TY - GEN
T1 - Case studies for data-oriented emergency management/planning in complex urban systems
AU - Xie, Kun
AU - Ozbay, Kaan
AU - Zhu, Yuan
AU - Yang, Hong
N1 - Publisher Copyright:
© Springer-Verlag GmbH Germany 2016.
PY - 2016
Y1 - 2016
N2 - To reduce the losses caused by natural disasters such as hurricanes, it is necessary to build effective and efficient emergency management/planning systems for cities. With increases in volume, variety and acquisition rate of urban data, major opportunities exist to implement data-oriented emergency management/planning. New York/New Jersey metropolitan area is selected as the study area. Large datasets related to emergency management/planning including, traffic operations, incidents, geographical and socio-economic characteristics, and evacuee behavior are collected from various sources. Five related case studies conducted using these unique datasets are summarized to present a comprehensive overview on how to use big urban data to obtain innovative solutions for emergency management and planning, in the context of complex urban systems. Useful insights are obtained from data for essential tasks of emergency management and planning such as evacuation demand estimation, determination of evacuation zones, evacuation planning and resilience assessment.
AB - To reduce the losses caused by natural disasters such as hurricanes, it is necessary to build effective and efficient emergency management/planning systems for cities. With increases in volume, variety and acquisition rate of urban data, major opportunities exist to implement data-oriented emergency management/planning. New York/New Jersey metropolitan area is selected as the study area. Large datasets related to emergency management/planning including, traffic operations, incidents, geographical and socio-economic characteristics, and evacuee behavior are collected from various sources. Five related case studies conducted using these unique datasets are summarized to present a comprehensive overview on how to use big urban data to obtain innovative solutions for emergency management and planning, in the context of complex urban systems. Useful insights are obtained from data for essential tasks of emergency management and planning such as evacuation demand estimation, determination of evacuation zones, evacuation planning and resilience assessment.
KW - Big data
KW - Complex urban systems
KW - Emergency management/planning
KW - Evacuation modeling
KW - Hurricane
UR - http://www.scopus.com/inward/record.url?scp=84988603415&partnerID=8YFLogxK
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U2 - 10.1007/978-3-662-53416-8_12
DO - 10.1007/978-3-662-53416-8_12
M3 - Conference contribution
AN - SCOPUS:84988603415
SN - 9783662534151
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 190
EP - 207
BT - Transactions on Large-Scale Data- and Knowledge-Centered Systems - 28th Symposium Big Data and Technology for Complex Urban Systems
A2 - Kalisch, Dominik
A2 - Hameurlain, Abdelkader
A2 - Hung, Patrick C.K.
A2 - Sobolevsky, Stanislav
A2 - Anjomshoaa, Amin
A2 - Küng, Josef
A2 - Wagner, Roland
PB - Springer Verlag
T2 - 49th Hawaii International Conference on System Sciences, HICSS 2016
Y2 - 5 January 2016 through 8 January 2016
ER -