Active and passive remote sensing for supporting the evaluation of the urban seismic vulnerability

Borfecchia, Flavio; Pollino, Maurizio; Cecco, L. De; Lugari, Alessandro; Martini, S.; Porta, Luigi La; Ristoratore, Elisabetta; Pascale, Carmine; Giustino, D.

doi:10.5721/itjrs201042310

Cited by 46 publications

(36 citation statements)

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“…Recently, apart from applications in post-earthquake impact assessments [24][25][26][27][28][29][30][31], many studies have addressed the application of high-resolution remote sensing technology to pre-earthquake exposure, vulnerability, and risk. In these pre-earthquake studies, the and/or -relevant issues (see Equation (1)) of various buildings were widely discussed, including various optical imagery-based specific analyses (Table 1) [32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50], some attempts at fusing optical imagery and LiDAR or SAR data [51][52][53] to help extract the heights of buildings, and several comprehensive reviews [54][55][56][57]. Table 1.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

Zhang

et al. 2015

Remote Sensing

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Rapid socioeconomic development in earthquake-prone areas can cause rapid changes in seismic loss risks. These changes make it difficult to ensure that risk reduction strategies are realistic, practical and effective over time. To overcome this difficulty, ongoing changes in risk should be captured timely, definitively, and accurately and then specific and well-timed adjustments of the relevant strategies should be made. However, methods for rapidly characterizing such seismic disaster risks over a large area have not been sufficiently developed. By focusing on building loss risks, this paper presents the development of an integrated method that combines remote sensing data and local OPEN ACCESSRemote Sens. 2015, 7 2544 knowledge to resolve this problem. This method includes two key interdependent steps.(1) To extract the heights and footprint areas of a large number of buildings accurately and quickly from single high-resolution optical remote sensing images; (2) To estimate the floor areas, identify structural types, develop damage probability matrixes, and determine economic parameters for calculating monetary losses due to seismic damage to the buildings by reviewing building-relevant local knowledge based on these two parameters (i.e., the building heights and footprint areas). This method is demonstrated in the Tangshan area of China. Based on the integrated method, the total floor area of the residential and public office buildings in central Tangshan in 2009 was 3.99% lower than the corresponding area number obtained by a conventional earthquake loss estimation project. Our field-based verification indicated that the mean relative error of the method for estimating the floor areas of the assessed buildings was 2.99%. A simulation of the impacts of the 1976 Ms 7.8 Tangshan earthquake using this method indicated that the total damaged floor area of the residential and public office buildings and the associated direct monetary loses in the study area could have been 8.00 and 28.73 times greater, respectively, than in 1976 if this earthquake had recurred in 2009, which is a strong warning to the local people regarding the increasing challenges they may face.

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Section: Introductionmentioning

confidence: 99%

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

Zhang

et al. 2015

Remote Sensing

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“…From an operational point of view, recent major disasters (e.g. 2010 Haiti earthquake, 2010 Pakistan Flood, 2011 Japan tsunami and 2012 Italy earthquake) [Ajmar et al, 2008[Ajmar et al, , 2011Mahendra et al, 2010;Baiocchi et al, 2012;Bhattacharya et al, 2013] clearly demonstrated the potential role of geomatics in supporting emergency response and recovery, as already depicted in different papers published by EuJRS [Ajmar et al, 2008[Ajmar et al, , 2011[Ajmar et al, , 2012Borfecchia et al, 2010;Dall'Osso et al, 2010;Pignatelli et al, 2010;Rivolta et al, 2010;Baiocchi et al, 2012;Laneve et al, 2012;Perez et al, 2012]. Remote sensing based analyses are nowadays frequently adopted to support both decision makers and responders in the field during disaster management activities, as clearly pointed out by the United Nations in the 2011 humanitarian appeal: " […] Remote sensing in the hours and days after the Haiti earthquake yielded estimates of numbers of severely affected people that stood the test of time and allowed an unusually rapid flash appeal.…”

Section: Introductionmentioning

confidence: 89%

New perspectives in emergency mapping

Boccardo

2013

European Journal of Remote Sensing

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In recent years, growing attention is paid to remote sensing when used for disaster management applications. This is essentially due to the large variety of remotely acquired imagery available for the extraction of geometric and thematic features in order to map, delineate and grade natural disasters impacts. Another key point is the quick availability of those images in rapid mapping procedures in order to deliver the data (reference and thematic) to concerned users. This paper briefly describes the current state-of-the-art of remote sensing techniques usage in emergency mapping, paying particular attention, in the second part, to the GIO-EMS new operational service delivered by the European Commission.Keywords: Disaster management, emergency mapping, remote sensing, spatial data infrastructure (SDI), data model, image processing. General remarksStarting with this editorial, the Italian Society of Remote Sensing (AIT) aims to favour an International debate related to the main geomatics (with particular attention to remote sensing) applications. The short papers that will be published in the next European Journal of Remote Sensing (EuJRS) issues are conceived to deliver basic and operational information to all EuJRS readers on different topics, highlighting potentialities (also in terms of possible financing coming from National and International opportunities) of these new application fields. This first paper is related to geomatics and emergency management; applications on health, weather, atmosphere, climate change, water resources, energy, geology, cryosphere, forest, natural ecosystems, biodiversity, land cover, coastal, ocean and transportation, infomobility and Intelligent Transport Systems (ITS), will follow in the next months.

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“…For instance, Taubenböck (2015) characterize the built environment with remote sensing data and retrieve specific fragility functions or damage probability matrices, respectively, for designated building types. In contrast to that, e.g., Borfecchia et al (2010), and Geiß et al (2014Geiß et al ( , 2015 combine limited in situ ground truth building inventory data with features from remote sensing and use techniques of statistical inference for a complete labelling of the residual building inventory according to relevant vulnerability levels. Similar methodological principles were exploited by Wieland et al (2012), Pittore and Wieland (2013), and Geiß et al (2016) to assess seismic vulnerability on an aggregated spatial level to allow for covering larger areas.…”

Section: Third Phase: Methodological Elaboration Of Specific Aspects mentioning

confidence: 99%

One step back for a leap forward: toward operational measurements of elements at risk

Geiß

Taubenböck

2017

Nat Hazards

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Active and passive remote sensing for supporting the evaluation of the urban seismic vulnerability

Cited by 46 publications

References 10 publications

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

New perspectives in emergency mapping

One step back for a leap forward: toward operational measurements of elements at risk

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