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Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data / Luliang Tang in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)
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Titre : Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data Type de document : Article/Communication Auteurs : Luliang Tang, Auteur ; Zihan Kan, Auteur ; Xia Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 417 - 426 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] carrefour
[Termes IGN] coordonnées GPS
[Termes IGN] dimension temporelle
[Termes IGN] données massives
[Termes IGN] durée de trajet
[Termes IGN] fréquence
[Termes IGN] logique floue
[Termes IGN] taxi
[Termes IGN] trafic routier
[Termes IGN] trajectoire (véhicule non spatial)
[Termes IGN] Wuhan (Chine)Résumé : (Auteur) Intersections are the critical parts where different traffic flows converge and change directions, forming “bottlenecks” and “clog points” in urban traffic. Intersection travel time is an important parameter for public route planning, traffic management, and engineering optimization. Based on low-frequency spatial-temporal Global Positioning System (GPS) trace data, this article presents a novel method for estimating intersection travel time. The proposed method first analyzes the different travel patterns of vehicles through an intersection, then determines the range of an intersection dynamically and reasonably, and obtains traffic flow speed and delay at the intersection under different travel patterns using a fuzzy fitting approach. Finally, the average intersection travel time is estimated from traffic flow speed and delay and intersection range in different travel patterns. Wuhan road network data and GPS trace data from taxicabs were tested in the experiments and the results show that the proposed method can improve the accuracy of travel time estimation at city intersections. Numéro de notice : A2016-692 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1080/15230406.2015.1130649 En ligne : https://doi.org/10.1080/15230406.2015.1130649 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82029
in Cartography and Geographic Information Science > vol 43 n° 5 (November 2016) . - pp 417 - 426[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Knowledge transfer for large-scale urban growth modeling based on formal concept analysis / Jinyao Lin in Transactions in GIS, vol 20 n° 5 (October 2016)
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Titre : Knowledge transfer for large-scale urban growth modeling based on formal concept analysis Type de document : Article/Communication Auteurs : Jinyao Lin, Auteur ; Xia Li, Auteur Année de publication : 2016 Article en page(s) : pp 684 – 700 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] croissance urbaine
[Termes IGN] découverte de connaissances
[Termes IGN] étalonnage des données
[Termes IGN] Kouangtoung (Chine)
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] modélisation spatialeRésumé : (auteur) Cellular automata (CA) are useful for studies on urban growth and land-use changes. Although various methods have been developed to define transition rules, modeling urban growth of large areas remains a tough challenge owing to heterogeneous geographical features. To address the problem, we present a novel method based on the combination of Formal Concept Analysis (FCA) and knowledge transfer techniques. FCA is used to solicit association rules among cities within a large area. This method can provide a theoretical basis for the knowledge transfer process. A cutting-edge algorithm called TrAdaBoost is then integrated with the commonly-used Logistic-CA as the modeling framework. The proposed method is applied to the urban growth modeling of Guangdong Province, a large region with 21 cities in China, from 2005 to 2008. Compared with traditional methods, this method can achieve better results at the provincial and local levels, according to the experiments. The combination of FCA and knowledge transfer is expected to provide a useful tool for calibrating large-scale urban CA models. Numéro de notice : A2016-997 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12172 En ligne : http://dx.doi.org/10.1111/tgis.12172 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83777
in Transactions in GIS > vol 20 n° 5 (October 2016) . - pp 684 – 700[article]Understanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley, Zimbabwe using Geographic Information Systems and remote sensing / Mbulisi Sibanda in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)
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Titre : Understanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley, Zimbabwe using Geographic Information Systems and remote sensing Type de document : Article/Communication Auteurs : Mbulisi Sibanda, Auteur ; Timothy Dube, Auteur ; Victor M. Bangamwabo, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1006 - 1018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aire protégée
[Termes IGN] chasse
[Termes IGN] couvert végétal
[Termes IGN] distribution spatiale
[Termes IGN] habitat animal
[Termes IGN] Mammalia
[Termes IGN] régression logistique
[Termes IGN] surveillance écologique
[Termes IGN] ZimbabweMots-clés libres : braconnage Résumé : (auteur) The objective of this study was to understand the factors that explain the spatial distribution of elephant poaching activities in the areas of the mid-Zambezi Valley, Zimbabwe using geographic information system (GIS) and remotely sensed data integrated with spatial logistic regression. The results showed that significant (α = 0.05) elephant poaching hot spots are located closer to wildlife protected areas. Results further demonstrated that resource availability (water and forage) are the main factors explaining elephant poaching activities in the mid-Zambezi Valley. For example, the majority of poaching activities were found to occur in areas with high vegetation fractional cover (high forage) and close to waterholes. The results also showed that poaching incidences were more prevalent during the dry season. The findings of this study highlight the significance of integrating GIS, remotely sensed data and spatial logistic regression tools for understanding and monitoring elephant poaching activities. This information is critical if poaching activities are to be minimized and it is also important for planning, monitoring and mitigation of poaching activities in similar protected areas across the sub-Saharan Africa. Numéro de notice : A2016-670 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094529 Date de publication en ligne : 27/10/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094529 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81902
in Geocarto international > Vol 31 n° 9 - 10 (October - November 2016) . - pp 1006 - 1018[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? / Qunying Huang in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
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Titre : Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? Type de document : Article/Communication Auteurs : Qunying Huang, Auteur ; David W. S. Wong, Auteur Année de publication : 2016 Article en page(s) : pp 1871 - 1898 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse socio-économique
[Termes IGN] base de données spatiotemporelles
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données massives
[Termes IGN] données socio-économiques
[Termes IGN] morphologie urbaine
[Termes IGN] surveillance
[Termes IGN] TwitterRésumé : (Auteur) Individual activity patterns are influenced by a wide variety of factors. The more important ones include socioeconomic status (SES) and urban spatial structure. While most previous studies relied heavily on the expensive travel-diary type data, the feasibility of using social media data to support activity pattern analysis has not been evaluated. Despite the various appealing aspects of social media data, including low acquisition cost and relatively wide geographical and international coverage, these data also have many limitations, including the lack of background information of users, such as home locations and SES. A major objective of this study is to explore the extent that Twitter data can be used to support activity pattern analysis. We introduce an approach to determine users’ home and work locations in order to examine the activity patterns of individuals. To infer the SES of individuals, we incorporate the American Community Survey (ACS) data. Using Twitter data for Washington, DC, we analyzed the activity patterns of Twitter users with different SESs. The study clearly demonstrates that while SES is highly important, the urban spatial structure, particularly where jobs are mainly found and the geographical layout of the region, plays a critical role in affecting the variation in activity patterns between users from different communities. Numéro de notice : A2016-570 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1145225 En ligne : http://dx.doi.org/10.1080/13658816.2016.1145225 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81714
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1871 - 1898[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Discovery of local topics by using latent spatio-temporal relationships in geo-social media / Kyoung-Sook Kim in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
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Titre : Discovery of local topics by using latent spatio-temporal relationships in geo-social media Type de document : Article/Communication Auteurs : Kyoung-Sook Kim, Auteur ; Isao Kojima, Auteur ; Hirotaka Ogawa, Auteur Année de publication : 2016 Article en page(s) : pp 1899 - 1922 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données massives
[Termes IGN] données spatiotemporelles
[Termes IGN] géovisualisation
[Termes IGN] positionnement automatique
[Termes IGN] temps réel
[Termes IGN] traitement de donnéesRésumé : (Auteur) Social networks have played a crucial role as information channels for people to understanding their daily lives beyond merely being communication tools. In particular, coupling social networks with geographic location has boosted the worth of social media to not only enable comprehension of the effects of natural phenomena such as global warming and disasters, but also the social patterns of human societies. However, the high rate of social data generation and the large amounts of noisy data makes it difficult to directly apply social media to decision-making processes. This article proposes a new system of analyzing the spatio-temporal patterns of social phenomena in real time and the discovery of local topics based on their latent spatio-temporal relationships. We will first describe a model that represents the local patterns of populations of geo-tagged social media. We will then define a local topic whose keywords share a region in space and time and present a system implementation based on existing open source technologies. We evaluated the model of local topics with several ways of visualization in experiments and demonstrated a certain social pattern from a dataset of daily Twitter streams. The results obtained from experiments revealed certain keywords had a strong spatio-temporal proximity even though they did not occur in the same message. Numéro de notice : A2016-571 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1146956 En ligne : http://dx.doi.org/10.1080/13658816.2016.1146956 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81715
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1899 - 1922[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Finding spatial outliers in collective mobility patterns coupled with social ties / Monica Wachowicz in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
PermalinkIncorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections? / Paul Holloway in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
PermalinkIntegrating social network data into GISystems / Clio Andris in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
PermalinkMeasures of transport mode segmentation of trajectories / Adrain C. Prelipcean in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
PermalinkA novel methodology for identifying environmental exposures using GPS data / Andreea Cetateanu in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
PermalinkScabies among the French armed forces in 2015 / Constance Brossier in Journal of infection, vol 73 n° 3 (September 2016)
PermalinkSuivi spatiotemporel de la tache urbaine à l'aide de cartes anciennes, d'images satellitaires et de SIG. La cas de Blida en Algérie (de 1936 à 2015) / Elodie Ruch in Géomatique expert, n° 112 (septembre - octobre 2016)
PermalinkUnderstanding the bias of call detail records in human mobility research / Ziliang Zhao in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
PermalinkA spatial data infrastructure approach for the characterization of New Zealand's groundwater systems / Alexander Kmoch in Transactions in GIS, vol 20 n° 4 (August 2016)
PermalinkApport de la sûreté de fonctionnement à l’analyse spatialisée du risque inondation / Michaël Gonzva in Revue internationale de géomatique, vol 26 n° 3 (juillet - septembre 2016)
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