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Factors Influencing the Intrinsic Seismic Risk of Open Spaces in Existing Built Environments: A Systematic Review

et al. 2021

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Open spaces (OSs), such as streets, squares, and green areas, in existing built environments (BEs) are key places in disaster risk management. The seismic risk in the OSs is strictly related to BE characteristics. Scientific literature mainly focuses on extrinsic factors affecting risk, which are related to BE elements on the OSs frontier (e.g., buildings) that could cause indirect effects on the OSs. Conversely, just a few risk assessment studies consider intrinsic factors, which are related to OS elements that could suffer direct effects. Moreover, synoptic studies on such factors are still missing. Through literature-based research, the paper identifies specific factors influencing seismic risk in the OSs, focusing notably on intrinsic vulnerability. The literature review methodology includes both a systematic review from Scopus databases and a traditional bibliographic search using snowball analysis. According to the final selected papers, risk factors are classified into five categories of OS characteristics: morpho-typology; physical; construction; use and users; and context. Statistical analysis of the categories’ recurrence in the final papers firstly allows current literature gaps to be defined. The results also provide a preliminary OSs risk index weighting each category in terms of such recurrences, thus representing a first useful step to support non-expert stakeholders in a preliminary assessment of priorities to define the seismic risk of Oss.

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Street-block collapsed buildings assessment: A case study of Banqiao District, New Taipei City

Lin

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et al. 2020

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Assessing the Blockage Risk of Disaster-Relief Road for a Large-Scale Earthquake

Cited by 10 publications

References 27 publications

A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides

A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides

Factors Influencing the Intrinsic Seismic Risk of Open Spaces in Existing Built Environments: A Systematic Review

Street-block collapsed buildings assessment: A case study of Banqiao District, New Taipei City

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