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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)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 16 p. 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 GPS Résumé : (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 [article]

Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data / Yue Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 49 – 61 Titre : Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data Type de document : Article/Communication Auteurs : Yue Zhang, Auteur ; Xuan Sun, Auteur ; Antje Thiele, Auteur ; Stefan Hinz, Auteur Année de publication : 2015 Article en page(s) : pp 49 – 61 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] image radar moirée [Termes IGN] image TanDEM-X [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle stochastique [Termes IGN] optimisation (mathématiques) [Termes IGN] reconstruction 3D du bâti Résumé : (auteur) Synthetic aperture radar (SAR) systems, such as TanDEM-X, TerraSAR-X and Cosmo-SkyMed, acquire imagery with high spatial resolution (HR), making it possible to observe objects in urban areas with high detail. In this paper, we propose a new top-down framework for three-dimensional (3D) building reconstruction from HR interferometric SAR (InSAR) data. Unlike most methods proposed before, we adopt a generative model and utilize the reconstruction process by maximizing a posteriori estimation (MAP) through Monte Carlo methods. The reason for this strategy refers to the fact that the noisiness of SAR images calls for a thorough prior model to better cope with the inherent amplitude and phase fluctuations. In the reconstruction process, according to the radar configuration and the building geometry, a 3D building hypothesis is mapped to the SAR image plane and decomposed to feature regions such as layover, corner line, and shadow. Then, the statistical properties of intensity, interferometric phase and coherence of each region are explored respectively, and are included as region terms. Roofs are not directly considered as they are mixed with wall into layover area in most cases. When estimating the similarity between the building hypothesis and the real data, the prior, the region term, together with the edge term related to the contours of layover and corner line, are taken into consideration. In the optimization step, in order to achieve convergent reconstruction outputs and get rid of local extrema, special transition kernels are designed. The proposed framework is evaluated on the TanDEM-X dataset and performs well for buildings reconstruction. Numéro de notice : A2015-851 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.004 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79221 [article]

Geometric structure simplification of 3D building models / Qingquan Li in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 84 (October 2013) . - pp 100 - 113 Titre : Geometric structure simplification of 3D building models Type de document : Article/Communication Auteurs : Qingquan Li, Auteur ; Xuan Sun, Auteur ; Bisheng Yang, Auteur ; Shaobo Jiang, Auteur Année de publication : 2013 Article en page(s) : pp 100 - 113 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] bâtiment [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle numérique du bâti [Termes IGN] reconstruction 3D du bâti [Termes IGN] simplification de contour [Termes IGN] simplification de surface Résumé : (Auteur) The complexity of building models directly affects the application efficiencies of 3D urban maps. To address the challenges of building models with various structures, we propose a structural simplification method in this paper. The geometric structures of building models are classified into three categories: embedded structures, compositional structures, and connecting structures, which can be extracted separately through convex/concave analysis. Some specific rules are proposed for the simplification of geometric structures, and the building models are suggested to be simplified progressively. The robustness and efficiency of the method are demonstrated by experiments, and the applications of the Levels of detail of the building models are illustrated. Numéro de notice : A2013-519 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.07.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32656 [article]

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