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scientifique

GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 336 Titre : GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data Type de document : Article/Communication Auteurs : Wanqin He, Auteur ; Sara Shirowzhan, Auteur ; Christopher Pettit, Auteur Année de publication : 2022 Article en page(s) : n° 336 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse diachronique [Termes IGN] apprentissage automatique [Termes IGN] brousse [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] coefficient de corrélation [Termes IGN] données météorologiques [Termes IGN] données spatiotemporelles [Termes IGN] humidité du sol [Termes IGN] incendie [Termes IGN] indice de végétation [Termes IGN] Nouvelle-Galles du Sud [Termes IGN] prévention des risques [Termes IGN] régression linéaire [Termes IGN] Spark [Termes IGN] système d'information géographique [Termes IGN] température de l'air Résumé : (auteur) The causes of bushfires are extremely complex, and their scale of burning and probability of occurrence are influenced by the interaction of a variety of factors such as meteorological factors, topography, human activity and vegetation type. An in-depth understanding of the combined mechanisms of factors affecting the occurrence and spread of bushfires is needed to support the development of effective fire prevention plans and fire suppression measures and aid planning for geographic, ecological maintenance and urban emergency management. This study aimed to explore how bushfires, meteorological variability and other natural factors have interacted over the past 40 years in NSW Australia and how these influencing factors synergistically drive bushfires. The CSIRO’s Spark toolkit has been used to simulate bushfire burning spread over 24 h. The study uses NSW wildfire data from 1981–2020, combined with meteorological factors (temperature, precipitation, wind speed), vegetation data (NDVI data, vegetation type) and topography (slope, soil moisture) data to analyse the relationship between bushfires and influencing factors quantitatively. Machine learning-random forest regression was then used to determine the differences in the influence of bushfire factors on the incidence and burn scale of bushfires. Finally, the data on each influence factor was imported into Spark, and the results of the random forest model were used to set different influence weights in Spark to visualise the spread of bushfires burning over 24 h in four hotspot regions of bushfire in NSW. Wind speed, air temperature and soil moisture were found to have the most significant influence on the spread of bushfires, with the combined contribution of these three factors exceeding 60%, determining the spread of bushfires and the scale of burning. Precipitation and vegetation showed a greater influence on the annual frequency of bushfires. In addition, burn simulations show that wind direction influences the main direction of fire spread, whereas the shape of the flame front is mainly due to the influence of land classification. Besides, the simulation results from Spark could predict the temporal and spatial spread of fire, which is a potential decision aid for fireproofing agencies. The results of this study can inform how fire agencies can better understand fire occurrence mechanisms and use bushfire prediction and simulation techniques to support both their operational (short-term) and strategic (long-term) fire management responses and policies. Numéro de notice : A2022-481 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11060336 Date de publication en ligne : 05/06/2022 En ligne : https://doi.org/10.3390/ijgi11060336 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100894 [article]

A web GIS-based integration of 3D digital models with linked open data for cultural heritage exploration / Ikrom Nishanbaev in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 684 Titre : A web GIS-based integration of 3D digital models with linked open data for cultural heritage exploration Type de document : Article/Communication Auteurs : Ikrom Nishanbaev, Auteur ; Erik Champion, Auteur ; David A. McMeekin, Auteur Année de publication : 2021 Article en page(s) : n° 684 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] Australie [Termes IGN] carte interactive [Termes IGN] édition en libre accès [Termes IGN] hétérogénéité [Termes IGN] informatique en nuage [Termes IGN] interface de programmation [Termes IGN] interopérabilité [Termes IGN] métadonnées [Termes IGN] modélisation 3D [Termes IGN] patrimoine culturel [Termes IGN] QGIS [Termes IGN] SPARQL [Termes IGN] visualisation 3D [Termes IGN] web des données [Termes IGN] WebSIG Résumé : (auteur) In recent years, considerable efforts have been made by cultural heritage institutions across the globe to digitise cultural heritage sites, artifacts, historical maps, etc. for digital preservation and online representation. On the other hand, ample research projects and studies have been published that demonstrate the great capabilities of web-geographic information systems (web-GIS) for the dissemination and online representation of cultural heritage data. However, cultural heritage data and the associated metadata produced by many cultural heritage institutions are heterogeneous. To make this heterogeneous data more interoperable and structured, an ever-growing number of cultural heritage institutions are adopting linked data principles. Although the cultural heritage domain has already started implementing linked open data concepts to the cultural heritage data, there are not many research articles that present an easy-to-implement, free, and open-source-based web-GIS architecture that integrates 3D digital cultural heritage models with cloud computing and linked open data. Furthermore, the integration of web-GIS technologies with 3D web-based visualisation and linked open data may offer new dimensions of interaction and exploration of digital cultural heritage. To demonstrate the high potential of integration of these technologies, this study presents a novel cloud architecture that attempts to enhance digital cultural heritage exploration by integrating 3D digital cultural heritage models with linked open data from DBpedia and GeoNames platforms using web-GIS technologies. More specifically, a digital interactive map, 3D digital cultural heritage models, and linked open data from DBpedia and GeoNames platforms were integrated into a cloud-based web-GIS architecture. Thus, the users of the architecture can easily interact with the digital map, visualise 3D digital cultural heritage models, and explore linked open data from GeoNames and DBpedia platforms, which offer additional information and context related to the selected cultural heritage site as well as external web resources. The architecture was validated by applying it to specific case studies of Australian cultural heritage and seeking expert feedback on the system, its benefits, and scope for improvement in the near future. Numéro de notice : A2021-802 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100684 Date de publication en ligne : 11/10/2021 En ligne : https://doi.org/10.3390/ijgi10100684 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98854 [article]

3D map creation using crowdsourced GNSS data / Terence Lines in Computers, Environment and Urban Systems, vol 89 (September 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 89 (September 2021) Titre : 3D map creation using crowdsourced GNSS data Type de document : Article/Communication Auteurs : Terence Lines, Auteur ; Anahid Basiri, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] approche participative [Termes IGN] Bootstrap (statistique) [Termes IGN] cartographie 3D [Termes IGN] données GNSS [Termes IGN] données localisées 2,5D [Termes IGN] hauteur du bâti [Termes IGN] interface de programmation [Termes IGN] régression logistique [Termes IGN] signal GNSS [Termes IGN] trajet multiple [Termes IGN] vision par ordinateur Résumé : (auteur) 3D maps are increasingly useful for many applications such as drone navigation, emergency services, and urban planning. However, creating 3D maps and keeping them up-to-date using existing technologies, such as laser scanners, is expensive. This paper proposes and implements a novel approach to generate 2.5D (otherwise known as 3D level-of-detail (LOD) 1) maps for free using Global Navigation Satellite Systems (GNSS) signals, which are globally available and are blocked only by obstacles between the satellites and the receivers. This enables us to find the patterns of GNSS signal availability and create 3D maps. The paper applies algorithms to GNSS signal strength patterns based on a boot-strapped technique that iteratively trains the signal classifiers while generating the map. Results of the proposed technique demonstrate the ability to create 3D maps using automatically processed GNSS data. The results show that the third dimension, i.e. height of the buildings, can be estimated with below 5 metre accuracy, which is the benchmark recommended by the CityGML standard. Numéro de notice : A2021-535 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101671 Date de publication en ligne : 19/06/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101671 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97998 [article]

Restituer les bidonvilles de Nanterre : l’apport d’un outil de visualisation 3D à un projet de sciences sociales / Paul Lecat in Humanités numériques, n° 3 (2021)  

Public [article]  inHumanités numériques > n° 3 (2021) . - n° 1946 Titre : Restituer les bidonvilles de Nanterre : l’apport d’un outil de visualisation 3D à un projet de sciences sociales Titre original : Restoring the Shantytowns of Nanterre: Benefits of a 3D Visualisation Tool for a Social Sciences Project Type de document : Article/Communication Auteurs : Paul Lecat, Auteur ; Emile Blettery , Auteur ; Laetitia Delavoipiere, Auteur ; Frédéric Saly-Giocanti, Auteur ; Sylvaine Conord, Auteur ; Valérie Gouet-Brunet , Auteur ; Alexandre Devaux , Auteur ; Mathieu Brédif , Auteur ; Frédéric Moret, Auteur Année de publication : 2021 Projets : ITowns / Paparoditis, Nicolas, Alegoria / Gouet-Brunet, Valérie Article en page(s) : n° 1946 Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] analyse spatio-temporelle [Termes IGN] bidonville [Termes IGN] image aérienne [Termes IGN] morphologie urbaine [Termes IGN] Nanterre [Termes IGN] outil logiciel [Termes IGN] sciences sociales [Termes IGN] SIG 3D [Termes IGN] sociologie [Termes IGN] visualisation 3D [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Au milieu des années 1950 surgissent à Nanterre les premières cabanes de fortune abritant des travailleurs algériens. Bientôt, ces baraques informelles s’agrègent et finissent par former des ensembles urbains, présentés et administrés comme des bidonvilles, et la ville de Nanterre y est alors durablement associée. Cet article se propose de revenir sur une expérience de recherche interdisciplinaire autour de cet objet d’étude. Des chercheurs en histoire et en sociologie urbaine ont collaboré avec des informaticiens de l’IGN afin d’utiliser et d’enrichir une plateforme de spatialisation et de visualisation de données hétérogènes pour documenter l’histoire de ces bidonvilles et comprendre la formation et la permanence de ces lieux dans la mémoire collective actuelle. Numéro de notice : A2021-308 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/revuehn.1946 Date de publication en ligne : 01/05/2021 En ligne : https://doi.org/10.4000/revuehn.1946 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97709 [article]

Artificial intelligence / Eneko Osaba (2021)  

Public Titre : Artificial intelligence : Latest advances, new paradigms and novel applications Type de document : Monographie Auteurs : Eneko Osaba, Auteur ; Esther Villar-Rodriguez, Auteur ; Jesus L. Lobo, Auteur ; et al., Auteur Editeur : London [UK] : IntechOpen Année de publication : 2021 Importance : 158 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-1-83962-389-9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage profond [Termes IGN] exploration de données [Termes IGN] innovation [Termes IGN] modèle orienté agent [Termes IGN] organisme international [Termes IGN] reconnaissance de formes [Termes IGN] règlement [Termes IGN] réseau neuronal artificiel [Termes IGN] Spark [Termes IGN] système d'information Résumé : (éditeur) Artificial Intelligence (AI) is widely known as a knowledge field that aims to make computers, robots, or products that mimic the way humans think. In the current scientific community, AI is an intensively studied area composed of multiple branches. Historically, machine learning and optimization are two of the most studied fronts thanks to the development of novel and challenging research topics such as transfer optimization, swarm robotics, and drift detection and adaptation to evolving conditions in real-time. This book collects radically new theoretical insights, reporting recent developments and evincing innovative applications regarding AI methods in all fields of knowledge. It also presents works focused on new paradigms and novel branches of AI science. Note de contenu : 1- Introductory chapter: Artificial intelligence - Latest advances, new paradigms and novel applications 2- Big data framework using Spark architecture for dose optimization based on deep learning in medical imaging 3- Novelty detection methodology based on self-organizing maps for power quality monitoring 4- AI-powered workforce management and its future in India 5- Agent based load balancing in grid computing 6- A food recommender based on frequent sets of food mining using image recognition 7- The prospects for creating instruments for the coordination of activities of international organizations in the regulation of artificial intelligence 8- Artificial intelligence assisted innovation 9- Quest for I (intelligence) in AI (artificial intelligence): A non-elusive attempt Numéro de notice : 28633 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87770 En ligne : https://doi.org/10.5772/intechopen.87770 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99636

Developing graphics frameworks with Python and OpenGL / Lee Stemkoski (2021)  

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Efficiently distributed watertight surface reconstruction / Laurent Caraffa (2021)  

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Mise en place d’une infrastructure de données spatiales sur le risque de piqures de tiques / Lilian Calas (2021) 

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Flex-ER: A platform to evaluate interaction techniques for immersive visualizations / María-Jesús Lobo in Proceedings of the ACM on Human-Computer Interaction, Vol 4 (November 2020)  

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Provably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

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Spatio-temporal mobility and Twitter: 3D visualisation of mobility flows / Joaquín Osorio Arjona in Journal of maps, vol 16 n° 1 ([02/01/2020])  

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Cartographie des essences forestières à partir de séries temporelles d’images satellitaires à hautes résolutions : stabilité des prédictions, autocorrélation spatiale et cohérence avec la phénologie observée in situ / Nicolas Karasiak (2020)  

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Creation of inspirational Web Apps that demonstrate the functionalities offered by the ArcGIS API for JavaScript / Arthur Genet (2020) 

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Développement d’outils web de data visualization / Edson Olivares Medina (2020) 

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Distributed and parallel architectures for spatial data / Alberto Belussi (2020)  

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