A dynamic decision support system based on geographical information and mobile social networks: A model for tsunami risk mitigation in Padang, Indonesia.
In coastal cities, population and property are concentrated in small areas, with abundant resources and convenient transportation, but also with potential tsunami , as shown by the tsunami disasters of 2004, 2010 in Indonesia. Coastal area citizens to evacuate to a safe place as soon as tsunamis occur. The prime evacuation time is very critical for them, but it is delayed in practice by complex information transfer processes. In recent years, spatial information has become an important resource used in dynamic decision support for emergencies, and smart phones have become a primary social communication device during interactions in emergencies. This paper outlines the design and development of a prototype geographical information system centric, social media based dynamic decision support system (GIS-SM-DDSS) that integrates geographical information with Twitter technology to enable self-organized information networks to support decision making and collective actions in situations. The actors include government policy makers, policy managers, highly influential social leaders in local communities, and policy executors and urban citizens impacted by disasters. The main system functions include dynamic analysis, timely dissemination of evacuation strategies to community residents, and real-time detection of environmental risk and evacuation support. This system is designed as a field in Padang, Indonesia, to help public officials design tsunami risk maps with timely evacuation routes and transmit these maps to influential leaders in local neighborhoods that are exposed to tsunami risk. Each neighborhood leader would then tweet the detailed route to citizens that follow the tweet. The proposed has potential to support evacuation strategies and real-time guidance of communities at risk during . [ABSTRACT FROM AUTHOR]/nCopyright of Safety Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
App development
regionFacilities locationShelter locationBarrier report
This system is designed as a field in Padang, Indonesia, to help public officials design tsunami maps with timely evacuation routes and transmit these maps to influential leaders in local neighborhoods that are exposed to tsunami .Each neighborhood leader would then tweet the detailed route to citizens that follow the tweet.The community leaders install the DDSS APP in their smart phones, they not only could view the tsunami risk, but also obtain real-time evacuation route information disseminated from the EOCThis APP will help community leaders to recognize real-time tsunami risk, and organize community citizens to take rapid and effective collective evacuation action.n.a., if the app was actually tested or it is only proposed to be tested this way.
The actors include government policy makers, policy managers, highly influential social leaders in local communities, and policy executors and urban citizens impacted by disasters.
The proposed has potential to support evacuation strategies and real-time guidance of communities at during .
The main system functions include dynamic analysis, timely dissemination of evacuation strategies to community residents, and real-time detection of environmental and evacuation support.The GIS-SM-DDSS gives collective action support for public evacuation in tsunami disasters. The Mobile-GIS provides realtime spatial visualization of tsunami risk and resources, the Operations Center analyzes the evacuation route to a safe area. The leaders are election based on the acquirable affinity information which reflects the relationships between candidates and their visited community. When the Internet is available, the Managers push the evacuation routes to local community leaders through the social media platform, Twitter, then tweet to their community citizens. When Internet is not available, the Opportunistic network – Coverage-based Probabilistic Forwarding in ad-hoc routing will work. The leaders will monitor and report environmental situations changing in real-time to guarantee the latest information update for the policy design. The public evacuates to assigned shelters that follow the detailed evacuation policies.
This paper outlines the design and development of a prototype geographical information system centric, social media based dynamic decision support system (GIS-SM-DDSS) that integrates geographical information with Twitter technology to enable selforganized information networks to support decision making and collective actions in situations.
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