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A GIS representation framework for location-based social media activities / Xuebin Wei in Transactions in GIS, vol 26 n° 3 (May 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 3 (May 2022) . - pp 1444 - 1464 Titre : A GIS representation framework for location-based social media activities Type de document : Article/Communication Auteurs : Xuebin Wei, Auteur ; Xiaobai Yao, Auteur Année de publication : 2022 Article en page(s) : pp 1444 - 1464 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] cadre conceptuel [Termes IGN] données issues des réseaux sociaux [Termes IGN] environnement géographique virtuel [Termes IGN] Facebook [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] ontologie [Termes IGN] relations sociales [Termes IGN] représentation des données [Termes IGN] réseau social géodépendant [Termes IGN] système d'information géographique [Termes IGN] Time-geography Résumé : (auteur) The past couple of decades have witnessed tremendous growth of location-based social media activities (LBSMA) data in virtual spaces, including virtual geographic environments. Such data become innovative resources for the analysis of human activities. Meanwhile, a shift of human interactions from geographical spaces to virtual spaces has been observed. Although this is an exciting research opportunity, it also imposes significant challenges on GIScience, as current GIS representation models are no longer sufficient to handle the increased sophistication of human activities data. This research formalizes an ontology for LBSMA data and a conceptual framework for representing such data in GIS. The framework contributes to GIScience as it enables interconnections of human activities in both the physical and virtual worlds to be represented, organized, retrieved, analyzed, and visualized. The proposed GIS representation model integrates a social dimension into the existing spatial–temporal representation models and allows data analysis in the spatial–temporal–social (STS) dimensions. The research tested this conceptual framework with a prototype and a case study using Facebook data. The prototype and the case study prove that the proposed framework can significantly enhance GIS capabilities for data organization, retrieval, and analysis of LBSMA data in STS dimensions. Numéro de notice : A2022-477 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1111/tgis.12929 Date de publication en ligne : 02/05/2022 En ligne : https://doi.org/10.1111/tgis.12929 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100825 [article]

Cross-dataset learning for generalizable land use scene classification / Dimitri Gominski (2022)  

Public Titre : Cross-dataset learning for generalizable land use scene classification Type de document : Article/Communication Auteurs : Dimitri Gominski , Auteur ; Valérie Gouet-Brunet , Auteur ; Liming Chen, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2022 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : EarthVision 2022, Large Scale Computer Vision for Remote Sensing Imagery, workshop joint to CVPR 2022 19/06/2022 24/06/2022 New Orleans Louisiane - Etats-Unis OA Proceedings Importance : 10 p. Note générale : EarthVision'22 workshop in conjunction with the Computer Vision and Pattern Recognition (CVPR) 2022 Conference Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] cadre conceptuel [Termes IGN] descripteur [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] intelligence artificielle [Termes IGN] scène urbaine [Termes IGN] segmentation sémantique [Termes IGN] utilisation du sol Résumé : (auteur) Few-shot and cross-domain land use scene classification methods propose solutions to classify unseen classes or uneen visual distributions, but are hardly applicable to real-world situations due to restrictive assumptions. Few-shot methods involve episodic training on restrictive training subsets with small feature extractors, while cross-domain methods are only applied to common classes. The underlying challenge remains open: can we accurately classify new scenes on new datasets? In this paper, we propose a new framework for few-shot, cross-domain classification. Our retrieval-inspired approach exploits the interrelations in both the training and testing data to output class labels using compact descriptors. Results show that our method can accurately produce land-use predictions on unseen datasets and unseen classes, going beyond the traditional few-shot or cross-domain formulation, and allowing cross-dataset training. Numéro de notice : C2022-031 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : en attente En ligne : https://openaccess.thecvf.com/content/CVPR2022W/EarthVision/papers/Gominski_Cros [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101087

A generic information framework for decision-making in a forest-based bio-economy / Jean-Baptiste Pichancourt in Annals of Forest Science [en ligne], vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 4 (December 2021) . - n° 97 Titre : A generic information framework for decision-making in a forest-based bio-economy Type de document : Article/Communication Auteurs : Jean-Baptiste Pichancourt, Auteur ; Rodolphe Bauer, Auteur ; Antoine Billard, Auteur ; Maree Brennan, Auteur ; Sylvain Caurla, Auteur ; Antoine Colin , Auteur ; Adrien Contini, Auteur ; Sylvain Cosgun, Auteur ; Henri E. Cuny , Auteur ; Stéphane Dumarçay, Auteur ; Mathieu Fortin, Auteur ; Philippe Gérardin, Auteur ; David Jean Hentges, Auteur ; Fleur Longuetaud, Auteur ; Béatrice Richard, Auteur ; Holger Wernsdörfer, Auteur ; Francis Colin, Auteur Année de publication : 2021 Projets : ExtraFor-Est / Gouet-Brunet, Valérie Article en page(s) : n° 97 Note générale : bibliographie It has been supported by the following funding agencies: the French Ministry of Agriculture (contractual project EXTRAFOR-EST/MAAF), the Lorraine-FEDER (contractual project EXTRAFOR-EST/FEDER), the French National Research Agency (ANR) as part of the Investissements d’Avenir programme (ANR-11-LABX-0002-01), the Lab of Excellence ARBRE (contractual project BARK-TAN-BIO). ADEME and Grand Est Region supported a PhD thesis on basic density of wood tissues. Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] aide à la décision [Termes IGN] biomasse forestière [Termes IGN] cadre conceptuel [Termes IGN] économie forestière [Termes IGN] molécule [Termes IGN] ressources forestières [Vedettes matières IGN] Economie forestière Résumé : (auteur) We present a methodological framework that both scientists and supply chain actors can mobilise to organise information at different scales of observation, and further make informed decisions regarding the supply and extraction of bio-molecules from forest biomass. We demonstrate its usefulness for extracting bio-molecules contained in silver fir growing in France. Context : Numerous bio-active molecules can be extracted from trees at an industrial scale. Supply chain actors play a central role in this emerging bio-economy. However, they do not have enough information and tools to make informed decisions with respect to species, growing locations, or identities of potential suppliers of relevant wood biomass. Aims : We explore and demonstrate an information chain and methodological framework that can help make three critical decisions regarding the selection of (1) the species containing the desired bio-molecules, (2) the locations where the resource is collected, and (3) the supply chain partners and types of industrial wood by-products necessary to obtain sufficient biomass for industrial extraction. Methods : The methodological framework provides detailed guidelines and references to select the right combination of sampling protocol, allometric models, chemical analyses, GIS tools, and forest growth and supply chain models in order to produce information for the three decision steps within various regional contexts. Results : We apply the framework within the context of supply chain actors who are interested in estimating the quantity and diversity of bio-molecules contained in silver fir (Abies alba Mill.) growing in the Grand Est region of France. We show how conflicting environmental, legal and economic constraints can affect the results. We discuss future challenges that need to be tackled to improve the methodological framework. Conclusion : This study represents a highly detailed overview of the potential bio-molecules contained in a tree species, from its natural habitat or plantation to the end of the regional supply chain. It also represents a step towards the development of a generic knowledge infrastructure and methodology that is necessary to solve various decision-making problems regarding the industrial supply and extraction of high-value bio-molecules. Numéro de notice : A2021-797 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01110-y En ligne : https://doi.org/10.1007/s13595-021-01110-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99200 [article]

Consistency assessment for open geodata integration: an ontology-based approach / Linfang Ding in Geoinformatica [en ligne], vol 25 n° 4 (October 2021)  

Public [article]  inGeoinformatica [en ligne] > vol 25 n° 4 (October 2021) . - pp 733 - 758 Titre : Consistency assessment for open geodata integration: an ontology-based approach Type de document : Article/Communication Auteurs : Linfang Ding, Auteur ; Guohui Xiao, Auteur ; Diego Calvanese, Auteur ; Liqiu Meng, Auteur Année de publication : 2021 Article en page(s) : pp 733 - 758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] cadre conceptuel [Termes IGN] cohérence des données [Termes IGN] données hétérogènes [Termes IGN] données localisées [Termes IGN] données ouvertes [Termes IGN] intégration de données [Termes IGN] Italie [Termes IGN] ontologie Résumé : (auteur) Integrating heterogeneous geospatial data sources is important in various domains like smart cities, urban planning and governance, but remains a challenging research problem. In particular, the production of high-quality integrated data from multiple sources requires an understanding of their respective characteristics and a systematic assessment of the consistency within and between the data sources. In order to perform the assessment, the data has to be placed on a common ground. However, in practice, heterogeneous geodata are often provided in diverse formats and organized in significantly different structures. In this work, we propose a framework that uses an ontology-based approach to overcome the heterogeneity by means of a domain ontology, so that consistency rules can be evaluated at the unified ontological representation of the data sources. In our case study, we use open governmental data from Open Data Portals (ODPs) and volunteered geographic information from OpenStreetMap (OSM) as two test data sources in the area of the province of South Tyrol, Italy. Our preliminary experiment shows that the approach is effective in detecting inconsistencies within and between ODP and OSM data. These findings provide valuable insights for a better combined usage of these datasets. Numéro de notice : A2021-967 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-019-00384-9 Date de publication en ligne : 03/12/2019 En ligne : https://doi.org/10.1007/s10707-019-00384-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100388 [article]

A framework to manage uncertainty in the computation of waste collection routes after a flood / Arnaud Le Guilcher in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2021 (July 2021)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-4-2021 (July 2021) . - pp 61 - 68 Titre : A framework to manage uncertainty in the computation of waste collection routes after a flood Type de document : Article/Communication Auteurs : Arnaud Le Guilcher , Auteur ; Sofiane Martel, Auteur ; Mickaël Brasebin , Auteur ; Yann Méneroux , Auteur Année de publication : 2021 Projets : 1-Pas de projet / Gouet-Brunet, Valérie Conférence : ISPRS 2021, Commission 4, 24th ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice on-line France OA Annals Commission 4 Article en page(s) : pp 61 - 68 Note générale : biblographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] cadre conceptuel [Termes IGN] calcul d'itinéraire [Termes IGN] catastrophe naturelle [Termes IGN] collecte des déchets [Termes IGN] discrétisation spatiale [Termes IGN] incertitude géométrique [Termes IGN] inondation [Termes IGN] programmation stochastique [Termes IGN] variable aléatoire Résumé : (auteur) In this paper, we describe a framework to find a good quality waste collection tour after a flood, without having to solve a complicated optimization problem from scratch in limited time. We model the computation of a waste collection tour as a capacitated routing problem, on the vertices or on the edges of a graph, with uncertain waste quantities and uncertain road availability. Multiple models have been conceived to manage uncertainty in routing problems, and we build on the ideas of discretizing the uncertain parameters and computing master solutions that can be adapted to propose an original method to compute efficient solutions. We first introduce our model for the progressive removal of the uncertainty, then outline our method to compute solutions: our method first considers a low-dimensional set of random variables that govern the behaviour of the problem parameters, discretizes these variables and computes a solution for each discrete point before the flood, and then uses these solutions as a basis to build operational solutions when there are enough information about the parameters of the routing problem. We then give computational tools to implement this method. We give a framework to compute the basis of solutions in an efficient way, by computing all the solutions simultaneously and sharing information (that can lead to good quality solutions) between the different problems based on how close their parameters are, and we also describe how real solutions can be derived from this basis. Our main contributions are our model for the progressive removal of uncertainty, our multi-step method to compute efficient solutions, and our intrusive framework to compute solutions on the discrete grid of parameters. Numéro de notice : A2021-316 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-4-2021-61-2021 En ligne : https://doi.org/10.5194/isprs-annals-V-4-2021-61-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97946 [article]

The urban governance configuration: A conceptual framework for understanding complexity and enhancing transitions to greater sustainability in cities / Isa Baud in Geography compass, vol 15 n° 5 (May 2021)  

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Pyramidal framework: guidance for the next generation of GIS spatial-temporal models / Cyril Carré in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)  

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Understanding the role of individual units in a deep neural network / David Bau in Proceedings of the National Academy of Sciences of the United States of America PNAS, vol 117 n° 48 (1 December 2020)  

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Understanding governance dynamics: The governing system of spatial data infrastructures / Jaap-Willem Sjoukema in International Journal of Spatial Data Infrastructures Research, vol 15 (Year 2020)  

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Smoothing algorithms for navigation, localisation and mapping based on high-grade inertial sensors / Paul Chauchat (2020)  

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Torch-Points3D: A modular multi-task framework for reproducible deep learning on 3D point clouds / Thomas Chaton (2020)  

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A cognitive framework for road detection from high-resolution satellite images / Naveen Chandra in Geocarto international, vol 34 n° 8 ([15/06/2019])  

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A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data / Luis Vilches-Blazquez in Transactions in GIS, vol 23 n° 1 (February 2019)  

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Mapping experience: Age and indigeneity as mediating factors in users’ experiences with the Algonquian linguistic atlas / Adam Stone in Cartographica, vol 53 n° 4 (winter 2018)  

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A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information : The case study of volunteered personal traces analysis against transport network data / Gloria Bordogna in Geo-spatial Information Science, vol 21 n° 3 (October 2018)  

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