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Record Nr. |
UNINA9910412353203321 |
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Autore |
Zhang Hui |
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Titolo |
EM-GIS 2019 : proceedings of the 5th ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management (EM-GIS 2019) : November 5th, 2019, Chicago, IL, USA / / Hui Zhang, Yan Huang, Jean-Claude Thill |
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Pubbl/distr/stampa |
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New York, New York : , : Association for Computing Machinery, , 2019 |
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Descrizione fisica |
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1 online resource (103 pages) : illustrations |
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Disciplina |
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Soggetti |
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Emergency management |
Emergency management - Geographic information systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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Emergency management is the creation of plans through which communities decrease the impact of disasters and prevent from unexpected events (i.e., human or natural disasters). By quick response and rescue, it saves human lives from the secondary disasters and enhances the stability of communities after disasters. Emergency management involves four stages: Planning and Mitigation, Preparedness, Response and Recovery. Geospatial applications (including GIS) have been extensively used in each stage of emergency management. GIS provides reliable support for spatial analysis and decision-making in emergency management. The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2019 (ACM SIGSPATIAL 2019), the twenty seventh edition, will be held in Chicago, November 5-8, 2019. All workshops will be held on November 5, 2019 at the conference hotel. The purpose of the EMGIS 2019 workshop is to provide a forum for researchers and practitioners to exchange ideas and progress in related areas. This workshop in the ACM SIGSPATIAL conference addresses the challenges of emergency management based on advanced GIS technologies. This workshop will bring together researchers and practitioners in massive spatiotemporal |
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data management, spatial database, spatial data analysis, spatial data visualization, data integration, model integration, cloud computing, parallel algorithms, internet of things, complex event detection, optimization theory, intelligent transportation systems and social networks to support better public policy through disaster detection, response and rescue. |
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