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Grid-enabling Geographically Weighted Regression: a case study of participation in higher education in England / R. Harris in Transactions in GIS, vol 14 n° 1 (February 2010)  

Public [article]  inTransactions in GIS > vol 14 n° 1 (February 2010) . - pp 43 - 61 Titre : Grid-enabling Geographically Weighted Regression: a case study of participation in higher education in England Type de document : Article/Communication Auteurs : R. Harris, Auteur ; A. Singleton, Auteur ; D. Grose, Auteur ; C. Brunsdon, Auteur ; Paul A. Longley, Auteur Année de publication : 2010 Article en page(s) : pp 43 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Angleterre [Termes IGN] données démographiques [Termes IGN] données socio-économiques [Termes IGN] enseignement supérieur [Termes IGN] géocodage [Termes IGN] grille [Termes IGN] modélisation spatio-temporelle [Termes IGN] régression géographiquement pondérée Résumé : (Auteur) Geographically Weighted Regression (GWR) is a method of spatial statistical analysis used to explore geographical differences in the effect of one or more predictor variables upon a response variable. However, as a form of local analysis, it does not scale well to (especially) large data sets because of the repeated processes of fitting and then comparing multiple regression surfaces. A solution is to make use of developing grid infrastructures, such as that provided by the National Grid Service (NGS) in the UK, treating GWR as an "embarrassing parallel" problem and building on existing software platforms to provide a bridge between an open source implementation of GWR (in R) and the grid system. To demonstrate the approach, we apply it to a case study of participation in Higher Education, using GWR to detect spatial variation in social, cultural and demographic indicators of participation. Copyright Blackwell Publishing Numéro de notice : A2010-004 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2009.01181.x Date de publication en ligne : 17/01/2010 En ligne : https://doi.org/10.1111/j.1467-9671.2009.01181.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30200 [article]

Classification through consultation: public views of the geography of the e-society / Paul A. Longley in International journal of geographical information science IJGIS, vol 23 n° 6 (june 2009)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 23 n° 6 (june 2009) . - pp 737 - 763 Titre : Classification through consultation: public views of the geography of the e-society Type de document : Article/Communication Auteurs : Paul A. Longley, Auteur ; A. Singleton, Auteur Année de publication : 2009 Article en page(s) : pp 737 - 763 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] classification [Termes IGN] données démographiques [Termes IGN] erreur systématique [Termes IGN] géomatique web [Termes IGN] participation du public [Termes IGN] société de l'information [Termes IGN] technologies de l'information et de la communication Résumé : (Auteur) Although viewed by business and commerce as successful solutions, geodemographic profiling of neighbourhoods has attracted wide-ranging criticism in the academic literature. This paper addresses some specific concerns that arise because the derivation of classifications is rarely transparent and open to scrutiny or challenge. The substantive focus of the research reported in this paper is a nationwide geodemographic classification of how people engage with new information and communication technologies (ICTs). In response to the critique of geodemographics as a 'black box' technology, we describe how the classification was opened up to public scrutiny and how we conducted a major consultation exercise into the reliability of its results. We assess the message of the 50,000+ searches and 3952 responses collected during the consultation exercise, in terms of possible systematic errors in the shape and detail of the classification. Unusually for Internet-based surveys, we also investigate the likely reliability of the response information received and identify ways in which the outcome of consultation might be used to improve the classification. We believe that this is the first-ever large-scale consultation survey of the validity and remit of a geodemographic classification and that it may have wider implications for the creation of geodemographic classifications. Copyright Taylor & Francis Numéro de notice : A2009-316 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810701704652 En ligne : https://doi.org/10.1080/13658810701704652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29946 [article]

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