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Analysis of cycling network evolution in OpenStreetMap through a data quality prism / Raphaël Bres (2023)  

Public Titre : Analysis of cycling network evolution in OpenStreetMap through a data quality prism Type de document : Article/Communication Auteurs : Raphaël Bres, Auteur ; Veronika Peralta, Auteur ; Arnaud Le Guilcher , Auteur ; Thomas Devogele , Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Cyril de Runz, Auteur Editeur : Göttingen : Copernicus publications Année de publication : 2023 Collection : AGILE GIScience Series num. 4 Conférence : AGILE 2023, 26th international AGILE Conference on Geographic Information Science, Spatial data for design 13/06/2023 16/06/2023 Delft Pays-Bas OA Proceedings Importance : n° 3 ; 9 p. Note générale : bibliographie voir aussi le rapport de reproductibilité : https://doi.org/10.17605/OSF.IO/9KP7U Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] bicyclette [Termes IGN] méthode de Monte-Carlo [Termes IGN] mobilité territoriale [Termes IGN] mobilité urbaine [Termes IGN] modèle de simulation [Termes IGN] OpenStreetMap [Termes IGN] qualité des données [Termes IGN] voie cyclable Résumé : (auteur) Cycling practice has been constantly increasing for several years and the COVID crisis has just accelerated the process. Indeed, more and more municipalities have developed new cycle paths to facilitate cycling. Considering this increasing interest for cycling, it makes sense to study how this recent evolution is reflected in the underlying representation of the cycling network in the geographic databases. Main studies analysing the evolution of the road network focus on the motor vehicle network in the major cities of the world. These studies do not seem applicable to cycling network specially to some low population density areas or even to smaller cities. This paper analyses the changes in the cycling network through OSM data from a data freshness perspective. These changes can be either updates from changes in the real-world network or upgrades to the network. To these end, we propose a method using a Monte Carlo simulation (MCS) to analyse the frequency of changes in cycling routes in several areas with different population density, all in the Loire Valley region in France. We also define the cycling network, which is a very complex concept and we explain how it is represented in OSM data and suffers from different data quality issues. Results show that the number of changes across time are similar in areas having a similar population density, while being lower in low population density areas. These phenomena is higher in the cycling network compared to other networks. Numéro de notice : C2023-011 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : Vers HAL Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/agile-giss-4-3-2023 Date de publication en ligne : 06/06/2023 En ligne : https://doi.org/10.5194/agile-giss-4-3-2023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103308

Identifying locations for new bike-sharing stations in Glasgow: an analysis of spatial equity and demand factors / Jeneva Beairsto in Annals of GIS, vol 28 n° 2 (April 2022)  

Public [article]  inAnnals of GIS > vol 28 n° 2 (April 2022) . - pp 111 - 126 Titre : Identifying locations for new bike-sharing stations in Glasgow: an analysis of spatial equity and demand factors Type de document : Article/Communication Auteurs : Jeneva Beairsto, Auteur ; Yufan Tian, Auteur ; Linyu Zheng, Auteur Année de publication : 2022 Article en page(s) : pp 111 - 126 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] analyse des besoins [Termes IGN] bicyclette [Termes IGN] données spatiotemporelles [Termes IGN] Glasgow [Termes IGN] modèle de régression [Termes IGN] optimisation spatiale [Termes IGN] système d'information géographique Résumé : (auteur) Worldwide bike-sharing systems are growing in popularity as an alternative, environmentally friendly mode of transportation. As cities seek to further develop bike-sharing programmes, it is important to consider how systems should expand to simultaneously address existing inequalities in accessibility, and best serve demand. In this paper, we determine ideal locations for future bike-sharing stations in Glasgow, Scotland, by integrating demand modelling with accessibility considerations. We began by analysing the spatio-temporal trends of bike-sharing usage, and assessed the spatial equity of access to stations in Glasgow. To identify important determinants of bike-sharing demand, we ran an ordinary least squares regression model using bike sharing trip data from Nextbike Glasgow. We then quantifiably measured the level of spatial accessibility to stations by applying the two-step floating catchment area (2SFCA) methodology and ran a GIS weighted overlay analysis using the significant determinants of station demand. Lastly, we combined the demand and accessibility results to determine where new stations should be located using a maximum covering location problem (MCLP) that maximized the population served. Our results show that distance from transit stations, distance from downtown, employment rates, and nearby cycling lanes are significant factors affecting station-level demand. Furthermore, levels of spatial access were found to be highest primarily in the centre and eastern neighbourhood of Glasgow. These findings aided in determining areas to prioritize for future station locations, and our methodology can easily be applied to other bike-share programmes with adjustments according to varying aims for system expansion. Numéro de notice : A2022-500 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2021.1936172 Date de publication en ligne : 30/06/2021 En ligne : https://doi.org/10.1080/19475683.2021.1936172 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100997 [article]

Changing mobility patterns in the Netherlands during COVID-19 outbreak / Sander Van Der Drift in Journal of location-based services, vol 16 n° 1 (March 2022)  

Public [article]  inJournal of location-based services > vol 16 n° 1 (March 2022) . - pp 1 - 24 Titre : Changing mobility patterns in the Netherlands during COVID-19 outbreak Type de document : Article/Communication Auteurs : Sander Van Der Drift, Auteur ; Luc Wismans, Auteur ; Marie-José Olde-Kalter, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] bicyclette [Termes IGN] comportement [Termes IGN] épidémie [Termes IGN] estimation bayesienne [Termes IGN] mobilité territoriale [Termes IGN] Pays-Bas [Termes IGN] téléphone intelligent [Termes IGN] transport [Termes IGN] transport public [Termes IGN] travail à domicile [Termes IGN] véhicule automobile Résumé : (auteur) The COVID-19 outbreak and associated measures taken had an enormous impact on society as well as a disruptive, but not necessarily negative, impact on mobility. The Ministry of Infrastructure and Water Management received the most recent insights from the Dutch Mobility Panel (DMP) on a weekly basis. These insights were used to monitor the travel behaviour and to analyse changes in the behaviour of different groups and usage of modes of transport during COVID-19. The analysis shows an enormous decrease in travel at the beginning of the implementation of the so-called ‘intelligent’ lockdown and gradual increase again towards comparable levels as before this ‘intelligent lockdown, although the distribution over time, motives and used modes has changed. It becomes clear that not everyone needs to travel during peak hours and commuter travel is also not the main reason for the increase in car usage. Furthermore, cycling has shown to be an alternative option for travellers and public transport is hardly used anymore. If it is possible to sustain the lower level of car usage and integrate public transport as an important alternative for travel again, the COVID-19 impact on mobility could have a substantial remaining positive impact on mobility. Numéro de notice : A2022-391 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2021.1876259 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.1080/17489725.2021.1876259 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100682 [article]

Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data / Santosh Giri in International Journal of Health Geographics, vol 21 (2022)  

Public [article]  inInternational Journal of Health Geographics > vol 21 (2022) . - n° 19 Titre : Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data Type de document : Article/Communication Auteurs : Santosh Giri, Auteur ; Ruben Brondeel, Auteur ; Tarik El Aarbaoui, Auteur ; Basile Chaix, Auteur Année de publication : 2022 Article en page(s) : n° 19 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accéléromètre [Termes IGN] bicyclette [Termes IGN] données GPS [Termes IGN] données médicales [Termes IGN] Ile-de-France [Termes IGN] transport public Résumé : (auteur) Background : There has been an increased focus on active transport, but the measurement of active transport is still difficult and error-prone. Sensor data have been used to predict active transport. While heart rate data have very rarely been considered before, this study used random forests (RF) to predict transport modes using Global Positioning System (GPS), accelerometer, and heart rate data and paid attention to methodological issues related to the prediction strategy and post-processing. Methods : The RECORD MultiSensor study collected GPS, accelerometer, and heart rate data over seven days from 126 participants living in the Ile-de-France region. RF models were built to predict transport modes for every minute (ground truth information on modes is from a GPS-based mobility survey), splitting observations between a Training dataset and a Test dataset at the participant level instead at the minute level. Moreover, several window sizes were tested for the post-processing moving average of the predicted transport mode. Results : The minute-level prediction rate of being on trips vs. at a visited location was 90%. Final prediction rates of transport modes ranged from 65% for public transport to 95% for biking. Using minute-level observations from the same participants in the Training and Test sets (as RF spontaneously does) upwardly biases prediction rates. The inclusion of heart rate data improved prediction rates only for biking. A 3 to 5-min bandwidth moving average was optimum for a posteriori homogenization. Conclusion : Heart rate only very slightly contributed to better predictions for specific transport modes. Moreover, our study shows that Training and Test sets must be carefully defined in RF models and that post-processing with carefully chosen moving average windows can improve predictions. Numéro de notice : A2022-077 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1186/s12942-022-00319-y Date de publication en ligne : 16/11/2022 En ligne : https://doi.org/10.1186/s12942-022-00319-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102445 [article]

Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model / Mingwei Liu in Computers, Environment and Urban Systems, vol 91 (January 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101725 Titre : Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model Type de document : Article/Communication Auteurs : Mingwei Liu, Auteur ; Tinggui Chen, Auteur ; Chiaki Matunaga, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101725 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] agent (intelligence artificielle) [Termes IGN] bicyclette [Termes IGN] comportement [Termes IGN] cycliste [Termes IGN] direction [Termes IGN] interaction spatiale [Termes IGN] modèle de dispersion [Termes IGN] modèle orienté agent [Termes IGN] navigation pédestre [Termes IGN] piéton [Termes IGN] sécurité [Termes IGN] vitesse [Termes IGN] zone urbaine Résumé : (auteur) As the number of bicyclists in urban areas continues to increase, the need to realistically model the movement and interactions of bicyclists in mixed urban traffic is rapidly gaining importance. Therefore, this paper presents an agent space model (ASM) to elucidate the movements of bicyclists and pedestrians on shared roads. The ASM model, via simulation, particularly illustrates the dispersion phenomenon observed for non-motorized road users. The mutual interactions and diverse bicyclist and pedestrian properties were also incorporated into this model. The mutual interactions were realised through agent spaces of different sizes in conflict and overtaking behaviours for the following combinations: bicyclist-to-pedestrian, bicyclist-to-bicyclist, pedestrian-to-bicyclist, and pedestrian-to-pedestrian, which were obtained through experiments. The hypothesis test indicated that different agent spaces exist for different types of interactions. The experimental data were used to obtain several variables that describe the elements of road user agent spaces, including longitudinal and lateral distances and the dynamic relationship between the longitudinal distance and speed. The simulation results indicated that with an increase in the number of pedestrians, the maximum capacity decreased and the dispersion degree increased. The following psychological and physiological factors affect the degree of dispersion of bicyclists: travelling speed, reaction time, intensity, probability of selecting the head-on direction, and probability of selecting the right-hand direction. In addition, lane formation was observed in all simulations. The results also demonstrated that dedicated bicycle lanes will significantly reduce the dispersion degree. Moreover, the safety and efficiency effects of different forms of bicycle lanes were analysed from the perspective of the degree of dispersion. The simulation results can provide specific guidelines for understanding the causes of phenomena such as dispersion and lane formation, as well as for studying the traffic dynamics, effects of dedicated bicycle lanes, and macroscopic characteristics according to different bicyclist-pedestrian ratios. Numéro de notice : A2021-826 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101725 Date de publication en ligne : 20/10/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101725 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98947 [article]

Spécification et qualité du réseau cyclable, application à la recherche d’itinéraires / Raphaël Bres (2022)  

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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)  

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Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data / Yang Ma in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

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Cyclists' exposure to air pollution and noise in Mexico City : contribution of real-time traffic density indicators integrated into GIS / Philippe Apparicio in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 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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WeCount, le trafic compté par les citoyens / Victor Oxombre (2020) 

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A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy / Yan Zhou in Transactions in GIS, Vol 23 n° 5 (October 2019)  

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A vélo au travers des Andes, pour OpenStreetMap / Anonyme in Géomatique expert, n° 126 (janvier - février 2019)

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A simple line clustering method for spatial analysis with origin-destination data and its application to bike-sharing movement data / Biao He in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)  

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An empirical evaluation of three elevation change symbolization methods along routes in bicycle maps / Annina Brügger in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)  

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