A GIS-based seismic hazard, building vulnerability and human loss assessment for the earthquake scenario in Tabriz

Karimzadeh, Sadra; Miyajima, Masakatsu; Hassanzadeh, Reza; Amiraslanzadeh, Reza; Kamel, Batoul

doi:10.1016/j.soildyn.2014.06.026

Cited by 104 publications

(62 citation statements)

References 23 publications

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“…This system can report economic losses and the number of affected people and the risk level within 30 min of a significant earthquake (magnitude greater than 5.5). However, because of the spatial variability of the ground motion, the estimated disaster loss accuracy is reduced by inaccurate information on the shaking caused by the event (Karimzadeh et al, 2014). Similar global (regional) systems include the Global Disaster Alert and Coordination System (GDACS; http://www.gdacs.org) and the World Agency of Planetary Monitoring and Earthquake Risk Reduction (WAPMERR; http://www.wapmerr.org).…”

Section: Related Researchmentioning

confidence: 99%

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A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

Xu¹,

An²,

Nie³

2016

Nat. Hazards Earth Syst. Sci.

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Abstract. Improving earthquake disaster loss estimation speed and accuracy is one of the key factors in effective earthquake response and rescue. The presentation of exposure data by applying a dasymetric map approach has good potential for addressing this issue. With the support of 30 × 30 areal exposure data (population and building data in China), this paper presents a new earthquake disaster loss estimation method for emergency response situations. This method has two phases: a pre-earthquake phase and a co-earthquake phase. In the pre-earthquake phase, we precalculate the earthquake loss related to different seismic intensities and store them in a 30 × 30 grid format, which has several stages: determining the earthquake loss calculation factor, gridding damage probability matrices, calculating building damage and calculating human losses. Then, in the co-earthquake phase, there are two stages of estimating loss: generating a theoretical isoseismal map to depict the spatial distribution of the seismic intensity field; then, using the seismic intensity field to extract statistics of losses from the pre-calculated estimation data. Thus, the final loss estimation results are obtained. The method is validated by four actual earthquakes that occurred in China. The method not only significantly improves the speed and accuracy of loss estimation but also provides the spatial distribution of the losses, which will be effective in aiding earthquake emergency response and rescue. Additionally, related pre-calculated earthquake loss estimation data in China could serve to provide disaster risk analysis before earthquakes occur. Currently, the precalculated loss estimation data and the two-phase estimation method are used by the China Earthquake Administration.

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Section: Related Researchmentioning

confidence: 99%

“…Generally, because earthquake loss estimation is a complex issue, different methods and parameters are needed for different areas of the world (Karimzadeh et al, 2014). Several local earthquake loss methods have been developed.…”

Section: Related Researchmentioning

confidence: 99%

A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

Xu¹,

An²,

Nie³

2016

Nat. Hazards Earth Syst. Sci.

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“…For instance, when large areas are affected, it can be difficult to obtain information on the number of damaged buildings through ground inspection in the period immediately after an earthquake. People trapped in collapsed buildings can generally survive for only about 48 h after an earthquake, so a rapid assessment of the damage to buildings is necessary [1,2]. For a better post-earthquake response, immediate decisions must be taken based on the severity of damage to the buildings affected; however, blocked roads and insufficient information about the spatial distribution of damage can hinder rescue operations in the first hours after an earthquake.…”

Section: Introductionmentioning

confidence: 99%

“…In the last decade, increasing use has been made of remote-sensing data to assess the damage caused by earthquakes, floods, and other disasters [1][2][3][4]. In particular, space-borne remote sensors, including optical or synthetic aperture radar (SAR) devices, permit the inspection of large areas at costs that are affordable for various institutes and organizations.…”

Section: Introductionmentioning

confidence: 99%

Building Damage Assessment Using Multisensor Dual-Polarized Synthetic Aperture Radar Data for the 2016 M 6.2 Amatrice Earthquake, Italy

Karimzadeh

Mastuoka

2017

Remote Sensing

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Abstract:On 24 August 2016, the M 6.2 Amatrice earthquake struck central Italy, well-known as a seismically active region, causing considerable damage to buildings in the town of Amatrice and the surrounding area. Damage from this earthquake was assessed quantitatively by means of multitemporal synthetic aperture radar (SAR) coherence and SAR intensity methods using dual-polarized SAR data obtained from the Sentinel-1 (VV, VH) and ALOS-2 (HH, HV) satellites. We developed linear discriminant functions based on three items: (1) the differential coherence values; (2) the differential backscattering intensity values of pre-and post-event images; and (3) a binary damage map of the optical pre-and post-event imagery. The accuracy of the proposed model was 84% for the Sentinel-1 data and 76% for the ALOS-2 data. The damage proxy maps deduced from the linear discriminant functions can be useful in the parcel-by-parcel assessment of building damage and development of spatial models for the allocation of urban search and rescue operations.

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“…The main difference between this methodology and the aforementioned is that the latter is far more customizable and versatile, as the layers of input information can be adjusted to the user's requirements, data availability and desired outcome. Such methodologies have been applied in various cities around the world such as Barcelona (Lantada et al, 2003), Brussels (Petermans et al, 2006), Thessaloniki (Pitilakis et al, 2006), Grenoble (Gueguen et al, 2007), Chania (Sarris et al, 2010) and Tabriz (Karimzadeh et al, 2014). Justification for this selection will be provided in the Materials and Methods chapter.…”

Section: Introductionmentioning

confidence: 99%

Seismic Risk Assessment in the Attica Basin

et al. 2017

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A GIS-based seismic hazard, building vulnerability and human loss assessment for the earthquake scenario in Tabriz

Cited by 104 publications

References 23 publications

A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

Building Damage Assessment Using Multisensor Dual-Polarized Synthetic Aperture Radar Data for the 2016 M 6.2 Amatrice Earthquake, Italy

Seismic Risk Assessment in the Attica Basin

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