MIS in Earthquake Response

‘Dream Team’Dan Xie(4172339)Ruiting Cai(4153120)Jessica Seddon(4174087)Jianan Zhang(4152409)Layla Delgosha(4166354)Pei Zhu(4156370)Yun Yang(4153964)

Agenda• Introduction to global earthquakes and their

consequences• Statistics about earthquake degree and death

rates• Critical evaluation of the role of MIS in disaster

response• Comparing MIS in developed and developing

countries (Japan's system vs. SAHANA) • Evaluation

Introduction

Source: OFDA

Earthquake degree and death rates

1990 1995 2000 2005 20100123456789

10

The marginal degree of Japan and In-

donesiaJapan Indonesia

Years

Deg

ree

05000

1000015000200002500030000

The Death rate resulting from the

EarthquakesJapan Indonesia

The Standard Characteristics of MIS in Earthquakes

• A system that records, collects, keeps, retrieves and analyses inputs and alters the reports and required earthquake information (Sima,2009)

• Once the earthquake is identified, the system will estimate the damage and loss

• It contains earthquake Early Warning System (EEW) and post recovery system

SWOT Analysis of Earthquake MIS

Strengths WeaknessesOpportunities Threats

Rapid response

Forecast (before)

Reconstruct (after)

Risk reducing

•Unpredictability •Software failure (e.g. virus)•Security of hardware

•Preparing for disasters in the future•Government support/Collaboration•New technology and innovation

•Information reliability•User involvement (information gap)•Budget constraints•Not easy to change

MIS in Developed Countries• Background of Japan • Japan is the third largest economy in the world

but also one of the most earthquake-prone countries.

• Japan Meteorological Agency (JMA) uses the “PHOENIX” post recovery system:

Benefits Drawbacks• Advanced networks• Direct connection with

broadcasting media• Fast, accurate, reliable

• Earthquakes are very much unpredictable

• Sensitivity – false alarms

• Vulnerability to human error

Phoenix System

Source from: Disaster Prevention and Management (2009)

• Introduced in the late 1950’s

• Localised systems in each town to collect information

MIS in Developing Countries

• Lack of resources to fund MIS• Prior to SAHANA – no globally accepted standard• Response to the Sumatra-Andaman earthquake (2004)• Tsunami Evaluation Commission:

“significant effort and funding should be dedicated to organizing open source, easily shareable software and training tools to prepare for all stages of disaster response”

• Open Source Software – can be improved and distributed at no cost (not built on proprietary of licensed software platforms and not owned by any single entity)

More on SAHANA• SAHANA – Low cost, FOSS approach, adaptability

• Awards2006 – Highest award in the Open Source Industry (Free Software Foundation)Award for Social Benefit (beat Project Gutenburg & Wikipedia)

• Drawback – lack of a helpline

Evaluation • PHOENIX Vs. SAHANA• CSF for MIS in earthquake

Top management supportPlanned channels for information flows User involvement and training Coordination and Cooperation within each department

References• Ajami, S. & Fattahi, M. (2009) ‘The role of earthquake information management systems (EIMSs) in reducing destruction: A comparative

study of Japan, Turkey and Iran’, Disaster Prevention and Management, 18(2), pp.150 – 161• Careem et al. (2006) ‘Sahana, Overview of a Disaster Management System’, Proceedings of the International Conference on

Information and Automation. Available at: ftp://ftp.umiacs.umd.edu/pub/louiqa/PUB06/Sahana6.pdf• Currion et al. (2007) ‘Open Source Software for Disaster Management’, Communications of the ACM, 50(3), pp. 61-65• Daniell, J. E. (2011) ‘Open Source Procedure for Assessment of Loss using Global Earthquake Modelling software (OPAL)’, Natural

Hazards and Earth Systems Science. Available at: http://www.nat-hazards-earth-syst-sci.net/11/1885/2011/nhess-11-1885-2011.pdf• Global Facility for Disaster Reduction and Recovery (2012). Available at: http://www.gfdrr.org/gfdrr/• International Free and Open Source Solutions Foundation (2012). Available at: http://ifossf.org/• Leebmann, J. & Kyalo Kiema, J. B, (n.d) ‘Knowledge Representation In Technical Information Systems For Earthquake Loss Mitigation’.

Available at: http://www.iiasa.ac.at/Research/RMP/july2000/Papers/leebmann.pdf• Phoenix Geographics Ltd (1996) ‘Earthquake Prediction in Future’, The Phoenix, 6, pp. 1-8• Seeger, M. W., Sellnow, T. L., & Ulmer, R. R. (2003). Communication, organization and crisis. West port, CT: Quoru• Society for Research and Initiatives for Sustainable Technologies and Institutions (2012). Available at: http://www.sristi.org/cms/• Reynolds, B. & Seeger, M. (2005) ‘Crisis and Emergency Risk Communication as an Integrative Model’, Journal of Health

Communication, 10, pp. 43-55• Woodworth, B. (n.d) ‘The SAHANA Disaster Management System: A contribution by IBM’. Available at:

http://www.bizforum.org/whitepapers/ibm-10.htm • Xu et al (2009). ‘Coseismic reverse- and oblique-slip surface faulting generated by the 2008 Mw 7.9 Wenchuan earthquake, China’, The

Geological Society of America, 37 (6), pp. 515-518• Yamada et al (2004). ‘Earthquake Disaster Prevention Information System Based on Risk Adaptive Regional Management Information

System Concept’ 13th World Conference on Earthquake Engineering, Vancouver, B.C., Canada. Available at: http://www.iitk.ac.in/nicee/wcee/article/13_709.pdf

• The system takes only two minutes to produce a report after the earthquake has occurred

• It can forecast a tsunami around three minutes in advance