Natural Hazards

, Volume 90, Issue 3, pp 1485–1507 | Cite as

Spatial decision support systems (SDSS) and software applications for earthquake disaster management with special reference to Turkey

  • Penjani Hopkins Nyimbili
  • Turan ErdenEmail author
Review Article


Earthquake disasters pose significant risks and remain a serious threat for millions of people causing a devastating loss of lives and damage to the infrastructure resulting in huge socio-economic and environmental losses in many regions worldwide. In the last decade, recent major and catastrophic earthquake occurrences have underscored the critical importance of the increasing need for effective disaster management in considering appropriate planning, responses and strategies, with time and complex decision-making, being vital across the four phases of the disaster and emergency management (DEM) life cycle-preparedness, mitigation, response and recovery. In this paper, selected spatial decision support systems (SDSSs) related to the geographic information system-based applications in earthquake DEM, ranging from scenario or simulation based, early warning and rapid response and loss estimation systems, have been analysed. These have been generalised into global systems to include HAZTURK, QLARM, SELENA, DBELA, CATS, PAGER and regional and local systems comprising of ELER, HAZUS-MH, KOERILoss, MAEviz, EQRM and LNECLOSS. From the analysis of SDSS usage worldwide, but especially in Turkey, HAZTURK has been recommended for implementation of earthquake risk and loss estimation studies in Turkey based on its significant comparative advantages over other SDSSs and the suitability and applicability to the local conditions of Turkey, which have been discussed in this research. Key challenges to be addressed, ranging from issues in spatial data acquisition, quality, interoperability, data exchange and lack of coordination among associated institutions involved in earthquake DEM and recommendations, as well as future functional improvements and developments of HAZTURK software, have been characterised for successful implementation in Turkey.


Earthquake Disaster and emergency management Geographic information systems (GIS) Spatial decision support systems (SDSS) Multi-criteria decision-making (MCDM) 


  1. Anderson E (2008) Central American Probabilistic Risk Assessment (CAPRA): objectives, applications and potential benefits of an open access architecture. Global Risk Forum, GRF Davos, DavosGoogle Scholar
  2. Ansal A, Akinci A, Cultrera G, Erdik M, Pessina V, Tönük G, Ameri G (2009) Loss estimation in Istanbul based on deterministic earthquake scenarios of the Marmara Sea region (Turkey). Soil Dyn Earthq Eng 29(4):699–709CrossRefGoogle Scholar
  3. Armaş I, Rădulian M (2014) Spatial multi-criteria risk assessment of earthquakes from Bucharest, Romania. In: Dan MB et al (eds) Earthquake hazard impact and urban planning. Springer, Berlin, pp 127–149CrossRefGoogle Scholar
  4. Atakan K, Ojeda A, Meghraoui M, Barka AA, Erdik M, Bodare A (2002) Seismic hazard in Istanbul following the 17 August 1999 Izmit and 12 November 1999 Düzce earthquakes. Bull Seismol Soc Am 92(1):466–482CrossRefGoogle Scholar
  5. Bal IE, Crowley H, Pinho R (2008) Displacement-based earthquake loss assessment for an earthquake scenario in Istanbul. J Earthq Eng 12(S2):12–22CrossRefGoogle Scholar
  6. Bilham R (2009) The seismic future of cities. Bull Earthq Eng 7(4):839–887CrossRefGoogle Scholar
  7. Bıyıkoglu H, Turkel V, Seralioglu MS (2012) Istanbul natural gas network risk mitigation system. Proceeding of the world gas conference, Kuala LumpurGoogle Scholar
  8. Bommer JJ, Pinho R, Crowley H (2006) Using a displacement-based approach for earthquake loss estimation. In: Advances in earthquake engineering for urban risk reduction. Springer, Berlin, pp 489–504Google Scholar
  9. Böse M (2006) Earthquake early warning for Istanbul using artificial neural networks. Doctoral dissertation, Karlsruhe Univ., Diss.Google Scholar
  10. CEDIM (2011) Forensic earthquake analysis group reports 1–4–2011 van earthquake, Karlsruhe, GermanyGoogle Scholar
  11. Chang KT, Wan S, Lei TC (2010) Development of a spatial decision support system for monitoring earthquake-induced landslides based on aerial photographs and the finite element method. Int J Appl Earth Obs Geoinf 12(6):448–456CrossRefGoogle Scholar
  12. Crossland MD, Wynne BE, Perkins WC (1995) Spatial decision support systems: an overview of technology and a test of efficacy. Decis Support Syst 14(3):219–235CrossRefGoogle Scholar
  13. Crowley H, Pinho R, Bommer JJ (2004) A probabilistic displacement-based vulnerability assessment procedure for earthquake loss estimation. Bull Earthq Eng 2(2):173–219CrossRefGoogle Scholar
  14. Crowley H, Colombi M, Crempien J, Erduran E, Lopez M, Liu H, Mayfield M, Milanesi M (2010) GEM1 seismic risk report: part 1. GEM Technical Rep. GEM Foundation, PaviaGoogle Scholar
  15. Dan MB, Armaş I, Goretti A (2014) Earthquake hazard impact and urban planning—an Introduction. In: Earthquake Hazard Impact and Urban Planning, pp 1–12Google Scholar
  16. Daniell JE (2009) Comparison and production of open source earthquake loss assessment packages. MEEES Thesis, ROSE School, Pavia, ItalyGoogle Scholar
  17. Deichmann U (2011) Using high resolution satellite data for the identification of urban natural disaster risk. World Bank European Union Joint Report, World Bank, Washington, DC, USA, p 81Google Scholar
  18. Demircioglu MB, Erdik M, Hancilar U, Sesetyan K, Tuzun C, Yenidogan C, Zulfikar AC (2009) Technical manual—earthquake loss estimation routine ELERv. 1.0. Bogazici University, Department of Earthquake Engineering, Istanbul, p 133Google Scholar
  19. Densham PJ (1991) Spatial decision support systems. Geogr Inf Syst Princ Appl 1:403–412Google Scholar
  20. Di Pasquale G, Ferlito R, Orsini G, Papa F, Pizza AG, Van Dyck J, Veneziano D (2004) Seismic scenario tools for emergency planning and management. In: Proceedings of the XXIX general assembly of the European Seismological Commission, Potsdam, Germany, Engineering Seismology Session SCF-2BGoogle Scholar
  21. Dilley M (2005) Natural disaster hotspots: a global risk analysis, vol 5. World Bank Publications, Washington, DCCrossRefGoogle Scholar
  22. Eguchi RT, Goltz JD, Seligson HA, Flores PJ, Blais NC, Heaton TH, Bortugno E (1997) Real-time loss estimation as an emergency response decision support system: the early post-earthquake damage assessment tool (EPEDAT). Earthq Spectra 13(4):815–832CrossRefGoogle Scholar
  23. ELER v3.1 (2010) Earthquake loss estimation routine, technical manual and users guide. Bogazici University, Department of Earthquake Engineering, Istanbul. Accessed 26 May 2017
  24. Elnashai AS, Hampton S, Karaman H, Lee JS, Mclaren T, Myers J, Navarro C, Şahin M, Spencer B, Tolbert N (2008) Overview and applications of Maeviz-Hazturk 2007. J Earthq Eng 12(S2):100–108CrossRefGoogle Scholar
  25. Erden T (2012) Disaster and emergency management activities by geospatial tools with special reference to Turkey. Disaster Adv 5(1):29–36Google Scholar
  26. Erden T, Coskun MZ (2010) Multi-criteria site selection for fire services: the interaction with analytic hierarchy process and geographic information systems. Nat Hazards Earth Syst Sci 10(10):2127CrossRefGoogle Scholar
  27. Erden T, Karaman H (2012) Analysis of earthquake parameters to generate hazard maps by integrating AHP and GIS for Küçükçekmece region. Nat Hazards Earth Syst Sci 12(2):475–483CrossRefGoogle Scholar
  28. Erdik M, Aydinoglu N (2002) Earthquake performance and vulnerability of buildings in Turkey. Report prepared for World Bank Disaster Management Facility, WashingtonGoogle Scholar
  29. Erdik M, Fahjan Y (2006) Damage scenarios and damage evaluation. In: Oliveira CS, Roca A, Goula X (eds) Assessing and managing earthquake risk. Springer, Dordrecht, pp 213–237Google Scholar
  30. Erdik M, Aydinoglu N, Fahjan Y, Sesetyan K, Demircioglu M, Siyahi B, Durukal E, Ozbey C, Biro Y, Akman H, Yuzugullu O (2003a) Earthquake risk assessment for Istanbul metropolitan area. Earthqu Eng Eng Vib 2(1):1–23CrossRefGoogle Scholar
  31. Erdik M, Fahjan Y, Ozel O, Alcik H, Mert A, Gul M (2003b) Istanbul earthquake rapid response and the early warning system. Bull Earthq Eng 1(1):157–163CrossRefGoogle Scholar
  32. Erdik M, Cagnan Z, Zulfikar C, Sesetyan K, Demircioglu MB, Durukal E, Kariptas C (2008) Development of rapid earthquake loss assessment methodologies for Euro-Med region. In: Proceedings of the 14th World conference on earthquake engineeringGoogle Scholar
  33. Erdik M, Sesetyan K, Demircioglu M, Hancilar U, Zulfikar C, Cakti E, Kamer Y, Yenidogan C, Tuzun C, Cagnan Z, Harmandar E (2010) Rapid earthquake hazard and loss assessment for Euro-Mediterranean region. Acta Geophys 58(5):855–892CrossRefGoogle Scholar
  34. Erdik M, Kamer Y, Demircioğlu M, Şeşetyan K (2012) 23 October 2011 Van (Turkey) earthquake. Nat Hazards 64(1):651–665CrossRefGoogle Scholar
  35. Erdik M, Şeşetyan K, Demircioğlu MB, Zülfikar C, Hancılar U, Tüzün C, Harmandar E (2014) Rapid earthquake loss assessment after damaging earthquakes. In: Perspectives on European earthquake engineering and seismology. Springer, Berlin, pp 53–95Google Scholar
  36. ESRI (2003) Spatial data standards and GIS interoperability. ESRI White PaperGoogle Scholar
  37. FEMA (2003) HAZUS-MH technical manual. Federal Emergency Management Agency, WashingtonGoogle Scholar
  38. Ferreira MA, De Sá FM, Oliveira CS (2014) Disruption Index, DI: an approach for assessing seismic risk in urban systems (theoretical aspects). Bull Earthq Eng 12(4):1431–1458CrossRefGoogle Scholar
  39. GDACS (2017) Global disaster and alert coordination system. Accessed 16 June 2017
  40. Gheorghe D, Armaş I (2015) GIS based decision support system for seismic risk in Bucharest. Case study-the historical centre. J Eng Stud Res 21(3):35Google Scholar
  41. Greene R, Devillers R, Luther JE, Eddy BG (2011) GIS-based multiple-criteria decision analysis. Geogr Compass 5(6):412–432CrossRefGoogle Scholar
  42. Inomata W, Norito Y (2011) Result of SUPREME (Super-dense Real time monitoring Earthquake system for city gas supply) in The Great East Japan Earthquake. In: Proceedings of the international symposium on engineering lessons learnedGoogle Scholar
  43. 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(2):685–709CrossRefGoogle Scholar
  44. Karaman H, Şahin M, Elnashai AS (2008) Earthquake loss assessment features of maeviz-istanbul (hazturk). J Earthq Eng 12(S2):175–186CrossRefGoogle Scholar
  45. Kircher CA, Whitman RV, Holmes WT (2006) HAZUS earthquake loss estimation methods. Nat Hazards Rev 7(2):45–59CrossRefGoogle Scholar
  46. Levi T, Bausch D, Katz O, Rozelle J, Salamon A (2015) Insights from Hazus loss estimations in Israel for Dead Sea Transform earthquakes. Nat Hazards 75(1):365–388CrossRefGoogle Scholar
  47. Liu SX, Zhang YM, Yuan F, Shen S, Cai X, Weng T, Song WG, Liao GX (2007) Emergency decision supporting system for community safety in medium-sized city. J Saf Environ 7(2):140–143Google Scholar
  48. LRCD (2005) A preliminary report to build national GIS-Action 47. Land Registry and Cadastre Directorate of TurkeyGoogle Scholar
  49. MAE (2009) ZEUS-NL Registration. Accessed 12 May 2017
  50. Maktav D, Jürgens C, Siegmund A, Sunar F, Eşbah H, Kalkan K, Uysal C, Mercan OY, Akar İ, Thunig H, Wolf N (2011) Multi-criteria spatial decision support system for valuation of open spaces for urban planning. In: 5th International IEEE conference on recent advances in space technologies (RAST), p 160–163Google Scholar
  51. Malczewski J (1999) GIS and multi-criteria decision analysis. Wiley, New YorkGoogle Scholar
  52. Malczewski J, Rinner C (2015) Multi-criteria decision analysis in geographic information science. Springer, BerlinGoogle Scholar
  53. Menteşe EY, Konukcu BE, Kiliç O, Khazai B (2015) Megacity indicator system for disaster risk management (MegaIST): integrated assessment of physical risks in Istanbul. Disaster Management and Human Health Risk IV. Edited by Sinan Mert Sener, CA Brebbia and Ozlem Ozcevik, pp 25–36Google Scholar
  54. Midorikawa S (2005) Dense strong-motion array in Yokohama, Japan, and its use for disaster management. In: Directions in strong motion instrumentation. Springer, Berlin, pp 197–208Google Scholar
  55. Molina S, Lindholm C (2005) A logic tree extension of the capacity spectrum method developed to estimate seismic risk in Oslo, Norway. J Earthq Eng 9(06):877–897Google Scholar
  56. Molina S, Lang DH, Lindholm CD (2010) SELENA–An open-source tool for seismic risk and loss assessment using a logic tree computation procedure. Comput Geosci 36(3):257–269CrossRefGoogle Scholar
  57. National Research Council (2007) Successful response starts with a map: improving geospatial support for disaster management. National Academies Press, Washington, pp 1–198Google Scholar
  58. NCHRP RRD (2009) A guide to planning resources on transportation and hazards. National Cooperative Highway Research Program/Transit Cooperative Research Program Research Results Digest-NCHRP RRD 333/TCRP RRD 90Google Scholar
  59. NIBS and FEMA (2003) Multi-hazard loss estimation methodology, earthquake model. HAZUS®MH Technical Manual, Federal Emergency Management Agency, Washington, DCGoogle Scholar
  60. Olyazadeh R, Aye ZC, Jaboyedoff M (2013) Development of a prototype for spatial decision support system in risk reduction based on open-source web-based platform. In: Conference PaperGoogle Scholar
  61. Parker D, Mitchell JK (1995) Disaster vulnerability of megacities: an expanding problem that requires rethinking and innovative responses. GeoJournal 37(3):295–301CrossRefGoogle Scholar
  62. Parsons T (2004) Recalculated probability of M ≥ 7 earthquakes beneath the Sea of Marmara, Turkey. J Geophys Res Solid Earth. Google Scholar
  63. Perilis T (2012) Rapid seismic risk assessment at urban scale: application in Istanbul & Thessaloniki building stock. Master’s Thesis, Aristotle University of Thessaloniki, GreeceGoogle Scholar
  64. Philip G (2007) Remote sensing data analysis for mapping active faults in the northwestern part of Kangra Valley, NW Himalaya, India. Int J Remote Sens 28(21):4745–4761CrossRefGoogle Scholar
  65. Pollino M, Fattoruso G, Della Rocca A, La Porta L, Curzio S, Arolchi A, James V, Pascale C (2011) An open source GIS system for earthquake early warning and post-event emergency management. In: Computational science and its applications-ICCSA, pp 376–91Google Scholar
  66. Porter K, Scawthorn C (2007) Open-source risk estimation software. Technical Report, SPA Risk, Pasadena, United States of AmericaGoogle Scholar
  67. Rasekh A, Vafaeinezhad AR (2012) Developing a GIS based decision support system for resource allocation in earthquake search and rescue operation. In: International conference on computational science and its applications. Springer, Berlin, pp 275–285Google Scholar
  68. Robinson D, Fulford G, Dhu T (2005) EQRM: geoscience australia’s earthquake risk model. Geoscience Australia record. Geoscience Australia, CanberraGoogle Scholar
  69. Robinson D, Fulford G, Dhu T (2006) EQRM: geoscience Australia’s earthquake risk model technical manual version 3.0. Geoscience Australia, CanberraGoogle Scholar
  70. Sahin M, Karaman H, Erden T (2006) Disaster and emergency management activities in Turkey. In: XXIII FIG congress shaping the change, Munich, GermanyGoogle Scholar
  71. Sahin A, Sisman R, Askan A, Hori M (2016) Development of integrated earthquake simulation system for Istanbul. Earth Planets Space 68(1):115CrossRefGoogle Scholar
  72. Schmidt J, Turek G, Matcham I, Reese S, Bell RK, King A (2007) RiskScape—an innovative tool for multi-hazard risk modelling. Geophysical Research abstractsGoogle Scholar
  73. Sharifi MA (2004) Site selection for waste disposal through spatial multiple criteria decision analysis. J Telecommun Inf Technol 76:28–38Google Scholar
  74. Silva V, Crowley H, Pagani M, Monelli D, Pinho R (2013) Development of the OpenQuake engine, the global earthquake model’s open-source software for seismic risk assessment. Nat Hazards 72:1409–1427CrossRefGoogle Scholar
  75. Sousa ML, Campos Costa A, Carvalho A, Coelho E (2004) An automatic seismic scenario loss methodology integrated on a geographic information system. In: Proceedings of the 13th world conference on earthquake engineering, Vancouver, CanadaGoogle Scholar
  76. Strasser FO, Stafford PJ, Bommer JJ, Erdik M (2008) State-of-the-Art of European earthquake loss estimation software. In: Proceedings of the 14th world conference on earthquake engineering, Beijing, ChinaGoogle Scholar
  77. Sugumaran R, Degroote J, Sugumaran V (2011) Spatial decision support systems. Taylor and Francis, RoutledgeGoogle Scholar
  78. Tang AP, Zhao AP (2012) A decision supporting system for earthquake disaster mitigation. In: Second international IEEE conference intelligent system design and engineering application (ISDEA), pp 748–751Google Scholar
  79. Thomas DS, Cutter SL, Hodgson M, Gutekunst M, Jones S (2003) Use of spatial data and geographic technologies in response to the September 11th terrorist attack on the World Trade Center. Beyond September 11th: an account of post-disaster research, pp 147–62Google Scholar
  80. Thompson S, Altay N, Green WG III, Lapetina J (2006) Improving disaster response efforts with decision support systems. Int J Emerg Manag 3(4):250–263CrossRefGoogle Scholar
  81. Trendafiloski G, Wyss M, Rosset P (2011) Loss estimation module in the second generation software QLARM. In: Human casualties in earthquakes. Springer, Berlin, pp 95–106Google Scholar
  82. Unen HC, Karaman H, Şahin M, Elnashai AS (2010) Seismic performance analysis of utility lifeline networks in Istanbul, Turkey. FIG Congress, SydneyGoogle Scholar
  83. UNISDR (2010) Living with risk. A global review of disaster reduction initiatives. United Nations/International Strategy for Disaster Reduction. United Nations PublicationsGoogle Scholar
  84. Vandenbroucke D, Biliouris D (2010) Spatial data infrastructures in Turkey: state of play 2011. Spatial Applications Division KE, Leuven Research and DevelopmentGoogle Scholar
  85. Wahlström R, Tyagunov S, Grünthal G, Stempniewski L, Zschau J, Müller M (2004) Seismic risk analysis for Germany: Methodology and preliminary results. Disasters and Society-From Hazard Assessment to Risk Reduction. Logos Verlag Berlin 83-90Google Scholar
  86. Wald DJ, Jaiswal KS, Marano KD, Bausch DB, Hearne MG (2010) PAGER—rapid assessment of an earthquake’s impact: U.S. Geological Survey Fact Sheet 2010–3036. Revised Nov 2011Google Scholar
  87. Wenzel F, Daniell JE, Khazai B, Kunz-Plapp T (2012) The CEDIM forensic earthquake analysis group and the test case of the 2011 Van earthquakes. In: 15th World conference on earthquake engineering (WCEE)Google Scholar
  88. Whitman RV, Anagnos T, Kircher CA, Lagorio HJ, Lawson RS, Schneider P (1997) Development of a national earthquake loss estimation methodology. Earthq Spectra 13(4):643–661CrossRefGoogle Scholar
  89. Yamazaki F, Katayama T, Noda S, Yoshikawa Y, Otani Y (1995) Development of large-scale city-gas network alert system based on monitored earthquake ground motion. Doboku Gakkai Ronbunshu 525:331–340CrossRefGoogle Scholar
  90. Yeh CH, Loh CH, Tsai KC (2006) Overview of Taiwan earthquake loss estimation system. Nat Hazards 37(1):23–37CrossRefGoogle Scholar
  91. Yildiz SS (2013) Development of a fire following earthquake function for HAZTURK Software. Doctoral dissertation, Istanbul Technical University, TurkeyGoogle Scholar
  92. Zonno G, Carvalho A, Franceschina G, Akinci A, Costa AC, Coelho E, Cultrera G, Pacor F, Pessina V, Cocco M (2009) Simulating earthquake scenarios in the European Project LESSLOSS: the case of Lisbon. The 1755 Lisbon earthquake: revisited. Springer, Berlin, pp 233–243Google Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Geomatics Engineering, Faculty of Civil EngineeringIstanbul Technical UniversityIstanbulTurkey

Personalised recommendations