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Toward a working taxonomy of geodesign practice / David Tulloch in Transactions in GIS, vol 21 n° 4 (August 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 4 (August 2017) . - pp 635 - 646 Titre : Toward a working taxonomy of geodesign practice Type de document : Article/Communication Auteurs : David Tulloch, Auteur Année de publication : 2017 Article en page(s) : pp 635 - 646 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données localisées [Termes IGN] données thématiques [Termes IGN] GeoDesign [Termes IGN] taxinomie [Termes IGN] traitement de données localisées Résumé : (Auteur) As an emerging area of study, geodesign discussions and publications have used practice as a vital source of inspiration and evidence of the early successes of the field. A closer examination of geodesign projects reveals some similarities and differences within the practice currently discussed as geodesign. Using 28 examples of geodesign projects, this paper identifies classes of examples that are similar. Based on the practical evidence represented in the examples, a 3-level classification system is proposed for providing a basic taxonomy for geodesign projects. This taxonomic system characterizes the classes based on: (1) whether the examples ceded some design control to the computer; (2) whether public participation is incorporated into the design process; and (3) whether it employs complex substantive models. This taxonomy offers a means for understanding and describing the diversity of geodesign while also raising new questions about the boundaries and structure of the field. Numéro de notice : A2017-627 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12245 En ligne : http://dx.doi.org/10.1111/tgis.12245 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86942 [article]

Reference data enhancement for geographic information retrieval using linked data / Tiago H. V. M. Moura in Transactions in GIS, vol 21 n° 4 (August 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 4 (August 2017) . - pp 683 - 700 Titre : Reference data enhancement for geographic information retrieval using linked data Type de document : Article/Communication Auteurs : Tiago H. V. M. Moura, Auteur ; Clodoveu A. Davis Jr., Auteur ; Frederico T. Fonseca, Auteur Année de publication : 2017 Article en page(s) : pp 683 - 700 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] base de connaissances [Termes IGN] recherche d'information géographique [Termes IGN] relation sémantique [Termes IGN] répertoire toponymique [Termes IGN] service web [Termes IGN] web des données Résumé : (Auteur) Gazetteers are instrumental in recognizing place names in documents such as Web pages, news, and social media messages. However, creating and maintaining gazetteers is still a complex task. Even though some online gazetteers provide rich sets of geographic names in planetary scale (e.g. GeoNames), other sources must be used to recognize references to urban locations, such as street names, neighborhood names or landmarks. We propose integrating Linked Data sources to create a gazetteer that combines a broad coverage of places with urban detail, including content on geographic and semantic relationships involving places, their multiple names and related non-geographic entities. Our final goal is to expand the possibilities for recognizing, disambiguating and filtering references to places in texts for geographic information retrieval (GIR) and related applications. The resulting ontological gazetteer, named LoG (Linked OntoGazetteer), is accessible through Web services by applications and research initiatives on GIR, text processing, named entity recognition and others. The gazetteer currently contains over 13 million places, 140 million attributes and relationships, and 4.5 million non-geographic entities. Data sources include GeoNames, Freebase, DBPedia and LinkedGeoData, which is based on OpenStreetMap data. An analysis on how these datasets overlap and complement one another is also presented. Numéro de notice : A2017-628 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12238 En ligne : http://dx.doi.org/10.1111/tgis.12238 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86943 [article]

SCOPED-W : SCalable Online Platform for extracting Environmental Data and Water-related model outputs / Yaniss Guigoz in Transactions in GIS, vol 21 n° 4 (August 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 4 (August 2017) . - pp 748 - 763 Titre : SCOPED-W : SCalable Online Platform for extracting Environmental Data and Water-related model outputs Type de document : Article/Communication Auteurs : Yaniss Guigoz, Auteur ; Pierre Lacroix, Auteur ; Elham Rouholahnejad, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 748 - 763 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] compatibilité [Termes IGN] données environnementales [Termes IGN] interopérabilité [Termes IGN] Noire, mer [Termes IGN] plateforme logicielle [Termes IGN] ressources en eau [Termes IGN] service web géographique [Termes IGN] web des données Résumé : (Auteur) This article presents SCOPED, an innovative approach for extracting environmental data using OGC services. In the field of water resource management, SCOPED-W (‘W’ for ‘Water’) is a method that was developed in the framework of EU/FP7 IASON and EOPOWER projects. This platform supports the collection of data required to build a Soil and Water Assessment Tool (SWAT) model and the uptake, spatialization and dissemination of raw data generated from the outputs of different SWAT models for the Black Sea region. Scientists are documenting the data served by the platform in ISO standardized metadata to support informed use. SCOPED-W primarily targets the community of SWAT users in the Black Sea region but it can easily be replicated in other geographical areas. Additionally, the SCOPED approach is based on data interoperability that makes it fully compatible with other domains of application as demonstrated here with three original use cases. The article also highlights the benefits of the approach for the GEO community and discusses future improvements for supporting integration with other platforms such as UNEP Live. Numéro de notice : A2017-629 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12227 En ligne : http://dx.doi.org/10.1111/tgis.12227 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86944 [article]

An evaluation of sampling and full enumeration strategies for Fisher Jenks classification in big data settings / Sergio J. Rey in Transactions in GIS, vol 21 n° 4 (August 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 4 (August 2017) . - pp 796 - 810 Titre : An evaluation of sampling and full enumeration strategies for Fisher Jenks classification in big data settings Type de document : Article/Communication Auteurs : Sergio J. Rey, Auteur ; Philip Stephens, Auteur ; Jason Laura, Auteur Année de publication : 2017 Article en page(s) : pp 796 - 810 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] autocorrélation spatiale [Termes IGN] carte choroplèthe [Termes IGN] classification contextuelle [Termes IGN] données massives [Termes IGN] échantillon [Termes IGN] méthode de Monte-Carlo [Termes IGN] précision de la classification [Termes IGN] simulation [Termes IGN] traitement de données localisées Résumé : (Auteur) Large data contexts present a number of challenges to optimal choropleth map classifiers. Application of optimal classifiers to a sample of the attribute space is one proposed solution. The properties of map classifiers methods are examined through a series of Monte Carlo simulations. The impacts of spatial autocorrelation, number of desired classes, and form of sampling are shown to have significant impacts on the accuracy of map classifications. Tradeoffs between improved speed of the sampling approaches and loss of accuracy are also considered. The results suggest the possibility of guiding the choice of classification scheme as a function of the properties of large data sets. Numéro de notice : A2017-630 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12236 En ligne : http://dx.doi.org/10.1111/tgis.12236 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86945 [article]