Centre dedocumentation
scientifique

Real-time mapping of natural disasters using citizen update streams / Iranga Subasinghe in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 393 - 421 Titre : Real-time mapping of natural disasters using citizen update streams Type de document : Article/Communication Auteurs : Iranga Subasinghe, Auteur ; Silvia Nittel, Auteur ; Michael Cressey, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 393 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] cartographie collaborative [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] diagramme de Voronoï [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] incendie [Termes descripteurs IGN] inondation [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] système multi-agents [Termes descripteurs IGN] tempête [Termes descripteurs IGN] temps réel [Termes descripteurs IGN] ville intelligente Résumé : (auteur) Natural disasters such as flooding, wildfires, and mudslides are rare events, but they affect citizens at unpredictable times and the impact on human life can be significant. Citizens located close to events can provide detailed, real-time data streams capturing their event response. Instead of visualizing individual updates, an integrated spatiotemporal map yields ‘big picture’ event information. We investigate the question of whether information from affected citizens is sufficient to generate a map of an unfolding natural disaster. We built the Citizen Disaster Reaction Multi-Agent Simulation (CDR-MAS), a multi-agent system that simulates the reaction of citizens to a natural disaster in an urban region. We proposed an rkNN classification algorithm to aggregate the update streams into a series of colored Voronoi event maps. We simulated the 2018 Montecito Creek mudslide and customized the CDR-MAS with the local environment to systematically generate stream data sets. Our experimental evaluation showed that event mapping based on citizen update streams is significantly influenced by the amount of citizen participation and movement. Compared with a baseline of 100% participation, with 40% citizen participation, the event region was predicted with 40% accuracy, showing that citizen update streams can provide timely information in a smart city. Numéro de notice : A2020-031 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1639185 date de publication en ligne : 15/07/2019 En ligne : https://doi.org/10.1080/13658816.2019.1639185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94486 [article]

Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne / Marcello Marini in Computers, Environment and Urban Systems, vol 78 (November 2019)  

Public [article]  inComputers, Environment and Urban Systems > vol 78 (November 2019) Titre : Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne Type de document : Article/Communication Auteurs : Marcello Marini, Auteur ; Ndaona Chokani, Auteur ; Reza S. Abhari, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] agglomération [Termes descripteurs IGN] banlieue [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] immigration [Termes descripteurs IGN] Lausanne [Termes descripteurs IGN] logement [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] modèle numérique du bâti [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] périphérie urbaine [Termes descripteurs IGN] projection perspective [Termes descripteurs IGN] système multi-agents Résumé : (auteur) Immigration accounts for 80% of Switzerland's annual population growth, and therefore profoundly impacts demographics, and the attendant housing needs. As there are different possible future scenarios of immigration that will impact urban transformation in Switzerland, we have developed an agent-based dwellings model that, with reasonable computing time due to the use of the computer architecture of graphical processor units, can simulate for a time horizon of decades, the annual evolution of millions of individually characterised households. This dwellings model is coupled to an agent-based population model that simulates millions of individual population agents. We simulate different immigration scenarios, up to 2035, in the Swiss agglomeration of Lausanne. It is shown that the building capacity of the city of Lausanne will reach a limit in 2022, subsequently leading to more rapid growth in the periphery of the agglomeration Lausanne. The construction of new residential dwellings consists primarily of smaller apartments that are more attractive to the demographic of smaller households; this demographic tends to move to the periphery. As families tend to move towards the city centre due to the availability of services, the city and periphery show opposite evolutions over time in the numbers of family households compared to numbers of singles and couples households. The periphery requires an increase in the number and typology of services targeted at the growing demographic of smaller households. Further as most workplaces are still be located in the city centre, the planned improvement of transportation infrastructure in the agglomeration should primarily focus on improved access to the periphery. These observations underline the profound impact of the typology of immigration on the demand for suitable housing, and thus on urban development. Numéro de notice : A2019-413 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2019.101400 date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93538 [article]

Is deep learning the new agent for map generalization? / Guillaume Touya in International journal of cartography, vol 5 n° 2-3 (July - November 2019)  

Public [article]  inInternational journal of cartography > vol 5 n° 2-3 (July - November 2019) . - pp 142 - 157 Titre : Is deep learning the new agent for map generalization? Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Xiang Zhang, Auteur ; Imran Lokhat , Auteur Congrès : Congrès: ICC 2019, 29th International Cartographic Conference ICA Mapping everything for everyone (15 - 20 juillet 2019; Tokyo, Japon) , Commanditaire Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : pp 142 - 157 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] système multi-agents [Vedettes matières IGN] Généralisation Résumé : (Auteur) The automation of map generalization has been keeping researchers in cartography busy for years. Particularly great progress was made in the late 90s with the use of the multi-agent paradigm. Although the current use of automatic processes in some national mapping agencies is a great achievement, there are still many unsolved issues and research seems to stagnate in the recent years. With the success of deep learning in many fields of science, including geographic information science, this paper poses the controversial question of the title: is deep learning the new agent, i.e. the technique that will make generalization research bridge the gap to fully automated generalization processes? The paper neither responds a clear yes nor a clear no but discusses what issues could be tackled with deep learning and what the promising perspectives. Some preliminary experiments with building generalization or data enrichments are presented to support the discussion. Numéro de notice : A2019-235 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1613071 date de publication en ligne : 09/05/2019 En ligne : https://doi.org/10.1080/23729333.2019.1613071 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92932 [article]

A four‐dimensional agent‐based model: A case study of forest‐fire smoke propagation / Alex Smith in Transactions in GIS, vol 23 n° 3 (June 2019)  

Public [article]  inTransactions in GIS > vol 23 n° 3 (June 2019) . - pp 417 - 434 Titre : A four‐dimensional agent‐based model: A case study of forest‐fire smoke propagation Type de document : Article/Communication Auteurs : Alex Smith, Auteur ; Suzana Dragićević, Auteur Année de publication : 2019 Article en page(s) : pp 417 - 434 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] Alberta [Termes descripteurs IGN] Colombie-Britannique (Canada) [Termes descripteurs IGN] données 4D [Termes descripteurs IGN] fumée [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] modélisation 4D [Termes descripteurs IGN] risque environnemental [Termes descripteurs IGN] système multi-agents Résumé : (Auteur) Dynamic geospatial complex systems are inherently four‐dimensional (4D) processes and there is a need for spatio‐temporal models that are capable of realistic representation for improved understanding and analysis. Such systems include changes of geological structures, dune formation, landslides, pollutant propagation, forest fires, and urban densification. However, these phenomena are frequently analyzed and represented with modeling approaches that consider only two spatial dimensions and time. Consequently, the main objectives of this study are to design and develop a modeling framework for 4D agent‐based modeling, and to implement the approach to the 4D case study for forest‐fire smoke propagation. The study area is central and southern British Columbia and the western parts of Alberta, Canada for forest fires that occurred in the summer season of 2017. The simulation results produced realistic spatial patterns of the smoke propagation dynamics. Numéro de notice : A2019-253 Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12551 date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.1111/tgis.12551 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93011 [article]

CartAGen: an open source research platform for map generalization / Guillaume Touya (2019)    

Public Titre : CartAGen: an open source research platform for map generalization Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Imran Lokhat , Auteur ; Cécile Duchêne , Auteur Congrès : Congrès: ICC 2019, 29th International Cartographic Conference ICA Mapping everything for everyone (15 - 20 juillet 2019; Tokyo, Japon) , Commanditaire Editeur : International Cartographic Association ICA Année de publication : 2019 Autre Editeur : Göttingen : Copernicus publications Collection : Proceedings of the ICA Projets : 1-Pas de projet / Importance : 9 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de généralisation [Termes descripteurs IGN] CartAGen (plateforme de généralisation) [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] logiciel libre [Termes descripteurs IGN] organisme cartographique national [Termes descripteurs IGN] plateforme logicielle [Termes descripteurs IGN] système multi-agents [Vedettes matières IGN] Généralisation Résumé : (Auteur) Automatic map generalization is a complex task that is still a research problem and requires the development of research prototypes before being usable in productive map processes. In the meantime, reproducible research principles are becoming a standard. Publishing reproducible research means that researchers share their code and their data so that other researchers might be able to reproduce the published experiments, in order to check them, extend them, or compare them to their own experiments. Open source software is a key tool to share code and software, and CartAGen is the first open source research platform that tackles the overall map generalization problem: not only the building blocks that are generalization algorithms, but also methods to chain them, and spatial analysis tools necessary for data enrichment. This paper presents the CartAGen platform, its architecture and its components. The main component of the platform is the implementation of several multi-agent based models of the literature such as AGENT, CartACom, GAEL, CollaGen, or DIOGEN. The paper also explains and discusses different ways, as a researcher, to use or to contribute to CartAGen. Numéro de notice : C2019-010 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-2-134-2019 date de publication en ligne : 10/07/2019 En ligne : https://doi.org/10.5194/ica-proc-2-134-2019 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93258

Documents numériques

peut être téléchargé CartAGen: an open source research platform - pdf éditeur Adobe Acrobat PDF

Integrating multi-agent evacuation simulation and multi-criteria evaluation for spatial allocation of urban emergency shelters / Jia Yu in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

Permalink

Video event recognition and anomaly detection by combining gaussian process and hierarchical dirichlet process models / Michael Ying Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 4 (April 2018)  

Permalink

Multi-agents systems for cartographic generalization: Feedback from past and on-going research / Cécile Duchêne (2018) 

Permalink

DIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)  

Permalink

ViCTOr : paysage virtuel pour explorer les dynamiques de la VIticulture et de la Consommation en TouRaine / Etienne Delay in Cybergeo, European journal of geography, n° 2017 (2017)  

Permalink

An intelligent spatial land use planning support system using socially rational agents / Seyed Moral Ghavami in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Permalink

An ontology-driven multi-agent system for nautical chart generalization / Jingya Yan in Cartography and Geographic Information Science, Vol 44 n° 3 (May 2017)  

Permalink

Modèles géographiques avec le langage Mathematica / André Dauphiné (2017)

Permalink

Modelling a dynamic forest fuelmarket focusing on wood chips: a spatial agent-based approach to simulate competition among heating plants in the province of Carinthia, Austria / Johannes Scholz in GI Forum, vol 2017 n° 1 ([01/01/2017])  

Permalink

An intelligent geospatial processing unit for image classification based on geographic vector agents (GVAs) / Kambiz Borna in Transactions in GIS, vol 20 n° 3 (June 2016)  

Permalink