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Pedestrian network generation based on crowdsourced tracking data / Xue Yang in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)
[article]
Titre : Pedestrian network generation based on crowdsourced tracking data Type de document : Article/Communication Auteurs : Xue Yang, Auteur ; Luliang Tang, Auteur ; Chang Ren, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1051 - 1074 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] approche participative
[Termes IGN] base de données multi-représentation
[Termes IGN] correction géométrique
[Termes IGN] correction topographique
[Termes IGN] dimension fractale
[Termes IGN] données localisées des bénévoles
[Termes IGN] estimation par noyau
[Termes IGN] mobilité urbaine
[Termes IGN] navigation pédestre
[Termes IGN] regroupement de pointsRésumé : (auteur) Pedestrian networks play an important role in various applications, such as pedestrian navigation services and mobility modeling. This paper presents a novel method to extract pedestrian networks from crowdsourced tracking data based on a two-layer framework. This framework includes a walking pattern classification layer and a pedestrian network generation layer. In the first layer, we propose a multi-scale fractal dimension (MFD) algorithm in order to recognize the two different types of walking patterns: walking with a clear destination (WCD) or walking without a clear destination (WOCD). In the second layer, we generate the pedestrian network by combining the pedestrian regions and pedestrian paths. The pedestrian regions are extracted based on a modified connected component analysis (CCA) algorithm from the WOCD traces. We generate the pedestrian paths using a kernel density estimation (KDE)-based point clustering algorithm from the WCD traces. The pedestrian network generation results using two actual crowdsourced datasets show that the proposed method has good performance in both geometrical correctness and topological correctness. Numéro de notice : A2020-207 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1702197 Date de publication en ligne : 09/12/2019 En ligne : https://doi.org/10.1080/13658816.2019.1702197 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94888
in International journal of geographical information science IJGIS > vol 34 n° 5 (May 2020) . - pp 1051 - 1074[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2020051 RAB Revue Centre de documentation En réserve L003 Disponible A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data / Haiyan Tao in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)
[article]
Titre : A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data Type de document : Article/Communication Auteurs : Haiyan Tao, Auteur ; Keli Wang, Auteur ; Li Zhuo, Auteur Année de publication : 2020 Article en page(s) : pp 604 - 624 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] Chine
[Termes IGN] diffusion spatiale
[Termes IGN] distribution de Poisson
[Termes IGN] données socio-économiques
[Termes IGN] hétérogénéité environnementale
[Termes IGN] hétérogénéité spatiale
[Termes IGN] maladie infectieuse
[Termes IGN] migration humaine
[Termes IGN] mobilité territoriale
[Termes IGN] modèle de régression
[Termes IGN] modèle mathématique
[Termes IGN] origine - destination
[Termes IGN] point d'intérêt
[Termes IGN] risque sanitaire
[Termes IGN] urbanisationRésumé : (auteur) International communication and global cooperation have greatly accelerated the worldwide spread of dengue fever, increasing the impact of imported cases on dengue outbreaks in non-naturally endemic areas. Existing studies mostly focus on describing the quantitative relationship between imported cases and local transmission but ignore the space-time diffusion mode of imported cases under the influence of individual mobility. In this paper, we propose a comprehensive framework at a fine scale to establish the disease transmission network and a mathematical model, which constructs ‘source-sink’ links between the imported and indigenous cases on a regular grid with a spatial resolution of 1 km to explore the diffusion pattern and spatiotemporal heterogeneity of imported cases. An application to Guangzhou, China, reveals the main flow and transmission path of imported cases under the influence of human movement and identifies the spatiotemporal distribution of transmission speed according to the time lag of each source-sink link. In addition, we demonstrate that using individual-based movement data and socio-economic factors to study human mobility and imported cases can help to understand the driving forces of dengue spread. Our research provides a comprehensive framework for the analysis of early dengue transmission patterns with benefits to similar urban applications. Numéro de notice : A2020-107 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684497 Date de publication en ligne : 18/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684497 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94707
in International journal of geographical information science IJGIS > vol 34 n° 3 (March 2020) . - pp 604 - 624[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2020031 RAB Revue Centre de documentation En réserve L003 Disponible Road network structure and ride-sharing accessibility: A network science perspective / Mingshu Wang in Computers, Environment and Urban Systems, vol 80 (March 2020)
[article]
Titre : Road network structure and ride-sharing accessibility: A network science perspective Type de document : Article/Communication Auteurs : Mingshu Wang, Auteur ; Zheyan Chen, Auteur ; Lan Mu, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Atlanta (Géorgie)
[Termes IGN] autopartage
[Termes IGN] densité de population
[Termes IGN] gestion urbaine
[Termes IGN] migration pendulaire
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] OpenStreetMap
[Termes IGN] réseau routier
[Termes IGN] système d'information géographiqueRésumé : (auteur) The prosperity of ride-sharing services has rippled in the communities of GIScience, transportation, and urban planning. Meanwhile, road network structure has been analyzed from a network science perspective that focuses on nodes and relational links and aims to predictive models. However, limited empirical studies have explored the relationship between road network structure and ride-sharing accessibility through such perspective. This paper utilizes the spatial Durbin model to understand the relationship between road network structure and ride-sharing accessibility, proxied by Uber accessibility, through classical network measures of degree, closeness, and betweenness centrality. Taking the city of Atlanta as a case study, we have found in addition to population density and road network density, larger values of degree centrality and smaller values of closeness centrality of the road network are associated with better accessibility of Uber services. However, the effects of betweenness centrality are not significant. Furthermore, we have revealed heterogeneous effects of degree centrality and closeness centrality on the accessibility of Uber services, as the magnitudes of their effects vary by different time windows (i.e., weekday vs. weekend, rush hour in the morning vs. evening). Network science provides us both conceptual and methodological measures to understand the association between road network structure and ride-sharing accessibility. In this study, we constructed road network structure measures with OpenStreetMap, which is reproducible, replicable, and scalable because of its global coverage and public availability. The study resonates with the notion of cities as the set of interactions across networks, as we have observed time-sensitive heterogeneous effects of road network structure on ride-sharing accessibility. Numéro de notice : A2020-190 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2019.101430 Date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101430 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94852
in Computers, Environment and Urban Systems > vol 80 (March 2020)[article]Uber movement data: a proxy for average one-way commuting times by car / Yeran Sun in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Uber movement data: a proxy for average one-way commuting times by car Type de document : Article/Communication Auteurs : Yeran Sun, Auteur ; Yinming Ren, Auteur ; Xuan Sun, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Boston (Massachusetts)
[Termes IGN] distribution spatiale
[Termes IGN] durée de trajet
[Termes IGN] flux
[Termes IGN] migration pendulaire
[Termes IGN] objet mobile
[Termes IGN] origine - destination
[Termes IGN] planification urbaine
[Termes IGN] taxi
[Termes IGN] trace GPSRésumé : (auteur) Recently, Uber released datasets named Uber Movement to the public in support of urban planning and transportation planning. To prevent user privacy issues, Uber aggregates car GPS traces into small areas. After aggregating car GPS traces into small areas, Uber releases free data products that indicate the average travel times of Uber cars between two small areas. The average travel times of Uber cars in the morning peak time periods on weekdays could be used as a proxy for average one-way car-based commuting times. In this study, to demonstrate usefulness of Uber Movement data, we use Uber Movement data as a proxy for commuting time data by which commuters’ average one-way commuting time across Greater Boston can be figured out. We propose a new approach to estimate the average car-based commuting times through combining commuting times from Uber Movement data and commuting flows from travel survey data. To further demonstrate the applicability of the commuting times estimated by Uber movement data, this study further measures the spatial accessibility of jobs by car by aggregating place-to-place commuting times to census tracts. The empirical results further uncover that 1) commuters’ average one-way commuting time is around 20 min across Greater Boston; 2) more than 75% of car-based commuters are likely to have a one-way commuting time of less than 30 min; 3) less than 1% of car-based commuters are likely to have a one-way commuting time of more than 60 min; and 4) the areas suffering a lower level of spatial accessibility of jobs by car are likely to be evenly distributed across Greater Boston. Numéro de notice : A2020-255 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030184 Date de publication en ligne : 24/03/2020 En ligne : https://doi.org/10.3390/ijgi9030184 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95010
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 16 p.[article]An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)
[article]
Titre : An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data Type de document : Article/Communication Auteurs : Xiaogang Guo, Auteur ; Zhijie Xu, Auteur ; Jianqin Zhang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par nuées dynamiques
[Termes IGN] distance euclidienne
[Termes IGN] données de flux
[Termes IGN] données vectorielles
[Termes IGN] erreur moyenne quadratique
[Termes IGN] origine - destination
[Termes IGN] Pékin (Chine)
[Termes IGN] regroupement de données
[Termes IGN] taxi
[Termes IGN] trafic routier
[Termes IGN] zone urbaineRésumé : (auteur) Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling relationship of urban subspace and dynamic causes. The existing flow clustering methods are limited by the spatial constraints of OD points, rely on the spatial similarity of geographical points, and lack in-depth analysis of high-dimensional flow characteristics, and therefore it is difficult to find irregular flow clusters. In this paper, we propose an OD flow clustering method based on vector constraints (ODFCVC), which defines OD flow event point and OD flow vector to express the spatial location relationship and geometric flow behavior characteristics of OD flow. First, the OD flow vector coordinate system is normalized by the Euclidean distance-based OD flow event point spatial clustering, and then the OD flow clusters with similar flow patterns are mined using adjusted cosine similarity-based OD flow vector feature clustering. The transformation of OD data from point set space to vector space is realized by constraining the vector coordinate system and vector similarity through two-step clustering, which simplifies the calculation of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. Due to the OD flow cluster property, the k-means algorithm is selected as the basic clustering logic in the two-step clustering method, and a sum of squared error perceptually important points algorithm considering silhouette coefficients (SSEPIP) is adopted to automatically extract the optimal cluster number without defining any parameters. Tested by origin-destination flow data in Beijing, China, new traffic flow communities based on traffic hubs are obtained by using the ODFCVC method, and irregular traffic flow clusters (including cluster mode, divergence mode, and convergence mode) with representative travel trends are found. Numéro de notice : A2020-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9020128 Date de publication en ligne : 22/02/2020 En ligne : https://doi.org/10.3390/ijgi9020128 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94720
in ISPRS International journal of geo-information > vol 9 n° 2 (February 2020)[article]Assessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA / Yongha Park in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)PermalinkSimilarity measurement on human mobility data with spatially weighted structural similarity index (SpSSIM) / Chanwoo Jin in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkSpatio-temporal mobility and Twitter: 3D visualisation of mobility flows / Joaquín Osorio Arjona in Journal of maps, vol 16 n° 1 ([02/01/2020])PermalinkAnalyse spatio-temporelle des mobilités de randonneurs dans le PNR du Massif des Bauges / Colin Kerouanton (2020)PermalinkDiagnostic qualité et apurement des données de mobilité quotidienne issues de l’enquête mixte et longitudinale Mobi’Kids / Sylvestre Duroudier in Revue internationale de géomatique, vol 30 n° 1-2 (janvier - juin 2020)PermalinkPermalinkPotentiel des sources de données collaboratives pour l'intégration de points de repère et des itinéraires pour le sauvetage en zone de montagne / Marie-Dominique Van Damme in Cartes & Géomatique, n° 241-242 (décembre 2019)PermalinkImmigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne / Marcello Marini in Computers, Environment and Urban Systems, vol 78 (November 2019)PermalinkFine-tuning the usability of a crowdsourced indoor navigation system / Kristien Ooms in Cartography and Geographic Information Science, Vol 46 n° 5 (September 2019)PermalinkSMSM: a similarity measure for trajectory stops and moves / Andre L. Lehmann in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)Permalink