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An approach to support decision-making in disaster management based on volunteer geographic information (VGI) and spatial decision support systems (SDSS)
Flávio E. A. Horita
author
João Porto De Albuquerque
author
2013
Karlsruher Institut fur Technologie
KIT; Baden-Baden
English
The damage caused by recent events in Japan in 2011 and USA in 2012 highlighted the need to adopt measures to increase the resilience of communities against extreme events and disasters. In addition to the conventional and official information that is necessary for adaptation to disasters, recently, common citizens residents in the affected areas also began contributing with voluntary qualified and updated information. In this context, this work-in-progress presents an approach that uses voluntary information – Also known by VGI (Volunteered Geographic Information) – As a data source for Spatial Decision Support Systems (SDSS) in order to assist the decision-making in disaster management. Our approach consists of a framework that integrates voluntary and conventional data, a SDSS and processes and methods for decision-making. As a result, it is expected that this approach will assist official organizations in disaster management by providing mechanisms and information.
Artificial intelligence
Decision making
Decision support systems
Disaster prevention
Information systems
Disaster management
Extreme events
Geographic information
Spatial decision support systems
Updated informations
Vgi
Volunteered geographic information
Work-in-progress
Disasters
exported from refbase (http://idl.iscram.org/show.php?record=592), last updated on Sun, 09 Aug 2015 05:36:34 +0200
text
http://idl.iscram.org/files/horita/2013/592_Horita+DeAlbuquerque2013.pdf
FlavioE.A.Horita+JoaoPortoDeAlbuquerque2013
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management
ISCRAM 2013
T. Comes
F
Fiedrich
editor
10th International ISCRAM Conference on Information Systems for Crisis Response and Management
2013
Karlsruher Institut fur Technologie
KIT; Baden-Baden
conference publication
301
306
9783923704804
2411-3387
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