Skip to main content
SpringerLink
Log in

An auxiliary framework to facilitate earthquake search and rescue operations in urban regions

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Here, we propose an auxiliary earthquake emergency framework to facilitate a post-earthquake rapid response. Searching through the rubble of collapsed buildings is essentially a race against time, as time is highly correlated with the chances of trapped victims surviving. The framework here is centered on full GIS integration and smartwatch (SW) for transferring victims’ vital data for search and rescue (SAR) operations considering the damage to the road network due to direct earthquake implications. The framework has two parts time-wise: pre- and post-earthquake. The first part assesses the initial situation under different earthquake scenarios, which calculates service areas for emergency rescue centers under different earthquake scenarios considering road blockages. Following an earthquake, the second part prioritizes victims and identifies critical rescue areas using an SW and initial assessments. The victims’ accessibility, health condition, and injury risk are the criteria used to determine victims’ rescue priority. The developed framework is then employed in an urban region for different earthquake scenarios. From a road blockage point of view, the critical areas are then recognized. The framework relies on GIS and SW technology for data transfer, but potential failures and challenges in post-earthquake scenarios, data availability, quality, timeliness, and ethical considerations like equity, cultural sensitivities, and privacy need to be addressed. Considering the golden rescue time, by integrating the latest technologies into management applications, the study’s results can help emergency first responders make rapid and efficient decisions and better allocate medical and rescue resources just after an earthquake, reducing earthquake losses and saving more human lives. Moreover, it can provide insight into the initial road network situation following different earthquake scenarios for first responders to estimate the road network’s initial situation; thus, they can operate better in real emergencies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Data availability

The results and data of the study here are available from the authors upon reasonable request and with permission from http://library.aut.ac.ir. Please contact lib_office@aut.ac.ir.

References

  • Argyroudis S, Pitilakis K, Anastasiadis A (2005) Roadway network seismic risk analysis in urban areas: The case of Thessaloniki-Greece. Proceedings of the Geoline Conference, Lyon, France

  • Badhrudeen M, Derrible S, Verma T, Kermanshah A, Furno A (2022) A geometric classification of World Urban Road Networks. Urban Sci 6(1):11

    Article  Google Scholar 

  • Baker JW (2011) Conditional mean spectrum: Tool for ground-motion selection. J Struct Eng 137(3):322–331

    Article  Google Scholar 

  • Behnam B (2017) Post-earthquake Fire Analysis in Urban structures: Risk Management Strategies, 1 edn. CRC Press, Taylor & Francis Group

  • Benson M, Koenig KL, Schultz CH (1996) Disaster triage: START, then SAVE—a new method of dynamic triage for victims of a catastrophic earthquake. Prehosp Disaster Med 11(2):117–124

    Article  Google Scholar 

  • Bhushan N, Rai K (2007) Strategic decision making: applying the analytic hierarchy process. Springer Science & Business Media

  • Blakeley CJ (2004) Major incident management system. Emerg Med J 21(1):126–126. https://emj.bmj.com/content/emermed/21/1/126.2.full.pdf

    Google Scholar 

  • Carter WN (2008) Disaster management: A disaster manager’s handbook

  • Cecchinato ME (2018) Communicating in a multi-role, multi-device, multi-channel world: how knowledge workers manage work-home boundaries UCL (University College London)]

  • Cetin M (2019) The effect of urban planning on urban formations determining bioclimatic comfort area’s effect using satellitia imagines on air quality: a case study of Bursa city. Air Qual Atmos Health 12(10):1237–1249

    Article  CAS  Google Scholar 

  • Chan TC, Killeen J, Griswold W, Lenert L (2004) Information technology and emergency medical care during disasters. Acad Emerg Med 11(11):1229–1236

    Article  Google Scholar 

  • Chen J, Yang S, Li H, Zhang B, Lv J (2013) Research on geographical environment unit division based on the method of natural breaks (Jenks). Int Arch Photogramm Remote Sens Spat Inf Sci 3:47–50

    Article  Google Scholar 

  • Coburn, A., & Spence, R. (2003). Earthquake protection. John Wiley & Sons.

  • Coetzee C, Van Niekerk D (2012) Tracking the evolution of the disaster management cycle: a general system theory approach. Jàmbá: J Disaster Risk Stud 4(1):1–9

    Article  Google Scholar 

  • Cova TJ (1999) GIS in emergency management. Geographical Inform Syst 2(12):845–858

    Google Scholar 

  • Etemadfard H, Moradi M (2021) Estimating the Damage of Earthquake Using RADIUS Model (Case Study: Tehran). Resilient Design and Construction of Geostructures Against Natural Hazards: Proceedings of the 6th GeoChina International Conference on Civil & Transportation Infrastructures: From Engineering to Smart & Green Life Cycle Solutions–Nanchang, China, 2021 6

  • Farahani S, Behnam B, Tahershamsi A (2020) Macrozonation of seismic transient ground displacement and Permanent Ground deformation of Iran. Nat Hazards Earth Syst Sci 2020(1–20). https://doi.org/10.5194/nhess-2020-48

  • Farahani S, Shojaeian A, Behnam B, Roohi M (2023) Probabilistic seismic multi-hazard risk and restoration modeling for resilience-informed decision making in Railway Networks. Sustainable Resilient Infrastructure, 1–22

  • Fiedrich F, Gehbauer F, Rickers U (2000) Optimized resource allocation for emergency response after earthquake disasters. Saf Sci 35(1–3):41–57

    Article  Google Scholar 

  • Graser A, Straub M, Dragaschnig M (2015) Is OSM good enough for vehicle routing? A study comparing street networks in Vienna. Progress in location-based services 2014. Springer, pp 3–17

  • Hooshangi N, Gharakhanlou M, N., Alesheikh AA (2021) Determining the number of rescuers in post-earthquake rescue operations using the agent-based modeling (case study: Tabriz city). 1st international conference and 2nd national conference on Modern Geomatics Technologies and Applications, Undefined, Tabriz

  • Hossain M, Gadagamma C, Bhattacharya Y, Numada M, Morimura N, Meguro K (2020) Integration of smart watch and Geographic Information System (GIS) to identify post-earthquake critical rescue area part. I. Development of the system. Progress Disaster Sci 7:100116

    Article  Google Scholar 

  • Jenelius E, Mattsson L-G (2015) Road network vulnerability analysis: conceptualization, implementation and application. Comput Environ Urban Syst 49:136–147

    Article  Google Scholar 

  • JICA C (2000) The study on seismic microzoning of the Greater Tehran Area in the Islamic Republic of Iran. Pac Consultants Int Rep OYO Cooperation Japan, 291–390

  • Johnson R (2000) GIS technology for disasters and emergency management

  • Kai N, Yao-ting Z, Yue-peng M (2014) Shortest path analysis based on Dijkstra’s algorithm in emergency response system. TELKOMNIKA Indonesian J Electr Eng 12(5):3476–3482

    Google Scholar 

  • Karaman H, Erden T (2014) Net earthquake hazard and elements at risk (NEaR) map creation for city of Istanbul via spatial multi-criteria decision analysis. Nat Hazards 73:685–709

    Article  Google Scholar 

  • Kohrangi M, Bazzurro P, Vamvatsikos D (2021a) Seismic risk and loss estimation for the building stock in Isfahan. Part I: exposure and vulnerability. Bull Earthq Eng 19(4):1709–1737

    Article  Google Scholar 

  • Kohrangi M, Bazzurro P, Vamvatsikos D (2021b) Seismic risk and loss estimation for the building stock in Isfahan: part II—hazard analysis and risk assessment. Bull Earthq Eng 19(4):1739–1763

    Article  Google Scholar 

  • Leitner G, Ahlström D, Hitz M (2007) Usability of mobile computing in emergency response systems–Lessons learned and future directions. Symposium of the Austrian HCI and Usability Engineering Group

  • Li Y (2011) A survey on communication networks in emergency warning systems

  • Li W, Batty M, Goodchild MF (2020) Real-time GIS for smart cities, vol 34. Taylor & Francis, pp 311–324

  • Liu Y, Yuan Y, Shen J, Gao W (2021) Emergency response facility location in transportation networks: a literature review. J Traffic Transp Eng (English Edition) 8(2):153–169

    Article  Google Scholar 

  • Malczewski J, Rinner C (2015) Multicriteria decision analysis in geographic information science, vol 1. Springer

  • Mohanty WK, Walling MY, Nath SK, Pal I (2007) First order seismic microzonation of Delhi, India using geographic information system (GIS). Nat Hazards 40(2):245–260

    Article  Google Scholar 

  • Mouroux P, Bertrand E, Bour M, Le Brun B, Depinois S, Masure P (2004) The European RISK-UE project: an advanced approach to earthquake risk scenarios. Proc. of the 13th World Conference on Earthquake Engineering

  • Nazmfar H, Saredeh A, Eshgi A, Feizizadeh B (2019) Vulnerability evaluation of urban buildings to various earthquake intensities: a case study of the municipal zone 9 of Tehran. Hum Ecol Risk Assessment: Int J 25(1–2):455–474

    Article  CAS  Google Scholar 

  • Nyimbili PH, Erden T, Karaman H (2018) Integration of GIS, AHP and TOPSIS for earthquake hazard analysis. Nat Hazards 92(3):1523–1546

    Article  Google Scholar 

  • Palen L (2008) Online social media in crisis events. Educause Q 31(3):76–78

    Google Scholar 

  • Pan M, Chen C, Yin X, Huang Z (2021) UAV-Aided Emergency Environmental Monitoring in Infrastructure-less areas: LoRa Mesh networking Approach. IEEE Internet Things J 9(4):2918–2932

    Article  Google Scholar 

  • Panahi M, Rezaie F, Meshkani S (2014) Seismic vulnerability assessment of school buildings in Tehran city based on AHP and GIS. Nat Hazards Earth Syst Sci 14(4):969–979

    Article  Google Scholar 

  • Peng D, Gatschke J (2021) • Statista-The Statistics Portal for Market Data, Market Research and Market Studies. Statista-The Statistics Portal for Market Data, Market Research and Market Studies, www.statista.com

  • Pitilakis KD, Kakderi K (2011) Seismic risk assessment and management of lifelines, utilities and infrastructures. 5th International Conference on Earthquake Geotechnical Engineering

  • Poteyeva M, Denver M, Barsky LE, Aguirre BE (2007) Search and rescue activities in disasters. Handbook of disaster research. Springer, pp 200–216

  • Qin X (2013) Local ideal point method for GIS-based multicriteria analysis. A case study in London, Ontario

    Google Scholar 

  • Rom A, Kelman I (2020) Search without rescue? Evaluating the international search and rescue response to earthquake disasters. BMJ Global Health, 5(12), e002398

  • Shoghi Kalkhoran MH, Izadkhah O, Y., Hosseini M (2020) Upgrading the evaluation methods of influential buildings for post-earthquake emergency response. Bull Earthq Sci Eng 7(2):177–192

    Google Scholar 

  • Statheropoulos M, Agapiou A, Pallis GC, Mikedi K, Karma S, Vamvakari J, Dandoulaki M, Andritsos F, Thomas C (2015) Factors that affect rescue time in urban search and rescue (USAR) operations. Nat Hazards 75(1):57–69

    Article  Google Scholar 

  • Statistics IC (2006) o. Census of 2006

  • Toma-Danila D (2018) A GIS framework for evaluating the implications of urban road network failure due to earthquakes: Bucharest (Romania) case study. Nat Hazards 93(1):97–111

    Article  Google Scholar 

  • Toma-Danila D, Armas I, Tiganescu A (2020) Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania. Nat Hazards Earth Syst Sci 20(5):1421–1439

    Article  Google Scholar 

  • Tong Q, Yang M, Zinetullina A (2020) A dynamic bayesian network-based approach to resilience assessment of engineered systems. J Loss Prev Process Ind 65:104152

    Article  Google Scholar 

  • Ural S, Hussain E, Kim K, Fu C-S, Shan J (2011) Building extraction and rubble mapping for city port-Au-Prince post-2010 earthquake with GeoEye-1 imagery and lidar data. Photogrammetric Eng Remote Sens 77(10):1011–1023

    Article  Google Scholar 

  • Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169(1):1–29

    Article  Google Scholar 

  • Van Tilburg C (2017) First report of using portable unmanned aircraft systems (drones) for search and rescue. Wilderness Environ Med 28(2):116–118

    Article  Google Scholar 

  • Wang J, Cai J, Yue X, Suresh NC (2021) Pre-positioning and real-time disaster response operations: optimization with mobile phone location data. Transp Res E 150:102344

    Article  Google Scholar 

  • Wong J, Robinson C (2004) Urban search and rescue technology needs: identification of needs. Fed Emerg Manage Agency (FEMA) Natl Inst Justice (NIJ) Doc 207771:20

    Google Scholar 

  • Yang M, Khan FI, Sadiq R (2011) Prioritization of environmental issues in offshore oil and gas operations: a hybrid approach using fuzzy inference system and fuzzy analytic hierarchy process. Process Saf Environ Prot 89(1):22–34

    Article  CAS  Google Scholar 

  • Yang Y, Ng ST, Dao J, Zhou S, Xu FJ, Xu X, Zhou Z (2021) BIM-GIS-DCEs enabled vulnerability assessment of interdependent infrastructures–A case of stormwater drainage-building-road transport Nexus in urban flooding. Autom Constr 125:103626

    Article  Google Scholar 

  • Yariyan P, Zabihi H, Wolf ID, Karami M, Amiriyan S (2020) Earthquake risk assessment using an integrated fuzzy Analytic Hierarchy process with Artificial neural networks based on GIS: a case study of Sanandaj in Iran. Int J Disaster Risk Reduct 50:101705

    Article  Google Scholar 

  • Yücel E, Salman FS, Arsik I (2018) Improving post-disaster road network accessibility by strengthening links against failures. Eur J Oper Res 269(2):406–422

    Article  Google Scholar 

  • Zanini MA, Faleschini F, Zampieri P, Pellegrino C, Gecchele G, Gastaldi M, Rossi R (2017) Post-quake urban road network functionality assessment for seismic emergency management in historical centres. Struct Infrastruct Eng 13(9):1117–1129

    Article  Google Scholar 

  • Zhu Y, Li N (2021) Virtual and augmented reality technologies for emergency management in the built environments: a state-of-the-art review. J Saf Sci Resil 2(1):1–10

    Google Scholar 

  • Zolfaghari M, Mousavi M (2013) Development of a probabilistic model for human loss estimation due to damage based on the buildings’ destruction mechanism Ministry of Science, Research and Technology -. Khajeh Nasireddin Tusi University of Technology - Faculty of Civil Engineering]

Download references

Author information

Authors and Affiliations

  1. School of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran

    Maedeh Haghbin Yousefi, Behrouz Behnam & Saeideh Farahani

Authors
  1. Maedeh Haghbin Yousefi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Behrouz Behnam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Saeideh Farahani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Behrouz Behnam.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yousefi, M.H., Behnam, B. & Farahani, S. An auxiliary framework to facilitate earthquake search and rescue operations in urban regions. Nat Hazards (2024). https://doi.org/10.1007/s11069-024-06619-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11069-024-06619-9

Keywords

Search

Navigation