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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)
[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]Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
[article]
Titre : Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection Type de document : Article/Communication Auteurs : Da He, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur Année de publication : 2020 Article en page(s) : pp 1696 - 1717 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification du maximum a posteriori
[Termes IGN] détection de changement
[Termes IGN] distribution spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image Quickbird
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle dynamique
[Termes IGN] optimisation spatiale
[Termes IGN] précision infrapixellaire
[Termes IGN] série temporelle
[Termes IGN] urbanisation
[Termes IGN] Wuhan (Chine)
[Termes IGN] zone urbaineRésumé : (Auteur) The maximum a posteriori (MAP) estimation model-based sub-pixel mapping (SPM) method is an alternative way to solve the ill-posed SPM problem. The MAP estimation model has been proven to be an effective SPM approach and has been extensively developed over the past few years, as a result of its effective regularization capability that comes from the spatial regularization model. However, various spatial regularization models do not always truly reflect the detailed spatial distribution in a real situation, and the over-smoothing effect of the spatial regularization model always tends to efface the detailed structural information. In this article, under the scenario of time-series observation by remote sensing imagery, the joint spectral–spatial–temporal MAP-based (SST_MAP) model for SPM is proposed. In SST_MAP, a newly developed temporal regularization model is added to the MAP model, based on the prerequisite for a temporally close fine image covering the same study region. This available fine image can provide the specific spatial structures most closely conforming to the ground truth for a more precise constraint, thereby reducing the over-smoothing effect. Furthermore, the three dimensions are mutually balanced and mutually constrained, to reach an equilibrium point and achieve restoration of both smooth areas for the homogeneous land-cover classes and a detailed structure for the heterogeneous land-cover classes. Four experiments were designed to validate the proposed SST_MAP: three synthetic-image experiments and one real-image experiment. The restoration results confirm the superiority of the proposed SST_MAP model. Notably, under the background of time-series observation, SST_MAP provides an alternative way of land-cover change detection (LCCD), achieving both detailed spatial-scale and high-frequency temporal LCCD observation for the study case of urbanization analysis within the city of Wuhan in China. Numéro de notice : A2020-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947708 Date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947708 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94662
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1696 - 1717[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]Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps / Alper Sen in Survey review, vol 52 n° 371 (March 2020)
[article]
Titre : Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps Type de document : Article/Communication Auteurs : Alper Sen, Auteur ; Baris Suleymanoglu, Auteur ; Metin Soycan, Auteur Année de publication : 2020 Article en page(s) : pp 150 - 158 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de filtrage
[Termes IGN] carte de Kohonen
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données lidar
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de points
[Termes IGN] filtre adaptatif
[Termes IGN] khi carré
[Termes IGN] pondération
[Termes IGN] réseau neuronal artificiel
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) The extraction of artificial and natural features using light detection and ranging (Lidar) data is a fundamental task in many fields of research for environmental science. In this study, the possibility of using self-organising maps (SOM), which is an unsupervised artificial neural network classification method to extract the bare earth surface and features from airborne Lidar data, was investigated for two different urban areas. The effect of the enlargement of the study area was analysed using the proposed approach. The appropriate weights of SOM inputs, which are 3D coordinates and intensity, obtained from a Lidar point cloud were determined by using Pearson's chi-squared independence test. The weighted SOM feature extraction performance was better than that of the unweighted SOM. The filtering results of SOM to separate ground and non-ground data were also compared with those obtained by the adaptive TIN filtering algorithm. Most of the non-ground features could be removed by the weighted SOM. Numéro de notice : A2020-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1532704 Date de publication en ligne : 12/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1532704 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94642
in Survey review > vol 52 n° 371 (March 2020) . - pp 150 - 158[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)PermalinkAutomated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference / Heidar Rastiveis in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkExtending Processing Toolbox for assessing the logical consistency of OpenStreetMap data / Sukhjit Singh Sehra in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkLand use and land cover change modeling and future potential landscape risk assessment using Markov-CA model and analytical hierarchy process / Biswajit Nath in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)PermalinkLandslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkObject‐oriented tracking of thematic and spatial behaviors of urban heat islands / Rui Zhu in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkTree annotations in LiDAR data using point densities and convolutional neural networks / Ananya Gupta in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkLa biodiversité à l’épreuve des choix d’aménagement : une approche par la modélisation appliquée à la Région Occitanie / Coralie Calvet in Sciences, eaux & territoires, n° 31 (janvier 2020)PermalinkAnalyse automatique du couvert végétal pour la gestion du risque végétation en milieu ferroviaire à partir d'imagerie aérienne / Hélène Rouillon (2020)PermalinkAnalyse de la distribution spatiale des implantations humaines : apports et limites d’indicateurs multi-échelles et trans-échelles / François Sémécurbe (2020)PermalinkAnalyse hydrologique du réseau de drainage de la zone sud de la métropole nantaise pour une meilleure gestion des eaux pluviales / Anna Guézénoc (2020)PermalinkApplication of geographic Information system and remote sensing in multiple criteria analysis to identify priority areas for biodiversity conservation in Vietnam / Xuan Dinh Vu (2020)PermalinkPermalinkPermalinkConstraint based evaluation of generalized images generated by deep learning / Azelle Courtial (2020)PermalinkCréation d’un outil d’interrogation du référentiel régional pédologique de Bretagne pour estimation du stock de carbone organique du sol / Louise Grall (2020)PermalinkPermalinkPermalinkDétection et vectorisation automatiqued’objets linéaires dans des nuages de points de voirie / Etienne Barçon (2020)PermalinkDevelopment of a GIS and model-based method for optimizing the selection of locations for drinking water extraction by means of riverbank filtration / Yan Zhou (2020)PermalinkDéveloppement d’une méthode d’intégration systématique des capteurs dans le BIM pour les constructions durables / Yasmine El Khadraoui (2020)PermalinkPermalinkEstimation of metabolic flows of urban environment based on fuzzy expert knowledge / Igor Patrakeyev in Geodesy and cartography, vol 46 n° 1 (January 2020)PermalinkEvaluation des mesures GPS effectuées par un smartphone Android Xiaomi Mi 8 / Umberto Robustelli in Géomatique expert, n° 132-133 (janvier - septembre 2020)PermalinkPermalinkPermalinkPermalinkGeographies of maritime transport, Ch. 4. Geography versus topology in the evolution of the global container shipping network (1977-2016) / César Ducruet (2020)PermalinkImproved indoor positioning based on range-free RSSI fingerprint method / Marcin Uradzinski in Journal of geodetic science, vol 10 n° 1 (January 2020)PermalinkInitiatives for Providing Data and Tools for Research and Education: EuroSDR survey / Bénédicte Bucher (2020)PermalinkMise en place d'un nouveau protocole relatif à la mise à jour de données géographiques produites par les Directions du Département des Hauts-de-Seine dans le SIG départemental / Gabriel Dousseau (2020)PermalinkLa modélisation en géographie / Denise Pumain (2020)PermalinkPermalinkA new cellular automata framework of urban growth modeling by incorporating statistical and heuristic methods / Yongjiu Feng in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)PermalinkOn the interoperability of IGS products for precise point positioning with ambiguity resolution / Simon Banville in Journal of geodesy, vol 94 n°1 (January 2020)PermalinkOptimiser la gestion conjointe de la voirie et des réseaux enterrés à l'aide de la géomatique : conception d'un référentiel spatial de voirie / Antonin Pavard (2020)PermalinkPotential of crowdsourced traces for detecting updates in authoritative geographic data / Stefan Ivanovic (2020)PermalinkPermalinkPratique des relevés en zones urbaines denses intégrant les nouvelles technologies / Théo Laporte (2020)PermalinkPermalinkRealistic modeling of power transmission lines with geographic information systems / Joram Schito (2020)PermalinkPermalinkReconnaissance automatique d’objets pour le jumeau numérique ferroviaire à partir d’imagerie aérienne / Valentin Desbiolles (2020)PermalinkPermalinkRevealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data / Yi Shi in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)Permalink