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Auteur Colin Robertson |
Documents disponibles écrits par cet auteur (2)
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Inference and analysis across spatial supports in the big data era : Uncertain point observations and geographic contexts / Colin Robertson in Transactions in GIS, vol 22 n° 2 (April 2018)
[article]
Titre : Inference and analysis across spatial supports in the big data era : Uncertain point observations and geographic contexts Type de document : Article/Communication Auteurs : Colin Robertson, Auteur ; Rob Feick, Auteur Année de publication : 2018 Article en page(s) : pp 455 - 476 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] incertitude des données
[Termes IGN] prise en compte du contexteRésumé : (Auteur) The ways in which geographic information are produced have expanded rapidly over recent decades. These advances have provided new opportunities for geographical information science and spatial analysis—allowing the tools and theories to be expanded to new domain areas and providing the impetus for theory and methodological development. In this light, old problems of inference and analysis are rediscovered and need to be reinterpreted, and new ones are made apparent. This article describes a new typology of geographical analysis problems that relates to uncertainties in the relationship between individual‐level data, represented as point features, and the geographic context(s) that they are associated with. We describe how uncertainty in context linkage (uncertain geographic context problem) is also related to, but distinct from, uncertainty in point‐event locations (uncertain point observation problem) and how these issues can impact spatial analysis. A case study analysis of a geosocial dataset demonstrates how alternative conclusions can result from failure to account for these sources of uncertainty. Sources of point observation uncertainties common in many forms of user‐generated and big spatial data are outlined and methods for dealing with them are reviewed and discussed. Numéro de notice : A2018-213 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12321 Date de publication en ligne : 23/03/2018 En ligne : https://doi.org/10.1111/tgis.12321 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90003
in Transactions in GIS > vol 22 n° 2 (April 2018) . - pp 455 - 476[article]Bumps and bruises in the digital skins of cities: unevenly distributed user-generated content across US urban areas / Colin Robertson in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)
[article]
Titre : Bumps and bruises in the digital skins of cities: unevenly distributed user-generated content across US urban areas Type de document : Article/Communication Auteurs : Colin Robertson, Auteur ; Robert Feick, Auteur Année de publication : 2016 Article en page(s) : pp 283 - 300 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse de données
[Termes IGN] Dallas (Texas)
[Termes IGN] données descriptives
[Termes IGN] données localisées des bénévoles
[Termes IGN] données socio-économiques
[Termes IGN] géobalise
[Termes IGN] image 2D
[Termes IGN] Nouvelle-Orléans (Louisiane)
[Termes IGN] qualité des données
[Termes IGN] représentation des données
[Termes IGN] representativité
[Termes IGN] Seattle (Washington)Résumé : (Auteur) As momentum and interest build to leverage new forms of user-generated content that contains geographical information, classical issues of data quality remain significant research challenges. In this article, we explore issues of representativeness for one form of user-generated content, geotagged photographs in US urban centers. Generalized linear models were developed to associate photograph distribution with underlying socioeconomic descriptors at the city-scale, and examine intra-city variation in relation to income inequality. We conclude our analyses with a detailed examination of Dallas, Seattle, and New Orleans. Our findings add to the growing volume of evidence outlining uneven representativeness in user-generated data, and our approach contributes to the stock of methods available to investigate geographic variations in representativeness. In addition to city-scale variables relating to distribution of user-generated content, variability remains at localized scales that demand an individual and contextual understanding of their form and nature. The findings demonstrate that careful analysis of representativeness at both macro and micro scales can simultaneously provide important insights into the processes giving rise to user-generated data sets and potentially shed light on their embedded biases and suitability as inputs to analysis. Numéro de notice : A2016-415 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2015.1088801 En ligne : https://doi.org/10.1080/15230406.2015.1088801 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81309
in Cartography and Geographic Information Science > Vol 43 n° 4 (September 2016) . - pp 283 - 300[article]Exemplaires(1)
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