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Assessing the veracity of methods for extracting place semantics from Flickr tags / William A Mackaness in Transactions in GIS, vol 17 n° 4 (August 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 4 (August 2013) . - pp 544 - 562 Titre : Assessing the veracity of methods for extracting place semantics from Flickr tags Type de document : Article/Communication Auteurs : William A Mackaness, Auteur ; Omair Chaudhry, Auteur Année de publication : 2013 Article en page(s) : pp 544 - 562 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données d'images [Termes IGN] données spatiotemporelles [Termes IGN] exploration de données [Termes IGN] grand public [Termes IGN] image Flickr [Termes IGN] inférence [Termes IGN] information sémantique [Termes IGN] milieu urbain [Termes IGN] régression logistique [Termes IGN] segmentation sémantique Résumé : (Auteur) The volume and potential value of user generated content (UGC) is ever growing. Multiply sourced, its value is greatly increased by the inclusion of metadata that adequately and accurately describes that content – particularly if such data are to be integrated with more formal data sets. Typically, digital photography is tagged with location and attribute information that variously describe the location, events or objects in the image. Often inconsistent and incomplete, these attributes reflect concepts at a range of geographic scales. From a spatial data integration perspective, the information relating to “place” is of primary interest. The challenge therefore is in selecting the most appropriate tags that best describe the geography of the image. This article presents a methodology based on an information retrieval technique that separates out “place related tags” from the remainder of the tags. Different scales of geography are identified by varying the size of the sampling area within which the imagery falls. This is applied in the context of urban environments, using Flickr imagery. Empirical analysis is then used to assess the correctness of the chosen tags (i.e. whether the tag correctly describes the geographic region in which the image was taken). Logistic regression and Bayesian inference are used to attach a probability value to each place tag. The high correlation values achieved indicate that this methodology can be used to automatically select place tags for any urban region and thus hierarchically structure UGC in order that it can be semantically integrated with other data sources. Numéro de notice : A2013-471 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12043 Date de publication en ligne : 28/05/2013 En ligne : https://doi.org/10.1111/tgis.12043 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32609 [article]

Automatic classification of retail spaces from a large scale topographic database / William A Mackaness in Transactions in GIS, vol 15 n° 3 (July 2011)  

Public [article]  inTransactions in GIS > vol 15 n° 3 (July 2011) . - pp 291 - 307 Titre : Automatic classification of retail spaces from a large scale topographic database Type de document : Article/Communication Auteurs : William A Mackaness, Auteur ; Omair Chaudhry, Auteur Année de publication : 2011 Article en page(s) : pp 291 - 307 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] base de données topographiques [Termes IGN] classification automatique [Termes IGN] classification bayesienne [Termes IGN] classification floue [Termes IGN] commerce de détail [Termes IGN] grande échelle Résumé : (Auteur) There is considerable interest in understanding the distribution patterns of different types of retail space, over time, and doing so at a national scale. Yet a lack of suitable data, coupled with poor classification schemas, has stymied efforts to create such a national perspective. This research reports on metrics and classification methodologies that have been applied to large scale topographic data, that afford a systematic classification of certain retail spaces potentially at the national coverage. By analysing the form, composition, extent and patterns of buildings within retail spaces, together with their degree of centrality and levels of access, we demonstrate that it is possible to classify different types of retail space. The research illustrates the utility of fine scale topographic data beyond mere mapping. The article compares three methodologies used for classification (Boolean, fuzzy logic and Bayesian modelling) and evaluates them through comparison with known locations of various retail types as a way of assessing the validity of these approaches. The quality of the results are good, though the work highlights the inconsistency in definitions that currently exist – reflecting, as much as anything, the shifting sands of definitions of various retail spaces that ebb and flow according to consumer needs, and the ambitions of urban planners. Numéro de notice : A2011-225 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2011.01259.x Date de publication en ligne : 06/06/2011 En ligne : https://doi.org/10.1111/j.1467-9671.2011.01259.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31003 [article]

Automatic identification of high streets and classification of urban land use in large scale topographic database / Omair Chaudhry (2010) 

Public contenu dans Proceedings of the GIS Research UK, 18th annual conference, University College London, 14th - 16th April 2010 / Muki M. Haklay (2010)     Titre : Automatic identification of high streets and classification of urban land use in large scale topographic database Type de document : Article/Communication Auteurs : Omair Chaudhry, Auteur ; Médéric Gravelle, Auteur ; Nicolas Regnauld , Auteur Editeur : Geographical Information Science Research - UK GISRUK Année de publication : 2010 Conférence : GISRUK 2010, 18th GIS Research UK annual conference 14/04/2010 16/04/2010 Londres Royaume-Uni Open access proceedings Langues : Anglais (eng) Descripteur : [Termes IGN] autoroute [Termes IGN] base de données topographiques [Termes IGN] grande échelle [Termes IGN] identification automatique [Termes IGN] utilisation du sol [Vedettes matières IGN] Généralisation Numéro de notice : C2010-021 Affiliation des auteurs : COGIT+Ext (1988-2011) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83788

Documents numériques

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Representing forested regions at small scales: automatic derivation from very large scale data / William A Mackaness in Cartographic journal (the), vol 45 n° 1 (February 2008)  

Public [article]  inCartographic journal (the) > vol 45 n° 1 (February 2008) . - pp 6 - 17 Titre : Representing forested regions at small scales: automatic derivation from very large scale data Type de document : Article/Communication Auteurs : William A Mackaness, Auteur ; S. Perikleous, Auteur ; Omair Chaudhry, Auteur Année de publication : 2008 Article en page(s) : pp 6 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] 1:250.000 [Termes IGN] carte dérivée [Termes IGN] forêt tempérée [Termes IGN] généralisation automatique de données [Termes IGN] généralisation cartographique automatisée [Termes IGN] grande échelle [Termes IGN] Ordnance Survey (UK) [Termes IGN] petite échelle [Termes IGN] Royaume-Uni [Termes IGN] service web géographique Résumé : (Auteur) As with any class of feature, it is important to be able to view woodland or forest at multiple levels of detail. At the detailed level, a map can show clusters of trees, tree types, tracks and paths; at the small scale, say 1:250 000, we can discern broad patterns of forests and other land use, which can inform planners and act as input to land resource models. Rather than store such information in separate databases (requiring multiple points of maintenance), the vision is that the information has a single point of storage and maintenance, and that from this detailed level, various, more generalised forms can be automatically derived. This paper presents a methodology and algorithm for automatically deriving forest patches suitable for representation at 1:250 000 scale directly from a detailed dataset. In addition to evaluation of the output, the paper demonstrates how such algorithms can be shared and utilised via 'generalisation web services', arguing that the sharing of such algorithms can help accelerate developments in map generalisation, and increase the uptake of research solutions within commercial systems. Copyright British Cartographic Society Numéro de notice : A2008-130 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/000870408X276576 En ligne : https://doi.org/10.1179/000870408X276576 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29125 [article]

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