Centre de documentation
scientifique

Interactive display of surnames distributions in historic and contemporary Great Britain / Justin Van Dijk in Journal of maps, vol 16 n° 1 ([02/01/2020])  

Public [article]  inJournal of maps > vol 16 n° 1 [02/01/2020] . - pp 68 - 76 Titre : Interactive display of surnames distributions in historic and contemporary Great Britain Type de document : Article/Communication Auteurs : Justin Van Dijk, Auteur ; Paul A. Longley, Auteur Année de publication : 2020 Article en page(s) : pp 68 - 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] anthroponymie [Termes IGN] base de données historiques [Termes IGN] base de données spatiotemporelles [Termes IGN] carte interactive [Termes IGN] données démographiques [Termes IGN] estimation par noyau [Termes IGN] géovisualisation [Termes IGN] Grande-Bretagne [Termes IGN] onomastique [Termes IGN] PostgreSQL Résumé : (auteur) We introduce a method to calculate and store approximately 1.2 million surname distributions calculated for surnames found in Great Britain for six years of historic population data and 20 years of contemporary population registers compiled from various consumer sources. We subsequently show how this database can be incorporated into an interactive web-environment specifically designed for the public dissemination of detailed surname statistics. Additionally, we argue that the database can be used in the quantitative analysis of surnames in Great Britain and potentially offer valuable insights into processes of contagious and hierarchical diffusion of populations as well as the regional distinctiveness of demographic change and stasis. Numéro de notice : A2020-644 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1746418 Date de publication en ligne : 04/04/2020 En ligne : https://doi.org/10.1080/17445647.2020.1746418 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96070 [article]

Geospatial Analysis / Michael J. de Smith (2018)  

Public Titre : Geospatial Analysis : a comprehensive guide to principles, techniques and software tools Type de document : Guide/Manuel Auteurs : Michael J. de Smith, Éditeur scientifique ; Michael F. Goodchild, Éditeur scientifique ; Paul A. Longley, Éditeur scientifique Mention d'édition : 6th edition Editeur : The Winchelsea Press Année de publication : 2018 Importance : 748 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] exploration de données [Termes IGN] géostatistique Index. décimale : 37.20 Analyse spatiale et ses outils Résumé : (Editeur) [Introduction] In this Guide we address the full spectrum of spatial analysis and associated modeling techniques that are provided within currently available and widely used geographic information systems (GIS) and associated software. Collectively such techniques and tools are often now described as geospatial analysis, although we use the more common form, spatial analysis, in most of our discussions. The term ‘GIS’ is widely attributed to Roger Tomlinson and colleagues, who used it in 1963 to describe their activities in building a digital natural resource inventory system for Canada (Tomlinson 1967, 1970). The history of the field has been charted in an edited volume by Foresman (1998) containing contributions by many of its early protagonists. A timeline of many of the formative influences upon the field up to the year 2000 is available via: http://www.casa.ucl.ac.uk/gistimeline/; and is provided by Longley et al. (2010). Useful background information may be found at the GIS History Project website (NCGIA): http://www.ncgia.buffalo.edu/gishist/. Each of these sources makes the unassailable point that the success of GIS as an area of activity has fundamentally been driven by the success of its applications in solving real world problems. Many applications are illustrated in Longley et al. (Chapter 2, “A gallery of applications”). In a similar vein the web site for this Guide provides companion material focusing on applications. Amongst these are a series of sector‑specific case studies drawing on recent work in and around London (UK), together with a number of international case studies. In order to cover such a wide range of topics, this Guide has been divided into a number of main sections or chapters. These are then further subdivided, in part to identify distinct topics as closely as possible, facilitating the creation of a web site from the text of the Guide. Hyperlinks embedded within the document enable users of the web and PDF versions of this document to navigate around the Guide and to external sources of information, data, software, maps, and reading materials. [...] Note de contenu : 1. Introduction and terminology 2. Conceptual Frameworks for Spatial Analysis 3. Methodological Context 4. Building Blocks of Spatial Analysis 5. Data Exploration and Spatial Statistics 6. Surface and Field Analysis 7. Network and Location Analysis 8. Geocomputational methods and modeling 9. Afterword - Big Data and Geospatial Analysis Numéro de notice : 22863 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Manuel En ligne : http://www.spatialanalysisonline.com/HTML/index.html Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89308

Geo-temporal Twitter demographics / Paul A. Longley in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 1-2 (January - February 2016) . - pp 369 - 389 Titre : Geo-temporal Twitter demographics Type de document : Article/Communication Auteurs : Paul A. Longley, Auteur ; Muhammad Adnan, Auteur Année de publication : 2016 Article en page(s) : pp 369 - 389 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données démographiques [Termes IGN] données issues des réseaux sociaux [Termes IGN] données spatiotemporelles [Termes IGN] entropie de Shannon [Termes IGN] géographie humaine [Termes IGN] Londres [Termes IGN] milieu urbain [Termes IGN] Twitter Résumé : (auteur) This paper seeks and uses highly disaggregate social media sources to characterize Greater London in terms of flows of people with modelled individual characteristics, as well as conventional measures of land use morphology and night-time residence. We conduct three analyses. First, we use the Shannon Entropy measure to characterize the geography of information creation across the city. Second, we create a geo-temporal demographic classification of Twitter users in London. Third, we begin to use Twitter data to characterize the links between different locations across the city. We see all three elements as data rich, highly disaggregate geo-temporal analysis of urban form and function, albeit one that pertains to no clearly defined population. Our conclusions reflect upon this severe shortcoming in analysis using social media data, and its implications for progressing our understanding of socio-spatial distributions within cities. Numéro de notice : A2016-091 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1089441 En ligne : https://doi.org/10.1080/13658816.2015.1089441 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79876 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2016011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Temporal uncertainty in a small area open geodemographic classification / Christopher G. Gale in Transactions in GIS, vol 17 n° 4 (August 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 4 (August 2013) . - pp 563 - 588 Titre : Temporal uncertainty in a small area open geodemographic classification Type de document : Article/Communication Auteurs : Christopher G. Gale, Auteur ; Paul A. Longley, Auteur Année de publication : 2013 Article en page(s) : pp 563 - 588 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse diachronique [Termes IGN] classification [Termes IGN] données démographiques [Termes IGN] exploration de données géographiques [Termes IGN] incertitude temporelle [Termes IGN] Royaume-Uni Résumé : (Auteur) The 2001 Output Area Classification (2001 OAC) is an open source geodemographic classification of the UK built exclusively from 2001 UK Census data. There has been considerable user interest in its applicability to subsequent time periods, particularly given the potential propensity of characteristics and attributes in some areas to change during inter-censual periods. Users often purchase commercial geodemographic classification products in the belief that purely census-based classifications such as the 2001 OAC are uniformly unreliable because there is no temporal updating of input data. Yet there is evidence to suggest that whilst some UK neighborhoods are prone to sudden changes, many others change very little over protracted time periods. Using measures that are available at the small area level, temporal uncertainty indicators can be constructed to identify those areas that are less stable. Using mid-year population estimates and dwelling stock data, this article develops three temporal uncertainty indicators. These provide a reliable means of gauging the stability or otherwise of neighborhood conditions. The conclusion from this is that while a large number of small areas in the UK do experience change over time, this change is not uniform in either degree or distribution, or by geodemographic type. Numéro de notice : A2013-472 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12035 Date de publication en ligne : 23/05/2013 En ligne : https://doi.org/10.1111/tgis.12035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32610 [article]

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)  

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vol 32 n°3 - May 2008 - Discrete global grids (Bulletin de Computers, Environment and Urban Systems) / Peter J. M. Van Oosterom  

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Geographic Information Systems and science / Paul A. Longley (2005)

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Geographic Information Systems and science / Paul A. Longley (2001)

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Remote sensing and urban analysis / Jean-Paul Donnay (2001)

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Geocomputation / Paul A. Longley (1998)

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Spatial analysis / Paul A. Longley (1996)

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