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Understanding the combined impacts of aggregation and spatial non-stationarity: The case of migration-environment associations in rural South Africa / Galen McLaurin in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 877 – 895 Titre : Understanding the combined impacts of aggregation and spatial non-stationarity: The case of migration-environment associations in rural South Africa Type de document : Article/Communication Auteurs : Galen McLaurin, Auteur ; Stefan Leyk, Auteur ; Lori Hunter, Auteur Année de publication : 2015 Article en page(s) : pp 877 – 895 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Afrique du sud (état) [Termes IGN] agrégation spatiale [Termes IGN] analyse de sensibilité [Termes IGN] données socio-économiques [Termes IGN] données statistiques [Termes IGN] indicateur démographique [Termes IGN] migration humaine [Termes IGN] milieu rural [Termes IGN] relation topologique Résumé : (auteur) Socio-demographic data are typically collected at various levels of aggregation, leading to the modifiable areal unit problem. Spatial non-stationarity of statistical associations between variables further influences the demographic analyses. This study investigates the implications of these two phenomena within the context of migration-environment associations. Global and local statistical models are fit across increasing levels of aggregation using household level survey data from rural South Africa. We raise the issue of operational scale sensitivity, which describes how the explanatory power of certain variables depends on the aggregation level. We find that as units of analysis (households) are aggregated, some variables become non-significant in the global models, while others are less sensitive to aggregation. Local model results show that aggregation reduces spatial variation in migration-related local associations but also affects variables differently. Spatial non-stationarity appears to be the driving force behind this phenomenon as the results from the global model mask this relationship. Operational scale sensitivity appears related to the underlying spatial autocorrelation of the non-aggregated variables but also to the way a variable is constructed. Understanding operational scale sensitivity can help to refine the process of selecting variables related to the scale of analysis and better understand the effects of spatial non-stationarity on statistical relationships. Numéro de notice : A2016-436 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12134 En ligne : http://dx.doi.org/10.1111/tgis.12134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81344 [article]