A Multiscale Exposure Model for Seismic Risk Assessment in Central Asia

Wieland, Marc; Pittore, Massimiliano; Parolai, Stefano; Begaliev, Ulugbek; Yasunov, Pulat; Tyagunov, Sergey; Moldobekov, Bolot; Saidiy, Saidislom; Ilyasov, Indalip; Abakanov, Tanatkan

doi:10.1785/0220140130

Cited by 27 publications

(28 citation statements)

References 17 publications

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“…The GEM Building Taxonomy is appropriate to consistently describe and classify buildings worldwide (Allen et al, 2015). It was already employed in several projects [(Global Earthquake Model (GEM), 2015; Wieland et al, 2015;Silva et al, 2018)]. The new developed paper form is also one of the few forms that allows for the collection of non-structural components seismic performance data.…”

Section: Improved Paper Form Based On the Gem Building Taxonomy V20mentioning

confidence: 99%

Damage Assessment on Buildings Following the 19th September 2017 Puebla, Mexico Earthquake

Roeslin

Quincy

García

2018

Front. Built Environ.

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Understanding seismic risk enables efficient resource allocation in the effort to increase the resilience of our cities and communities. Field reconnaissance and data collection following disasters document the damaging effects of earthquakes to enable lessons and wisdom to accumulate from past events. An important aim of such field data analysis is establishing a better understanding of building performance such as causes of building failures. These lessons provide essential basis to improve our design codes, develop regulations and policies, to increase building resilience by addressing the infrastructure vulnerability. Currently, to make use of the datasets from around the world, significant effort is required to decode the data which often have unique local and regional context and bias. The struggle begins at data collection where there is a lack of consistent methodology and definitions that can adequately cover the regional nuance. This manuscript proposes a new paper-based tool which addresses the need for a global yet detailed universal methodology for building damage assessment post-earthquakes. The new form is based on the GEM taxonomy v2.0 and the European Macroseismic Scale EMS-98. The recent Mexican earthquake from the 19 September 2017 led to significant building damage in the capital Mexico City and the state of Morelos. A team from New Zealand assessed damage throughout the capital and tested the new paper form in Calle La Morena. The street case study presents a novel visualization of the damage data and buildings characteristics which highlights the correlation between the damage and the building features. It is hoped that this kind of illustration will lead to better comprehension of the damage drivers.

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Section: Improved Paper Form Based On the Gem Building Taxonomy V20mentioning

confidence: 99%

Damage Assessment on Buildings Following the 19th September 2017 Puebla, Mexico Earthquake

Roeslin

Quincy

García

2018

Front. Built Environ.

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“…In the context of disaster risk management, multi-resolution is of high relevance, mainly due to the fact that exposed assets and/or damages are often described by data from different sources and at different scales. In previous work of the authors [27], for example, point-and path-wise visual screenings of single buildings are used in combination with large area remote sensing observations to derive a multi-scale exposure model. Due to the fact that exposure models often combine datasets from different sources at different scales, particular emphasis was given to implement independent matching procedures.…”

Section: Multi-representation Of Spatial Objectsmentioning

confidence: 99%

“…The building footprints have been imported from OpenStreetMap (OSM) by selecting 500 buildings from a German city. The building attributes were extracted from a database of buildings that were inspected by structural engineers by using the Remote Rapid Visual Screening (RRVS) procedure described in [27]. Further attributes were derived from census data.…”

Section: Scenario Ii: Real-world Changes and Object Life-cyclementioning

confidence: 99%

A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution

Wieland

Pittore

2017

IJGI

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Abstract:With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout the different phases of risk management reaching from pre-disaster mitigation to the response after an event and the long-term recovery of affected assets. Spatio-temporal changes need to be integrated into a sound conceptual and technological framework able to deal with data coming from different sources, at varying scales, and changing in space and time. Especially managing the information life-cycle, the integration of heterogeneous information and the distributed versioning and release of geospatial information are important topics that need to become essential parts of modern exposure modelling solutions. The main purpose of this study is to provide a conceptual and technological framework to tackle the requirements implied by disaster risk management for describing exposed assets in space and time. An information life-cycle management solution is proposed, based on a relational spatio-temporal database model coupled with Git and GeoGig repositories for distributed versioning. Two application scenarios focusing on the modelling of residential building stocks are presented to show the capabilities of the implemented solution. A prototype database model is shared on GitHub along with the necessary scenario data.

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“…At least 50% of a building should be visible in order to be assigned the label visible. A Remote Rapid Visual Screening (RRVS) desktop environment has been set up to perform the image analysis, as is described in [28]. In Table 5 the results of the detailed occlusion analysis are reported.…”

Section: Survey Coveragementioning

confidence: 99%

Improving Post-Earthquake Insurance Claim Management: A Novel Approach to Prioritize Geospatial Data Collection

Pittore

Wieland

Errize

et al. 2015

IJGI

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With a population exceeding 14 million and a GDP of more than 300 billion USD, Istanbul dominates the Turkish economy. Unfortunately, this concentration of social and economic assets is permanently threatened by potentially devastating earthquakes, given the city's close proximity to several well-known fault systems. As a measure to mitigate the consequences of such events, and to increase the resilience of the exposed communities, the Turkish Catastrophe Insurance Pool (TCIP) has been set up to provide affordable and reliable earthquake insurance to households all over the country. In the aftermath of a damaging event, especially in Istanbul, the operational capacity of TCIP will be seriously challenged by the high number of claims whose settlement would have to be swift and fair in order to kick-start the recovery process. In this paper we explore an integrated approach based on mobile mapping and ad hoc prioritization techniques to streamline the data collection and analysis process, with application to both the pre-event

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A Multiscale Exposure Model for Seismic Risk Assessment in Central Asia

Cited by 27 publications

References 17 publications

Damage Assessment on Buildings Following the 19th September 2017 Puebla, Mexico Earthquake

Damage Assessment on Buildings Following the 19th September 2017 Puebla, Mexico Earthquake

A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution

Improving Post-Earthquake Insurance Claim Management: A Novel Approach to Prioritize Geospatial Data Collection

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