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Exploring multi-modal evacuation strategies for a landlocked population using large-scale agent-based simulations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 9 (September 2022) . - pp 1741 - 1783 Titre : Exploring multi-modal evacuation strategies for a landlocked population using large-scale agent-based simulations Type de document : Article/Communication Auteurs : Kevin Chapuis, Auteur ; Pham Minh-Duc, Auteur ; Arthur Brugière, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1741 - 1783 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] gestion de crise [Termes IGN] gestion des risques [Termes IGN] inondation [Termes IGN] modèle de simulation [Termes IGN] modèle orienté agent [Termes IGN] prévention des risques [Termes IGN] secours d'urgence [Termes IGN] trafic routier [Termes IGN] Viet Nam [Termes IGN] zone urbaine Résumé : (auteur) At a time when the impacts of climate change and increasing urbanization are making risk management more complex, there is an urgent need for tools to better support risk managers. One approach increasingly used in crisis management is preventive mass evacuation. However, to implement and evaluate the effectiveness of such strategy can be complex, especially in large urban areas. Modeling approaches, and in particular agent-based models, are used to support implementation and to explore a large range of evacuation strategies, which is impossible through drills. One major limitation with simulation of traffic based on individual mobility models is their capacity to reproduce a context of mixed traffic. In this paper, we propose an agent-based model with the capacity to overcome this limitation. We simulated and compared different spatio-temporal evacuation strategies in the flood-prone landlocked area of the Phúc Xá district in Hanoi. We demonstrate that the interaction between distribution of transport modalities and evacuation strategies greatly impact evacuation outcomes. More precisely, we identified staged strategies based on the proximity to exit points that make it possible to reduce time spent on road and overall evacuation time. In addition, we simulated improved evacuation outcomes through selected modification of the road network. Numéro de notice : A2022-644 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2069774 Date de publication en ligne : 16/05/2022 En ligne : https://doi.org/10.1080/13658816.2022.2069774 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101455 [article]

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079-2022091	SL	Revue	Centre de documentation	Revues en salle	Disponible

Gen*: a generic toolkit to generate spatially explicit synthetic populations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1194 - 1210 Titre : Gen*: a generic toolkit to generate spatially explicit synthetic populations Type de document : Article/Communication Auteurs : Kevin Chapuis, Auteur ; Patrick Taillandier , Auteur ; Misslin Renaud, Auteur ; Alexis Drogoul, Auteur Année de publication : 2018 Article en page(s) : pp 1194 - 1210 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] distribution spatiale [Termes IGN] figuration de la densité [Termes IGN] modèle orienté agent [Termes IGN] population urbaine [Termes IGN] programmation par contraintes [Termes IGN] recensement démographique [Termes IGN] régression [Termes IGN] Rouen [Termes IGN] système d'information géographique Résumé : (Auteur) Agent-based models tend to integrate more and more data that can deeply impact their outcomes. Among these data, the ones that deal with agent attributes and localization are particularly important, but are very difficult to collect. In order to tackle this issue, we propose a complete generic toolkit called Gen* dedicated to generating spatially explicit synthetic populations from global (census and GIS) data. This article focuses on the localization methods provided by Gen* that are based on regression, geometrical constraints and spatial distributions. The toolkit is applied for a case study concerning the generation of the population of Rouen (France) and shows the capabilities of Gen* regarding population spatialization. Numéro de notice : A2018-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1440563 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1080/13658816.2018.1440563 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89875 [article]

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079-2018031	RAB	Revue	Centre de documentation	En réserve L003	Disponible