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Extracting urban functional regions from points of interest and human activities on location-based social networks / Song Gao in Transactions in GIS, vol 21 n° 3 (June 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 3 (June 2017) . - pp 446 - 467 Titre : Extracting urban functional regions from points of interest and human activities on location-based social networks Type de document : Article/Communication Auteurs : Song Gao, Auteur ; Krzysztof Janowicz, Auteur ; Helen Couclelis, Auteur Année de publication : 2017 Article en page(s) : pp 446 - 467 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] classification par nuées dynamiques [Termes IGN] connaissance thématique [Termes IGN] Etats-Unis [Termes IGN] point d'intérêt [Termes IGN] problème de Dirichlet [Termes IGN] réseau social géodépendant [Termes IGN] trace GPS [Termes IGN] triangulation de Delaunay [Termes IGN] zone urbaine Résumé : (Auteur) Data about points of interest (POI) have been widely used in studying urban land use types and for sensing human behavior. However, it is difficult to quantify the correct mix or the spatial relations among different POI types indicative of specific urban functions. In this research, we develop a statistical framework to help discover semantically meaningful topics and functional regions based on the co-occurrence patterns of POI types. The framework applies the latent Dirichlet allocation (LDA) topic modeling technique and incorporates user check-in activities on location-based social networks. Using a large corpus of about 100,000 Foursquare venues and user check-in behavior in the 10 most populated urban areas of the US, we demonstrate the effectiveness of our proposed methodology by identifying distinctive types of latent topics and, further, by extracting urban functional regions using K-means clustering and Delaunay triangulation spatial constraints clustering. We show that a region can support multiple functions but with different probabilities, while the same type of functional region can span multiple geographically non-adjacent locations. Since each region can be modeled as a vector consisting of multinomial topic distributions, similar regions with regard to their thematic topic signatures can be identified. Compared with remote sensing images which mainly uncover the physical landscape of urban environments, our popularity-based POI topic modeling approach can be seen as a complementary social sensing view on urban space based on human activities. Numéro de notice : A2017-623 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12289 En ligne : http://dx.doi.org/10.1111/tgis.12289 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86938 [article]

VGDI – advancing the concept: Volunteered geo-dynamic information and its benefits for population dynamics modeling / Christoph Aubrecht in Transactions in GIS, vol 21 n° 2 (April 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 2 (April 2017) Titre : VGDI – advancing the concept: Volunteered geo-dynamic information and its benefits for population dynamics modeling Type de document : Article/Communication Auteurs : Christoph Aubrecht, Auteur ; Dilek Özceylan Aubrecht, Auteur ; Joachim Ungar, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] connaissance thématique [Termes IGN] dimension temporelle [Termes IGN] données localisées des bénévoles [Termes IGN] extraction de données [Termes IGN] géomatique [Termes IGN] modèle dynamique Résumé : (auteur) The concept of Volunteered Geographic Information (VGI) has progressed from being an exotic prospect to making a profound impact on GIScience and geography in general, as initially anticipated. However, while massive and manifold data is continuously produced voluntarily and applications are built for information and knowledge extraction, the initially introduced concept of VGI lacks certain methodological perspectives in this regard which have not been fully elaborated. In this article we highlight and discuss an important gap in this concept, i.e. the lack of formal acknowledgment of temporal aspects. By coining the proposed advanced framework ‘Volunteered Geo-Dynamic Information’ (VGDI), we attempt to lay the ground for full conceptual and applied spatio-temporal integration. To illustrate that integrative approach of VGDI and its benefits, we describe the potential impact on the field of dynamic population distribution modeling. While traditional approaches in that domain rely on survey-based data and statistics as well as static geographic information, the use of VGDI enables a dynamic setup. Foursquare venue and user check-in data are presented for a test site in Lisbon, Portugal. Two core modules of spatio-temporal population assessment are thereby addressed, namely time use profiling and target zone characterization, motivated by the potential integration in existing population dynamics frameworks such as the DynaPop model. Numéro de notice : A2017-165 Affiliation des auteurs : non IGN Thématique : SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/DOI: 10.1111/tgis.12203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84699 [article]

Integrating user needs on misclassification error sensitivity into image segmentation quality assessment / Hugo Costa in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 6 (June 2015) . - pp 451 - 459 Titre : Integrating user needs on misclassification error sensitivity into image segmentation quality assessment Type de document : Article/Communication Auteurs : Hugo Costa, Auteur ; Giles M. Foody, Auteur ; Doreen S. Boyd, Auteur Année de publication : 2015 Article en page(s) : pp 451 - 459 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des besoins [Termes IGN] classification dirigée [Termes IGN] connaissance thématique [Termes IGN] objet géographique [Termes IGN] occupation du sol [Termes IGN] segmentation d'image [Termes IGN] similitude [Termes IGN] utilisateur Résumé : (auteur) Commonly the assessment of the quality of image segmentations used in object-based land cover classification uses the geometric match between the derived segmentation and a reference dataset. This paper argues that a more appropriate assessment of a segmentation is to also consider the thematic content of the objects generated. This allows the assessment to be tailored to the needs of the specific user. A new method for image segmentation quality assessment is described, which combines a traditional geometric-only method with the thematic similarity index (TSI), a metric that expresses the degree of thematic quality of objects from a user’s perspective. The perspectives of two users (a wolf researcher and a general user of land cover information) were adopted in a case study to demonstrate the new method. The results show that the new method allowed the production of more accurate land cover classifications for the two users than the use of the geometric-only approach Numéro de notice : A2015-976 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80059 [article]

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Thematic workshop on building an ontology of generalisation for on-demand mapping / William A Mackaness (2015)    

Public Titre : Thematic workshop on building an ontology of generalisation for on-demand mapping Type de document : Article/Communication Auteurs : William A Mackaness, Auteur ; Nick Gould, Auteur ; Sean Bechhofer, Auteur ; Dirk Burghardt, Auteur ; Cécile Duchêne , Auteur ; Robert Stevens, Auteur ; Guillaume Touya , Auteur Congrès : UKON 2015, 4th UK Ontology Network Meeting (14 avril 2015; Leeds, Royaume-Uni), Commanditaire ; GISRUK 2015, 23th GIS Research UK annual conference (15 - 17 avril 2015; School of Geography, University of Leeds, Leeds, Royaume-Uni), Commanditaire ; Congrès: ICA 2015, 19th workshop, Commission on Generalisation and Multiple Representation Thematic Workshop on building an Ontology of Generalisation for On-demand Mapping (26 - 27 mars 2015; Saint-Mandé, France), Auteur Editeur : UK ontology network Année de publication : 2015 Importance : 10 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartographie [Termes IGN] connaissance thématique [Termes IGN] ontologie [Vedettes matières IGN] Généralisation Mots-clés libres : cartographic-knowledge Résumé : (auteur) A workshop comprising experts in the field of map generalization came together with experts in ontological modelling in order to explore the role of ontologies in map generalization. A sequence of participatory activities identified the need for ontologies related to tasks, algorithms, data quality and truth, content selection, layout constraints, and geographical modelling (the set of relations among a set of map features). The workshop resulted in a deeper shared understanding of relationships between concepts that lie at the heart of map generalization. At the conclusion to the workshop attendees were tasked with developing case studies that will be shared via a wiki, and reported upon in a subsequent meeting devoted to ontological modelling for map generalization. This report is not exhaustive in its presentation of all the ideas and material presented at the workshop, but seeks to convey the over-arching methodology and its core findings. Numéro de notice : C2015-036 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://kartographie.geo.tu-dresden.de/downloads/ica-gen/ThemWorkshop/ThematicOn [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83291

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Domain adaptation for land use classification: A spatio-temporal knowledge reusing method / Yilun Liu in ISPRS Journal of photogrammetry and remote sensing, vol 98 (December 2014)

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 98 (December 2014) . - pp 133 - 144 Titre : Domain adaptation for land use classification: A spatio-temporal knowledge reusing method Type de document : Article/Communication Auteurs : Yilun Liu, Auteur ; Xia Li, Auteur Année de publication : 2014 Article en page(s) : pp 133 - 144 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] classificateur [Termes IGN] classification [Termes IGN] classification dirigée [Termes IGN] connaissance thématique [Termes IGN] données anciennes [Termes IGN] utilisation du sol Résumé : (Auteur) Land use classification requires a significant amount of labeled data, which may be difficult and time consuming to obtain. On the other hand, without a sufficient number of training samples, conventional classifiers are unable to produce satisfactory classification results. This paper aims to overcome this issue by proposing a new model, TrCbrBoost, which uses old domain data to successfully train a classifier for mapping the land use types of target domain when new labeled data are unavailable. TrCbrBoost adopts a fuzzy CBR (Case Based Reasoning) model to estimate the land use probabilities for the target (new) domain, which are subsequently used to estimate the classifier performance. Source (old) domain samples are used to train the classifiers of a revised TrAdaBoost algorithm in which the weight of each sample is adjusted according to the classifier’s performance. This method is tested using time-series SPOT images for land use classification. Our experimental results indicate that TrCbrBoost is more effective than traditional classification models, provided that sufficient amount of old domain data is available. Under these conditions, the proposed method is 9.19% more accurate. Numéro de notice : A2014-632 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75048 [article]

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Peut-on se fier aux cartes marines ? Considérations sur le statut des cartes marines au XVI [16e] / Marica Milanesi in Cartes & Géomatique, n° 216 (juin 2013)  

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Automatic revision of the control knowledge used by trial and error methods: Application to cartographic generalisation / Patrick Taillandier in Applied soft computing, vol 11 n° 2 (March 2011)  

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Vague spatio-thematic query processing: a qualitative approach to spatial closeness / R. Grütter in Transactions in GIS, vol 14 n° 2 (April 2010)  

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Discovering relative motion patterns in groups of moving point objects / P. Laube in International journal of geographical information science IJGIS, vol 19 n° 6 (july 2005)

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Thematic knowledge for the generalization of land use data / Wenxiu Gao in Cartographic journal (the), vol 41 n° 3 (December 2004)

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