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Relative space-based GIS data model to analyze the group dynamics of moving objects / Mingxiang Feng in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 153 (July 2019) . - pp 74 - 95 Titre : Relative space-based GIS data model to analyze the group dynamics of moving objects Type de document : Article/Communication Auteurs : Mingxiang Feng, Auteur ; Shih-Lung Shaw, Auteur ; Zhixiang Fang, Auteur ; Hao Cheng, Auteur Année de publication : 2019 Article en page(s) : pp 74 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] base de données orientée objet [Termes descripteurs IGN] modèle conceptuel de données [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] SIG dynamique [Termes descripteurs IGN] trajectoire [Termes descripteurs IGN] UML Résumé : (Auteur) The relative motion of moving objects is an essential research topic in geographical information science (GIScience), which supports the innovation of geodatabases, spatial indexing, and geospatial services. This analysis is very popular in the domains of urban governance, transportation engineering, logistics and geospatial information services for individuals or industrials. Importantly, data models of moving objects are one of the most crucial approaches to support the analysis for dynamic relative motion between moving objects, even in the age of big data and cloud computing. Traditional geographic information systems (GIS) usually organize moving objects as point objects in absolute coordinated space. The derivation of relative motions among moving objects is not efficient because of the additional geo-computation of transformation between absolute space and relative space. Therefore, current GISs require an innovative approach to directly store, analyze and interpret the relative relationships of moving objects to support their efficient analysis. This paper proposes a relative space-based GIS data model of moving objects (RSMO) to construct, operate and analyze moving objects’ relationships and introduces two algorithms (relationship querying and relative relationship dynamic pattern matching) to derive and analyze the dynamic relationships of moving objects. Three scenarios (epidemic spreading, tracker finding, and motion-trend derivation of nearby crowds) are implemented to demonstrate the feasibility of the proposed model. The experimental results indicates the execution times of the proposed model are approximately 5–50% those of the absolute GIS method for the same function of these three scenarios. It’s better computational performance of the proposed model when analyzing the relative relationships of moving objects than the absolute methods in a famous commercial GIS software based on this experimental results. The proposed approach fills the gap of traditional GIS and shows promise for relative space-based geo-computation, analysis and service. Numéro de notice : A2019-261 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.002 date de publication en ligne : 15/05/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93074 [article]

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A conceptual framework for studying collective reactions to events in location-based social media / Alexander Dunkel in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 780 - 804 Titre : A conceptual framework for studying collective reactions to events in location-based social media Type de document : Article/Communication Auteurs : Alexander Dunkel, Auteur ; Gennady Andrienko, Auteur ; Natalia Andrienko, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 780 - 804 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] diffusion de l'information [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] événement [Termes descripteurs IGN] hypercube [Termes descripteurs IGN] information géographique [Termes descripteurs IGN] modèle conceptuel de données [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] traitement interactif Résumé : (Auteur) Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events. Numéro de notice : A2019-216 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1546390 date de publication en ligne : 18/11/2018 En ligne : https://doi.org/10.1080/13658816.2018.1546390 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92688 [article]

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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)  

Public [article]  inTransactions in GIS > vol 23 n° 1 (February 2019) . - pp 22 - 47 Titre : A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data Type de document : Article/Communication Auteurs : Luis Vilches-Blazquez, Auteur ; Jhonny Saavedra, Auteur Année de publication : 2019 Article en page(s) : pp 22 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] cadre conceptuel [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] données multisources [Termes descripteurs IGN] GML [Termes descripteurs IGN] interopérabilité [Termes descripteurs IGN] partage de données localisées [Termes descripteurs IGN] RDF [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] Web des données [Termes descripteurs IGN] Web Feature Service [Termes descripteurs IGN] web sémantique Résumé : (auteur) Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi‐structured datasets, and often use distinct data models, are encoded using ad‐hoc vocabularies, and sometimes are being published in non‐standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non‐expert users. Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain. Numéro de notice : A2019-089 Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12496 date de publication en ligne : 28/11/2018 En ligne : https://doi.org/10.1111/tgis.12496 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92236 [article]

GIS approach to publishing commonfacilities plans of land consolidation in the Czech Republic / Arnošt Müller in Geodetski vestnik, vol 62 n° 4 (December 2018 - February 2019)  

Public [article]  inGeodetski vestnik > vol 62 n° 4 (December 2018 - February 2019) . - pp 641 - 656 Titre : GIS approach to publishing commonfacilities plans of land consolidation in the Czech Republic Type de document : Article/Communication Auteurs : Arnošt Müller, Auteur Année de publication : 2018 Article en page(s) : pp 641 - 656 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes descripteurs IGN] base de données foncières [Termes descripteurs IGN] base de données localisées [Termes descripteurs IGN] cadastre étranger [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] données hydrographiques [Termes descripteurs IGN] érosion [Termes descripteurs IGN] modèle orienté objet [Termes descripteurs IGN] normalisation [Termes descripteurs IGN] paysage agricole [Termes descripteurs IGN] remembrement agricole [Termes descripteurs IGN] République Tchèque Résumé : (auteur) This paper introduces the process of land consolidation and current use of geographic information systems (GIS) in the Czech Republic. Contemporary land consolidation in the Central European region, unlike Western Europe, has been implemented relatively recently, hence there is no contingency or previous experience to build upon. This brings about an opportunity for a modern design of GIS‐based land consolidation. Although the design of land consolidation projects in the Czech Republic is mainly conducted in CAD software, this paper focuses on the utilisation of GIS and stresses the importance of standardisation of land consolidation data. Standardisation allows automatic processing of data as well as effortless publishing. The author proposes a new object‐oriented data model of the landscape plan (Common Facilities Plan), which allows for the storing of such plans in a central spatial database and adding attribute information to each object, thus providing analysis of the data in a GIS. The data model alongside data standardisation lays the groundwork for the architectural proposal of a new GIS (geoportal) of Common Facilities Plans. Numéro de notice : A2019-017 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.15292/geodetski-vestnik.2018.04.641-656 date de publication en ligne : 03/12/2018 En ligne : https://doi.org/10.15292/geodetski-vestnik.2018.04.641-656 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91631 [article]

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Scene classification based on multiscale convolutional neural network / Yanfei Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7109 - 7121 Titre : Scene classification based on multiscale convolutional neural network Type de document : Article/Communication Auteurs : Yanfei Liu, Auteur ; Yanfei Zhong, Auteur ; Qianqing Qin, Auteur Année de publication : 2018 Article en page(s) : pp 7109 - 7121 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image multidimensionnelle [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] mesure de similitude [Termes descripteurs IGN] modèle orienté objet Résumé : (auteur) With the large amount of high-spatial resolution images now available, scene classification aimed at obtaining high-level semantic concepts has drawn great attention. The convolutional neural networks (CNNs), which are typical deep learning methods, have widely been studied to automatically learn features for the images for scene classification. However, scene classification based on CNNs is still difficult due to the scale variation of the objects in remote sensing imagery. In this paper, a multiscale CNN (MCNN) framework is proposed to solve the problem. In MCNN, a network structure containing dual branches of a fixed-scale net (F-net) and a varied-scale net (V-net) is constructed and the parameters are shared by the F-net and V-net. The images and their rescaled images are fed into the F-net and V-net, respectively, allowing us to simultaneously train the shared network weights on multiscale images. Furthermore, to ensure that the features extracted from MCNN are scale invariant, a similarity measure layer is added to MCNN, which forces the two feature vectors extracted from the image and its corresponding rescaled image to be as close as possible in the training phase. To demonstrate the effectiveness of the proposed method, we compared the results obtained using three widely used remote sensing data sets: the UC Merced data set, the aerial image data set, and the google data set of SIRI-WHU. The results confirm that the proposed method performs significantly better than the other state-of-the-art scene classification methods. Numéro de notice : A2018-556 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2848473 date de publication en ligne : 26/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2848473 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91660 [article]

Ontologies pour représenter l’évolution des découpages territoriaux statistiques / Camille Bernard in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)  

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A spatio-temporal scenario model for emergency decision / Cheng Liu in Geoinformatica [en ligne], vol 22 n° 2 (April 2018)  

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Analyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)

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Geospatial data on the web / Linda Van Den Brink (2018)    

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Harmonisation de données géographiques hétérogènes décrivant le réseau d’assainissement francilien / Laurie Nino (2018)

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Researches about the living condition in Ulaanbaatar with mapping developments based on a participatory approach / Paul Roux (2018) 

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Valorisation des référentiels géographiques de Nanterre / Rémi Rouger (2018) 

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Quantifying the sources of epistemic uncertainty in model predictions of insect disturbances in an uncertain climate / David R. Gray in Annals of Forest Science [en ligne], vol 74 n° 3 (September 2017)  

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Extrapolated georeferencing of high-resolution satellite imagery based on the strip constraint / Jinshan Cao in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 7 (July 2017)  

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Knowledge-based data enrichment for HBIM: Exploring high-quality models using the semantic-web / Ramona Quattrini in Journal of Cultural Heritage, vol ([01/06/2017])  

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