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Understanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors / Feng Gao in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 9 (September 2021) . - pp 1905 - 1925 Titre : Understanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors Type de document : Article/Communication Auteurs : Feng Gao, Auteur ; Shaoying Li, Auteur ; Zhangzhi Tan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1905 - 1925 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aménagement du territoire [Termes IGN] bicyclette [Termes IGN] données issues des réseaux sociaux [Termes IGN] mobilité urbaine [Termes IGN] origine - destination [Termes IGN] planification urbaine [Termes IGN] problème d'unité zonale modifiable [Termes IGN] Shenzhen Résumé : (auteur) Understanding the influence mechanisms of dockless bike-sharing usage is essential for land use planning and bike scheduling strategy implementation. Although various studies have been carried out to explore the impact of built environment (BE) factors on bike-sharing usage, few studies have examined the modifiable areal unit problem (MAUP). Moreover, previous studies mainly focused on the separate effect of each factor but neglected the interactions between these factors. Taking Shenzhen, China as the case, this study fills these two gaps by employing the geographical detector method to examine the MAUP in dockless bike-sharing usage as well as the interactive effects of BE factors. The results revealed that the influences of most BE variables are sensitive to the spatial areal units, which have informed urban planners what built-environment factors should be paid more attention to at certain spatial scales. Additionally, through the comparisons between single effect and interactive effect, this study revealed some interesting findings that can provide scientific basis for temporal rebalance strategy for the innovative and high-density metropolis in China. Numéro de notice : A2021-593 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1863410 date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1863410 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98214 [article]

Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility / Qingqing Chen in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1425 - 1448 Titre : Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility Type de document : Article/Communication Auteurs : Qingqing Chen, Auteur ; Ate Poorthuis, Auteur Année de publication : 2021 Article en page(s) : pp 1425 - 1448 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] géopositionnement [Termes IGN] logement [Termes IGN] mobilité urbaine [Termes IGN] R (langage) [Termes IGN] service fondé sur la position [Termes IGN] Singapour Résumé : (auteur) Identifying meaningful locations, such as home or work, from human mobility data has become an increasingly common prerequisite for geographic research. Although location-based services (LBS) and other mobile technology have rapidly grown in recent years, it can be challenging to infer meaningful places from such data, which – compared to conventional datasets – can be devoid of context. Existing approaches are often developed ad-hoc and can lack transparency and reproducibility. To address this, we introduce an R package for inferring home locations from LBS data. The package implements pre-existing algorithms and provides building blocks to make writing algorithmic ‘recipes’ more convenient. We evaluate this approach by analyzing a de-identified LBS dataset from Singapore that aims to balance ethics and privacy with the research goal of identifying meaningful locations. We show that ensemble approaches, combining multiple algorithms, can be especially valuable in this regard as the resulting patterns of inferred home locations closely correlate with the distribution of residential population. We hope this package, and others like it, will contribute to an increase in use and sharing of comparable algorithms, research code and data. This will increase transparency and reproducibility in mobility analyses and further the ongoing discourse around ethical big data research. Numéro de notice : A2021-449 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887489 date de publication en ligne : 10/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97861 [article]

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Using information entropy and a multi-layer neural network with trajectory data to identify transportation modes / Qingying Yu in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1346 - 1373 Titre : Using information entropy and a multi-layer neural network with trajectory data to identify transportation modes Type de document : Article/Communication Auteurs : Qingying Yu, Auteur ; Yonglong Luo, Auteur ; Dongxia Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1346 - 1373 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] classification par Perceptron multicouche [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] direction [Termes IGN] données spatiotemporelles [Termes IGN] entropie [Termes IGN] extraction de traits caractéristiques [Termes IGN] mobilité urbaine [Termes IGN] Pékin (Chine) [Termes IGN] plan de déplacement urbain [Termes IGN] segmentation [Termes IGN] trajectoire [Termes IGN] vitesse de déplacement Résumé : (auteur) Residents’ trajectory data denote their instantaneous locations along their movements. Mobility research that applies trajectory mining techniques to identify the transportation modes of these movements can inform urban transportation planning. Herein, we propose a five-step approach with information entropy and a multi-layer neural network to identify transportation modes from trajectory data. First, this approach extracts the motion features at each time-stamped location based on foundation geospatial data and spatiotemporal trajectory data, including the speed, acceleration, change of direction, rate of change in direction, and distance from each basic transportation facility. The second step uses information entropy to identify the features that play key roles in identifying transportation modes. The third step weighs each attribute in the feature vector consisting of the selected features and normalizes it to prepare it as input data. The fourth step constructs, trains, and tests a multi-layer neural network with seven-fold cross-validation. The final step includes a post-processing method to optimize the identification result. We use F-measure metric to evaluate the performance. Experimental results on a real trajectory dataset show that the proposed approach can identify the transportation mode at each time-stamped location and outperforms existing transportation-mode identification methods in terms of accuracy and stability. Numéro de notice : A2021-448 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1901904 date de publication en ligne : 15/04/2021 En ligne : https://doi.org/10.1080/13658816.2021.1901904 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97860 [article]

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Urban Informatics / Wenzhong Shi (2021)  

Public Titre : Urban Informatics Type de document : Monographie Auteurs : Wenzhong Shi, Éditeur scientifique ; Michael F. Goodchild, Éditeur scientifique ; Michael Batty, Éditeur scientifique ; et al., Auteur Editeur : Springer Nature Année de publication : 2021 Collection : The Urban Book Series Importance : 941 p. ISBN/ISSN/EAN : 978-981-1589836-- Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Urbanisme [Termes IGN] données massives [Termes IGN] infrastructure urbaine de données localisées [Termes IGN] mobilité urbaine [Termes IGN] planification urbaine [Termes IGN] pollution [Termes IGN] sécurité publique [Termes IGN] système d'information géographique [Termes IGN] ville durable [Termes IGN] ville intelligente Résumé : (éditeur) This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity. Note de contenu : 1- Introduction 2- Dimensions of Urban Science 3- Urban Systems and Applications Numéro de notice : 28559 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Monographie DOI : 10.1007/978-981-15-8983-6 En ligne : https://link.springer.com/book/10.1007/978-981-15-8983-6 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97592

Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks / Egor Smirrnov in Geo-spatial Information Science, vol 23 n° 4 (December 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 362 - 374 Titre : Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks Type de document : Article/Communication Auteurs : Egor Smirrnov, Auteur ; Sergei Dunaenko, Auteur ; Sergei Kudinov, Auteur Année de publication : 2020 Article en page(s) : pp 362 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] itinéraire piétionnier [Termes IGN] modèle de simulation [Termes IGN] navigation pédestre [Termes IGN] optimisation par colonie de fourmis [Termes IGN] piéton [Termes IGN] plan de déplacement urbain [Termes IGN] regroupement de données [Termes IGN] sécurité routière [Termes IGN] système multi-agents [Termes IGN] urbanisme Résumé : (auteur) When arranging the pedestrian infrastructure, one of the most important components that make a tangible contribution to the safety of pedestrians is to organize the safe road crossing. In cities, pedestrians often cross a road in the wrong place due to established routes or inadequate location of crosswalks. Accidents with the participation of pedestrians who crossed the road neglecting the traffic rules, make up a significant part of the total amount of road accidents. In this paper, we propose a method that allows us, on the basis of the results of a computer simulation of pedestrian traffic, to obtain predicted routes for road crossing and to indicate optimal locations for crosswalks that take into account established pedestrian routes and increase their safety. The work describes an extension for the existing AntRoadPlanner simulation algorithm, which searches for and clusters points where pedestrians cross the roadway and suggests locations for new crosswalks. This method was tested on the basis of a comparative simulation of several territories before and after its application, as well as on the basis of a field study of the territories. The developed algorithm can also be used to search for other potentially dangerous places for pedestrians on plans of districts, for example, crossings in places with limited visibility. Numéro de notice : A2020-789 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1847003 date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1847003 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96551 [article]

Modalflow: cross-origin flow data visualization for urban mobility / Ignacio Pérez-Messina in Algorithms, vol 13 n° 11 (November 2020)  

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Unfolding spatial-temporal patterns of taxi trip based on an improved network kernel density estimation / Boxi Shen in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

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Urban Wi-Fi fingerprinting along a public transport route / Guenther Retscher in Journal of applied geodesy, vol 14 n° 4 (October 2020)  

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Impact of extreme weather events on urban human flow: A perspective from location-based service data / Zhenhua Chen in Computers, Environment and Urban Systems, vol 83 (September 2020)  

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Objets connectés et mobilité urbaine : visualiser les déplacements des usagers de Twitter avec des graphes dynamiques / Françoise Lucchini in Mappemonde [en ligne], n° 128 (juillet 2020)  

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An empirical study on the intra-urban goods movement patterns using logistics big data / Pengxiang Zhao in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)  

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Extracting commuter-specific destination hotspots from trip destination data – comparing the boro taxi service with Citi Bike in NYC / Andreas Keler in Geo-spatial Information Science, vol 23 n° 2 (June 2020)  

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Dynamic floating stations model for emergency medical services with a consideration of traffic data / Chih-Hong Sun in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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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)  

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Road network structure and ride-sharing accessibility: A network science perspective / Mingshu Wang in Computers, Environment and Urban Systems, vol 80 (March 2020)  

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