Centre dedocumentation
scientifique

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)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 2 (February 2020) 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 descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] distance euclidienne [Termes descripteurs IGN] données de flux [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] origine - destination [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] taxi [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] zone urbaine Résumé : (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 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 [article]

Pré-localisation des données pour la modélisation 3D de tunnels : développements et évaluations / Christophe Heinkelé in Revue Française de Photogrammétrie et de Télédétection, n° 221 (novembre 2019)

Public [article]  inRevue Française de Photogrammétrie et de Télédétection > n° 221 (novembre 2019) . - pp 49 - 62 Titre : Pré-localisation des données pour la modélisation 3D de tunnels : développements et évaluations Type de document : Article/Communication Auteurs : Christophe Heinkelé, Auteur ; Philippe Foucher, Auteur ; Emmanuel Moisan, Auteur ; Pierre Charbonnier, Auteur Année de publication : 2019 Article en page(s) : pp 49 - 62 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] coordonnées curvilignes [Termes descripteurs IGN] disparité [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] odomètre [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] séquence d'images [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] structure-from-motion [Termes descripteurs IGN] tunnel [Termes descripteurs IGN] visualisation de données Résumé : (Auteur) Le présent article décrit l'implémentation d'une méthode de pré-localisation d'images au sein de grands volumes de données dans des tunnels navigables et routiers. Elle repose sur une technique d'odométrie visuelle simplifiée, rapide et facile à mettre en oeuvre et dont la précision est évaluée par comparaison avec des techniques plus conventionnelles. Nous expliquons comment cette méthode permet de former des sous-ensembles d'images se rapportant à une même coupe transversale de l'ouvrage et présentant un fort taux de recouvrement, appelés "tuiles". Ces sous-ensembles permettent de faciliter la navigation dans les séquences ainsi que les traitements postérieurs, comme par exemple la reconstruction 3D par photogrammétrie. Numéro de notice : A2019-564 Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94429 [article]

Réservation

Réserver ce document

Exemplaires (2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
018-2019021	SL	Revue	Centre de documentation	Revues en salle	Disponible
018-2019022	SL	Revue	Centre de documentation	Revues en salle	Disponible

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)  

Public [article]  inTransactions in GIS > Vol 23 n° 5 (October 2019) . - pp 1125 - 1151 Titre : A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy Type de document : Article/Communication Auteurs : Yan Zhou, Auteur ; Yanxi Li, Auteur ; Qing Zhu, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1125 - 1151 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] bicyclette [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] gestion prévisionnelle [Termes descripteurs IGN] New York (Etats-Unis ; ville) [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] SOLAP [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] Washington D.C. Résumé : (auteur) Bike‐sharing systems have been widely used in major cities across the world. As bike borrowing and return at different stations in different periods are not balanced, the bikes in a bike‐sharing system need to be redistributed frequently to rebalance the system. Therefore, traffic flow forecasting of the bike‐sharing system is an important issue, as this is conducive to achieving rebalancing of the bike system. In this article, we present a new traffic flow prediction approach based on the temporal links in dynamic traffic flow networks. A station clustering algorithm is first introduced to cluster stations into groups. A temporal link prediction method based on the dynamic traffic flow network method (STW+M) is then proposed to predict the traffic flow between stations. In our method, the non‐negative tensor decomposition and time‐series analysis model capture the rich information (temporal variabilities, spatial characteristics, and weather information) of the across‐clusters transition. Then, a temporal link prediction strategy is used to forecast potential links and weights in the traffic flow network by investigating both the network structure and the results of tensor computations. In order to assess the methods proposed in this article, we have used the data of bike‐sharing systems in New York and Washington, DC to conduct bike traffic prediction and the experimental results have shown that our method produces the lowest root mean square error (RMSE) and mean square error (MSE). Compared to four prediction methods from the literature, our RMSE and MSE of the two datasets have been lowered by an average of 2.55 (Washington, DC) and 2.41 (New York) and 3.35 (Washington, DC) and 2.96 (New York), respectively. The results show that the proposed approach improves predictions of traffic flow. Numéro de notice : A2019-551 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12560 date de publication en ligne : 03/07/2019 En ligne : https://doi.org/10.1111/tgis.12560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94201 [article]

A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data / Luis Vilches-Blazquez in Transactions in GIS, vol 23 n° 1 (February 2019)  

Public [article]  inTransactions in GIS > vol 23 n° 1 (February 2019) . - pp 22 - 47 Titre : A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data Type de document : Article/Communication Auteurs : Luis Vilches-Blazquez, Auteur ; Jhonny Saavedra, Auteur Année de publication : 2019 Article en page(s) : pp 22 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] cadre conceptuel [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] données multisources [Termes descripteurs IGN] GML [Termes descripteurs IGN] interopérabilité [Termes descripteurs IGN] partage de données localisées [Termes descripteurs IGN] RDF [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] Web des données [Termes descripteurs IGN] Web Feature Service [Termes descripteurs IGN] web sémantique Résumé : (auteur) Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi‐structured datasets, and often use distinct data models, are encoded using ad‐hoc vocabularies, and sometimes are being published in non‐standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non‐expert users. Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain. Numéro de notice : A2019-089 Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12496 date de publication en ligne : 28/11/2018 En ligne : https://doi.org/10.1111/tgis.12496 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92236 [article]

Progressive amalgamation of building clusters for map generalization based on scaling subgroups / Xianjin He in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 3 (March 2018) Titre : Progressive amalgamation of building clusters for map generalization based on scaling subgroups Type de document : Article/Communication Auteurs : Xianjin He, Auteur ; Xinchang Zhang, Auteur ; Jie Yang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] représentation multiple [Vedettes matières IGN] Généralisation Résumé : (Auteur) Map generalization utilizes transformation operations to derive smaller-scale maps from larger-scale maps, and is a key procedure for the modelling and understanding of geographic space. Studies to date have largely applied a fixed tolerance to aggregate clustered buildings into a single object, resulting in the loss of details that meet cartographic constraints and may be of importance for users. This study aims to develop a method that amalgamates clustered buildings gradually without significant modification of geometry, while preserving the map details as much as possible under cartographic constraints. The amalgamation process consists of three key steps. First, individual buildings are grouped into distinct clusters by using the graph-based spatial clustering application with random forest (GSCARF) method. Second, building clusters are decomposed into scaling subgroups according to homogeneity with regard to the mean distance of subgroups. Thus, hierarchies of building clusters can be derived based on scaling subgroups. Finally, an amalgamation operation is progressively performed from the bottom-level subgroups to the top-level subgroups using the maximum distance of each subgroup as the amalgamating tolerance instead of using a fixed tolerance. As a consequence of this step, generalized intermediate scaling results are available, which can form the multi-scale representation of buildings. The experimental results show that the proposed method can generate amalgams with correct details, statistical area balance and orthogonal shape while satisfying cartographic constraints (e.g., minimum distance and minimum area). Numéro de notice : A2018-102 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030116 En ligne : https://doi.org/10.3390/ijgi7030116 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89517 [article]

Knowledge-guided consistent correlation analysis of multimode landslide monitoring data / Shuangxi Miao in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)  

Permalink

A geometric correspondence feature based-mismatch removal in vision based-mapping and navigation / Zeyu Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 10 (October 2017)  

Permalink

3D building roof reconstruction from airborne LiDAR point clouds : a framework based on a spatial database / Rujun Cao in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)  

Permalink

Graph mapping: Multi-scale community visualization of massive graph data / David Jonker in Information visualization, vol 16 n° 3 (July 2017)  

Permalink

Evaluating data stability in aggregation structures across spatial scales: revisiting the modifiable areal unit problem / Jonathan K. Nelson in Cartography and Geographic Information Science, Vol 44 n° 1 (January 2017)  

Permalink

Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test / Moshen Kalantari in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)  

Permalink

Modeling spatiotemporal information generation / Simon Scheider in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)  

Permalink

A hierarchical approach to three-dimensional segmentation of LiDAR data at single-tree level in a multilayered forest / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)  

Permalink

Classification of remotely sensed images using the geneSIS fuzzy segmentation algorithm / Stelios Mylonas in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)  

Permalink

Points of interest recommendation from GPS trajectories / Yaqiong Liu in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)  

Permalink