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An advanced systematic literature review on spatiotemporal analyses of twitter-data / Enrico Steiger in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 809 – 834 Titre : An advanced systematic literature review on spatiotemporal analyses of twitter-data Type de document : Article/Communication Auteurs : Enrico Steiger, Auteur ; João Porto de Albuquerque, Auteur ; Alexander Zipf, Auteur Année de publication : 2015 Article en page(s) : pp 809 – 834 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] données issues des réseaux sociaux [Termes IGN] état de l'art [Termes IGN] requête spatiotemporelle [Termes IGN] Twitter Résumé : (auteur) The objective of this article is to conduct a systematic literature review that provides an overview of the current state of research concerning methods and application for spatiotemporal analyses of the social network Twitter. Reviewed papers and their application domains have shown that the study of geographical processes by using spatiotemporal information from location-based social networks represent a promising and still underexplored field for GIScience researchers. Numéro de notice : A2016-435 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12132 En ligne : http://dx.doi.org/10.1111/tgis.12132 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81343 [article]

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]

An exploration of future patterns of the contributions to OpenStreetMap and development of a contribution index / Jamal Jokar Arsanjani in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 896 – 914 Titre : An exploration of future patterns of the contributions to OpenStreetMap and development of a contribution index Type de document : Article/Communication Auteurs : Jamal Jokar Arsanjani, Auteur ; Peter Mooney, Auteur ; Marco Helbich, Auteur ; Alexander Zipf, Auteur Année de publication : 2015 Article en page(s) : pp 896 – 914 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] Allemagne [Termes IGN] approche participative [Termes IGN] automate cellulaire [Termes IGN] base de données spatiotemporelles [Termes IGN] cartographie collaborative [Termes IGN] données localisées des bénévoles [Termes IGN] indexation sémantique [Termes IGN] OpenStreetMap [Termes IGN] Stuttgart Résumé : (auteur) OpenStreetMap (OSM) represents one of the most well-known examples of a collaborative mapping project. Major research efforts have so far dealt with data quality analysis but the modality of OSM's evolution across space and time has barely been noted. This study aims to analyze spatio-temporal patterns of contributions in OSM by proposing a contribution index (CI) in order to investigate the dynamism of OSM. The CI is based on a per cell analysis of the node quantity, interactivity, semantics, and attractivity (the ability to attract contributors). Additionally this research explores whether OSM has been constantly attracting new users and contributions or if OSM has experienced a decline in its ability to attract continued contributions. Using the Stuttgart region of Germany as a case study the empirical findings of the CI over time confirm that since 2007, OSM has been constantly attracting new users, who create new features, edit the existing spatial objects, and enrich them with attributes. This rate has been dramatically growing since 2011. The utilization of a Cellular Automata-Markov (CA-Markov) model provides evidence that by the end of 2016 and 2020, the rise of CI will spread out over the study area and only a few cells without OSM features will remain. Numéro de notice : A2016-437 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12139 En ligne : http://dx.doi.org/10.1111/tgis.12139 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81347 [article]

A hybrid link-node approach for finding shortest paths in road networks with turn restrictions / Qingquan Li in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 915 - 929 Titre : A hybrid link-node approach for finding shortest paths in road networks with turn restrictions Type de document : Article/Communication Auteurs : Qingquan Li, Auteur ; Bi Yu Chen, Auteur ; Yafei Wang, Auteur ; William H. K. Lam, Auteur Année de publication : 2015 Article en page(s) : pp 915 - 929 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] calcul d'itinéraire [Termes IGN] chemin le plus court, algorithme du [Termes IGN] navigation automobile [Termes IGN] noeud [Termes IGN] requête spatiale [Termes IGN] réseau routier [Termes IGN] traitement de données localisées Résumé : (auteur) Turn restrictions, such as ‘no left turn’ or ‘no U-turn’, are commonly encountered in real road networks. These turn restrictions must be explicitly considered in the shortest path problem and ignoring them may lead to infeasible paths. In the present study, a hybrid link-node Dijkstra's (HLND) algorithm is proposed to exactly solve the shortest path problem in road networks with turn restrictions. A new hybrid link–node labelling approach is devised by using a link–based labelling strategy at restricted nodes with turn restrictions, and a node-based labelling strategy at unrestricted nodes without turn restrictions. Computational results for several real road networks show that the proposed HLND algorithm obtains the same optimal results as the link-based Dijkstra's algorithm, while having a similar computational performance to the classical node-based Dijkstra's algorithm. Numéro de notice : A2016-438 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12133 En ligne : http://dx.doi.org/10.1111/tgis.12133 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81349 [article]

A back-propagation neural network-based approach for multi-represented feature matching in update propagation / Yanxia Wang in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 964 – 993 Titre : A back-propagation neural network-based approach for multi-represented feature matching in update propagation Type de document : Article/Communication Auteurs : Yanxia Wang, Auteur ; Deng Chen, Auteur ; Zhiyuan Zhao, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 964 – 993 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] appariement de données localisées [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] mise à jour de base de données [Termes IGN] objet géographique zonal [Termes IGN] pondération [Termes IGN] représentation multiple [Termes IGN] réseau neuronal artificiel Résumé : (auteur) Spatial data infrastructures, which are characterized by multi-represented datasets, are prevalent throughout the world. The multi-represented datasets contain different representations for identical real-world entities. Therefore, update propagation is useful and required for maintaining multi-represented datasets. The key to update propagation is the detection of identical features in different datasets that represent corresponding real-world entities and the detection of changes in updated datasets. Using polygon features of settlements as examples, this article addresses these key problems and proposes an approach for multi-represented feature matching based on spatial similarity and a back-propagation neural network (BPNN). Although this approach only utilizes the measures of distance, area, direction and length, it dynamically and objectively determines the weight of each measure through intelligent learning; in contrast, traditional approaches determine weight using expertise. Therefore, the weight may be variable in different data contexts but not for different levels of expertise. This approach can be applied not only to one-to-one matching but also to one-to-many and many-to-many matching. Experiments are designed using two different approaches and four datasets that encompass an area in China. The goals are to demonstrate the weight differences in different data contexts and to measure the performance of the BPNN-based feature matching approach. Numéro de notice : A2015--077 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12138 En ligne : http://dx.doi.org/10.1111/tgis.12138 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81352 [article]