Centre dedocumentation
scientifique

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)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 11 (November 2020) . - n° 683 Titre : Unfolding spatial-temporal patterns of taxi trip based on an improved network kernel density estimation Type de document : Article/Communication Auteurs : Boxi Shen, Auteur ; Xiang Xu, Auteur ; Jun Li, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 683 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] circulation urbaine [Termes descripteurs IGN] estimation par noyau [Termes descripteurs IGN] Map Matching [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] modèle conceptuel de données localisées [Termes descripteurs IGN] modèle conceptuel de flux [Termes descripteurs IGN] Shenzhen [Termes descripteurs IGN] taxi [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] trajet Résumé : (auteur) Taxi mobility data plays an important role in understanding urban mobility in the context of urban traffic. Specifically, the taxi is an important part of urban transportation, and taxi trips reflect human behaviors and mobility patterns, allowing us to identify the spatial variety of such patterns. Although taxi trips are generated in the form of network flows, previous works have rarely considered network flow patterns in the analysis of taxi mobility data; Instead, most works focused on point patterns or trip patterns, which may provide an incomplete snapshot. In this work, we propose a novel approach to explore the spatial-temporal patterns of taxi travel by considering point, trip and network flow patterns in a simultaneous fashion. Within this approach, an improved network kernel density estimation (imNKDE) method is first developed to estimate the density of taxi trip pick-up and drop-off points (ODs). Next, the correlation between taxi service activities (i.e., ODs) and land-use is examined. Then, the trip patterns of taxi trips and its corresponding routes are analyzed to reveal the correlation between trips and road structure. Finally, network flow analysis for taxi trip among areas of varying land-use types at different times are performed to discover spatial and temporal taxi trip ODs from a new perspective. A case study in the city of Shenzhen, China, is thoroughly presented and discussed for illustrative purposes. Numéro de notice : A2020-730 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9110683 date de publication en ligne : 15/11/2020 En ligne : https://doi.org/10.3390/ijgi9110683 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96337 [article]

From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity / Elham Naghizade in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 10 (October 2020) . - pp 2004 - 2029 Titre : From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity Type de document : Article/Communication Auteurs : Elham Naghizade, Auteur ; jeffrey Chan, Auteur ; Martin Tomko, Auteur Année de publication : 2020 Article en page(s) : pp 2004 - 2029 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] comportement [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] gestion de trafic [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] mouvement [Termes descripteurs IGN] origine - destination [Termes descripteurs IGN] trajectoire [Termes descripteurs IGN] trajet [Termes descripteurs IGN] voyage Résumé : (auteur) The ubiquity of personal sensing devices has enabled the collection of large, diverse, and fine-grained spatio-temporal datasets. These datasets facilitate numerous applications from traffic monitoring and management to location-based services. Recently, there has been an increasing interest in profiling individuals' movements for personalized services based on fine-grained trajectory data. Most approaches identify the most representative paths of a user by analyzing coarse location information, e.g., frequently visited places. However, even for trips that share the same origin and destination, individuals exhibit a variety of behaviors (e.g., a school drop detour, a brief stop at a supermarket). The ability to characterize and compare the variability of individuals' fine-grained movement behavior can greatly support location-based services and smart spatial sampling strategies. We propose a TRip DIversity Measure --TRIM – that quantifies the regularity of users' path choice between an origin and destination. TRIM effectively captures the extent of the diversity of the paths that are taken between a given origin and destination pair, and identifies users with distinct movement patterns, while facilitating the comparison of the movement behavior variations between users. Our experiments using synthetic and real datasets and across geographies show the effectiveness of our method. Numéro de notice : A2020-512 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1730849 date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1080/13658816.2020.1730849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95666 [article]

Prediction of RTK positioning integrity for journey planning / A. El-Mowafy in Journal of applied geodesy, vol 14 n° 4 (October 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 4 (October 2020) . - pp 431 – 443 Titre : Prediction of RTK positioning integrity for journey planning Type de document : Article/Communication Auteurs : A. El-Mowafy, Auteur ; Nobuaki Kubo, Auteur Année de publication : 2020 Article en page(s) : pp 431 – 443 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] gestion des itinéraires [Termes descripteurs IGN] modèle 3D de l'espace urbain [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] planification [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] Receiver Autonomous Integrity Monitoring [Termes descripteurs IGN] système de transport intelligent [Termes descripteurs IGN] Tokyo (Japon) [Termes descripteurs IGN] trajet Résumé : (auteur) Positioning integrity is crucial for Intelligent Transport Systems (ITS) applications. In this article, a method is presented for prediction of GNSS positioning integrity for ITS journey planning. This information, in addition to other route information, such as distance and time, can be utilized to choose the safest and economical route. We propose to combine the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) technique, tailored for ITS, with 3D city models. Positioning is performed by GNSS Real-Time Kinematic (RTK) method, which can provide the accuracy required for ITS. A new threat model employed for computation of the protection levels (PLs) for RTK positioning is discussed. Demonstration of the proposed approach is performed through a kinematic test in an urban area in Tokyo. The comparison between the prediction method and the actual observations show that the two estimate close satellite geometry and PLs. The method produced PLs that bounds the actual position errors all the time and they were less than the preset alert limit. Numéro de notice : A2020-678 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0038 date de publication en ligne : 20/10/2020 En ligne : https://doi.org/10.1515/jag-2020-0038 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96174 [article]

Map construction algorithms: a local evaluation through hiking data / David Duran in Geoinformatica [en ligne], vol 24 n° 3 (July 2020)  

Public [article]  inGeoinformatica [en ligne] > vol 24 n° 3 (July 2020) . - pp 633 – 681 Titre : Map construction algorithms: a local evaluation through hiking data Type de document : Article/Communication Auteurs : David Duran, Auteur ; Vera Sacristan, Auteur ; Rodrigo I. Silveira, Auteur Année de publication : 2020 Article en page(s) : pp 633 – 681 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] artefact [Termes descripteurs IGN] cartographie automatique [Termes descripteurs IGN] conception cartographique [Termes descripteurs IGN] randonnée [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] rédaction cartographique [Termes descripteurs IGN] trajet Résumé : (auteur) We study five existing map construction algorithms, designed and tested with urban vehicle data in mind, and apply them to hiking trajectories with different terrain characteristics. Our main goal is to better understand the existing strategies and their limitations, in order to shed new light into the current challenges for map construction algorithms. We carefully analyze the results obtained by each algorithm focusing on the local details of the generated maps. Our analysis includes the characterization of 10 types of common artifacts, which occur in the results of more than one algorithm, and 7 algorithmic-specific artifacts, which are consequences of different algorithmic strategies. This allows us to extract systematic conclusions about the main challenges to fully automatize the construction of maps from trajectory data, to detect the strengths and weaknesses of the potential different strategies, and to suggest possible ways to design higher-quality map construction methods. We consider that this analysis will be of help for designing new and better methods that perform well in wider and more realistic contexts, not only for road map or hiking reconstruction, but also for other types of trajectory data. Numéro de notice : A2020-371 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-019-00386-7 date de publication en ligne : 26/02/2020 En ligne : https://doi.org/10.1007/s10707-019-00386-7 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95266 [article]

Developing shopping and dining walking indices using POIs and remote sensing data / Yingbin Deng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 22 p. Titre : Developing shopping and dining walking indices using POIs and remote sensing data Type de document : Article/Communication Auteurs : Yingbin Deng, Auteur ; Yingwei Yan, Auteur ; Yichun Xie, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 22 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] achat [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] distance [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] loisir [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] sport [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] trajet Résumé : (auteur) Walking is one of the most commonly promoted traveling methods and is garnering increasing attention. Many indices/scores have been developed by scholars to measure the walkability in a local community. However, most existing walking indices/scores involve urban planning-oriented, local service-oriented, regional accessibility-oriented, and physical activity-oriented walkability assessments. Since shopping and dining are two major leisure activities in our daily lives, more attention should be given to the shopping or dining-oriented walking environment. Therefore, we developed two additional walking indices that focus on shopping or dining. The point of interest (POI), vegetation coverage, water coverage, distance to bus/subway station, and land surface temperature were employed to construct walking indices based on 50-meter street segments. Then, walking index values were categorized into seven recommendation levels. The field verification illustrates that the proposed walking indices can accurately represent the walking environment for shopping and dining. The results in this study could provide references for citizens seeking to engage in activities of shopping and dining with a good walking environment. Numéro de notice : A2020-310 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060366 date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060366 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95157 [article]

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)  

Permalink

Analyse spatio-temporelle des mobilités de randonneurs dans le PNR du Massif des Bauges / Colin Kerouanton (2020)  

Permalink

SMSM: 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

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records / Zhang Liu in Transactions in GIS, vol 22 n° 2 (April 2018)  

Permalink

Multilevel visualization of travelogue trajectory data / Yongsai Ma in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Permalink

Unveiling movement uncertainty for robust trajectory similarity analysis / Andre Salvaro Furtado in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)  

Permalink

An analysis of movement patterns between zones using taxi GPS data / Zhanlong Chen in Transactions in GIS, vol 21 n° 6 (December 2017)  

Permalink

Extracting spatial patterns in bicycle routes from crowdsourced data / Jody Sultan in Transactions in GIS, vol 21 n° 6 (December 2017)  

Permalink

Apports et limites des données passives de la téléphonie mobile pour la construction de matrices origine-destination / Patrick Bonnel in Revue d'économie régionale et urbaine, vol 2017 n° 4 (2017-4)  

Permalink

Ship Traffic Simulation to assess noise exposure of whale populations in Canada / Axel Orger (2017) 

Permalink