Where to go first: prioritization of damaged areas for allocation of Urban Search and Rescue (USAR) operations (PI-USAR model)

Abstract

This paper presents the development of a spatial model for the allocation of the Urban Search and Rescue (USAR) operation by computing the priority index of damaged areas (PI-USAR model). The relevant prioritization criteria were identified through a literature review and interviews with 30 disaster managers. The relative importance of these criteria was computed as weights using an analytic hierarchy process (AHP) method; the criteria were combined based on AHP rules and spatial multi-criteria decision-making analysis in geographic information system (GIS). The PI-USAR model was applied in the case study area of the Bam city in Iran and a priority map was produced indicating four highly prioritized areas. The model was validated by comparing the obtained priority map with the actual priority map (APM) using fuzzy inference system and relative operating characteristic methods. The result suggested a good fit between the APM and the model's output. Sensitivity analyses were performed using the map removal and the single parameter methods. With the uncertainties and complexities that are inherent to the spatial data, spatial modelling and the earthquake phenomenon itself, the PI-USAR model offers some utility to disaster managers in understanding the significance of each criterion in the decision-making process and in identifying the highly prioritized areas for the allocation of USAR operations. However, its utility is best exploited in conjunction with other complementary sources of field data based on the immediate post-disaster situation.

Advancements toward autonomous access hole detection for urban search and rescue

“…Quickly locating regions likely to contain voids is crucial in order to concentrate available rescue personnel where victims may be entrapped [12]. Using information gathered from the literature and interviews of disaster managers, a framework for the prioritization of disaster search areas was developed [13].…”

Designing visualization and interaction for industrial control rooms of the future

“…To get a decent SA, the user would need to click through the tabs in the menu in the right corner of the interface. Second, the map taking the central place in the interface was impractical mostly because it is hard to compare and prioritize one mission over another using a map whereas prioritizing is one of the critical tasks in SAR operators' work [101,184]. Therefore, it was decided to improve the interface so that it would: 1) give 4.…”

New approaches to modelling of local seismic amplification susceptibility using direct characteristics of influencing criteria: case study of Bam City, Iran

“…The potential criteria influencing local seismic amplification susceptibility were determined through a critical review of literature. By reviewing documents on earthquake engineering, seismology, geology, tectonic and structural engineering, geomorphology, and seismic microzonation reports and guidelines (Fäh et al, 1997;Ding et al, 2004;Molina et al, 2010;Mundepi et al, 2010;Marulanda et al, 2012;Hassanzadeh et al, 2013;FEMA, 2014;Fraume et al, 2014;Grelle et al, 2014Grelle et al, , 2016SM Working Group, 2015;Rehman et al, 2016;Nwe and Tun, 2016;GEM, 2017;CAPRA, 2017;Michel et al, 2017;Trifunac, 2016;Hassanzadeh and Nedovic-Budic, 2016), in total 14 influencing criteria were identified (Table 1).…”

“…The MERM (2003) microzonation manual sets different criteria affecting the amplitude and duration of ground shaking at a specific site. These include the magnitude of the earthquake, focal point and depth of the earthquake, directivity of the energy released, distance of rupture from the site, geological condition from the site to the location of the earthquake, local geological settings, geotechnical properties, and topographical condition of the site (SM Working Group, 2015;Boore, 2003;Hassanzadeh et al, 2013;Castelli et al, 2016a, b).…”