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Documents disponibles écrits par cet auteur (2644)
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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)
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Titre : Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records Type de document : Article/Communication Auteurs : Zhang Liu, Auteur ; Ting Ma, Auteur ; Yunyan Du, Auteur ; Tao Pei, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 494 - 513 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] carte thématique
[Termes IGN] cartographie des flux
[Termes IGN] classification par réseau neuronal
[Termes IGN] mobilité urbaine
[Termes IGN] population urbaine
[Termes IGN] régression
[Termes IGN] téléphone intelligent
[Termes IGN] trace numérique
[Termes IGN] trajet (mobilité)Résumé : (Auteur) Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation. Numéro de notice : A2018-215 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12323 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1111/tgis.12323 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90006
in Transactions in GIS > vol 22 n° 2 (April 2018) . - pp 494 - 513[article]A novel computational knowledge-base framework for visualization and quantification of geospatial metadata in spatial data infrastructures / Gangothri Rajaram in Geoinformatica, vol 22 n° 2 (April 2018)
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Titre : A novel computational knowledge-base framework for visualization and quantification of geospatial metadata in spatial data infrastructures Type de document : Article/Communication Auteurs : Gangothri Rajaram, Auteur ; Harish Chandra Karnatak, Auteur ; Swaminathan Venkatraman, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 269 - 305 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] cadre conceptuel
[Termes IGN] métadonnées
[Termes IGN] métadonnées géographiques
[Termes IGN] pondération
[Termes IGN] qualité des metadonnées
[Termes IGN] service webRésumé : (Auteur) Advances in Metadata research have been instrumental in predictions and `fitness-of-use evaluation' for the effective Decision-making process. For the past two decades, the model has been developed to provide visual assistance for assessing the quality information in metadata and quantifying the degree of metadata population. Still, there is a need to develop a framework that can be generic to adopt all the standards available for Geospatial Metadata. The computational analysis of metadata for specific applications remains uncharted for investigations and studies. This work proposes a computational framework for Geospatial Metadata by integrating TopicMaps and Hypergraphs (HXTM) based on the elements and their dependency relationships. A purpose-built dataset extracted from schemas of various standardisation organisations and existing knowledge in the discipline is utilised to model the framework and thereby evaluate ranking strategies. Hypergraph-Helly Property based Weight-Assignment Algorithm (HHWA) have been proposed for HXTM framework to calculate Stable weights for Metadata Elements. Recursive use of Helly-property ensures predominant elements, while Rank Order Centroid (ROC) method is used to compute standard weights. A real corpus using case studies from FGDC's Standard for Geospatial Metadata, INSPIRE Metadata Standards, and ISRO Metadata Content Standard (NSDI 2.0) is used to validate the proposed framework. The observations show that the Information Gain (Entropy) of the proposed model along with the algorithm proves to be computationally smart for quantification purposes and visualises the strength of Metadata Elements for all applications. A prototype tool, `MetDEVViz- MetaData Editor, Validator &Visualization' is designed to exploit the benefits of the proposed algorithm for the case studies that acts as a web service to provide a user interface for editing, validating and visualizing metadata elements. Numéro de notice : A2018-365 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-018-0317-6 Date de publication en ligne : 28/02/2018 En ligne : https://doi.org/10.1007/s10707-018-0317-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90730
in Geoinformatica > vol 22 n° 2 (April 2018) . - pp 269 - 305[article]Space-time tree ensemble for action recognition and localization / Shugao Ma in International journal of computer vision, vol 126 n° 2-4 (April 2018)
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Titre : Space-time tree ensemble for action recognition and localization Type de document : Article/Communication Auteurs : Shugao Ma, Auteur ; Jianming Zhang, Auteur ; Stan Sclaroff, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 314 - 332 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre (mathématique)
[Termes IGN] géopositionnement
[Termes IGN] reconnaissance de gestesRésumé : (Auteur) Human actions are, inherently, structured patterns of body movements. We explore ensembles of hierarchical spatio-temporal trees, discovered directly from training data, to model these structures for action recognition and spatial localization. Discovery of frequent and discriminative tree structures is challenging due to the exponential search space, particularly if one allows partial matching. We address this by first building a concise action word vocabulary via discriminative clustering of the hierarchical space-time segments, which is a two-level video representation that captures both static and non-static relevant space-time segments of the video. Using this vocabulary we then utilize tree mining with subsequent tree clustering and ranking to select a compact set of discriminative tree patterns. Our experiments show that these tree patterns, alone, or in combination with shorter patterns (action words and pairwise patterns) achieve promising performance on three challenging datasets: UCF Sports, HighFive and Hollywood3D. Moreover, we perform cross-dataset validation, using trees learned on HighFive to recognize the same actions in Hollywood3D, and using trees learned on UCF-Sports to recognize and localize the similar actions in JHMDB. The results demonstrate the potential for cross-dataset generalization of the trees our approach discovers. Numéro de notice : A2018-407 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-016-0980-8 Date de publication en ligne : 02/02/2017 En ligne : https://doi.org/10.1007/s11263-016-0980-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90880
in International journal of computer vision > vol 126 n° 2-4 (April 2018) . - pp 314 - 332[article]The characteristics of asymmetric pedestrian behavior : A preliminary study using passive smartphone location data / Nick Malleson in Transactions in GIS, vol 22 n° 2 (April 2018)
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Titre : The characteristics of asymmetric pedestrian behavior : A preliminary study using passive smartphone location data Type de document : Article/Communication Auteurs : Nick Malleson, Auteur ; Anthony Vanky, Auteur ; Behrooz Hashemian, Auteur ; Paolo Santi, Auteur ; Santosh K. Verma, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 616 - 634 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] chemin le plus court, algorithme du
[Termes IGN] matrice
[Termes IGN] piéton
[Termes IGN] téléphone intelligent
[Termes IGN] trace numériqueRésumé : (Auteur) Understanding the movements of people is essential for the design and management of urban areas. This article presents a novel approach to understanding the asymmetry in route choice (i.e., the degree to which people choose different walking routes for their outbound and return journeys). The study utilizes a large volume of traces of individual routes, captured using a smartphone application. The routes are aggregated to a regular grid, and matrix statistics are developed to estimate the aggregate degree of route asymmetry for different types of route (shortest, longest, weekday, weekend, etc.). The results suggest that people change their route approximately 15% of the time. Although this varied little when observing trips made at the weekend or on a weekday, people taking journeys that deviated substantially from the shortest possible path were 6 percentage points less likely to change their routes than those taking journeys that were closest to the shortest path (14 and 20% asymmetry, respectively). The absolute length also impacted on the asymmetry of journeys, but not as substantially. This result is important because, for the first time, it reports a correlation between deviation from shortest route and aggregate pedestrian choice. Numéro de notice : A2018-218 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12336 Date de publication en ligne : 06/04/2018 En ligne : https://doi.org/10.1111/tgis.12336 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90010
in Transactions in GIS > vol 22 n° 2 (April 2018) . - pp 616 - 634[article]The national geographic characteristics of online public opinion propagation in China based on WeChat network / Chuan Ai in Geoinformatica, vol 22 n° 2 (April 2018)
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Titre : The national geographic characteristics of online public opinion propagation in China based on WeChat network Type de document : Article/Communication Auteurs : Chuan Ai, Auteur ; Bin Chen, Auteur ; Lingnan He, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 311 - 334 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] caractérisation
[Termes IGN] Chine
[Termes IGN] interaction spatiale
[Termes IGN] réseau social
[Termes IGN] villeRésumé : (Auteur) Offline networks have been the subject of intense academic scrutiny for many decades, but we still know little about the nationwide spatial interaction patterns and its application for public opinion management of online social networks. With the aim of uncovering the geographic interaction characteristics of online public opinion propagation, we analyze a large dataset obtained from WeChat, the most popular social media application in China, and construct the spatial interaction network G, which contains 359 city-nodes. It is found that the communities in the network and the administrative division corresponded well with each other, and cities with high betweenness and degree also develop well in the economy. Public opinion propagation depends on the state of online interaction. The findings indicate that public opinion should be managed separately by regions divided according to the community division, and different regions should adopt different management methods according to their economic, historical and political characteristics. In our work, the possibility and opportunity is presented to study the spatial interaction patterns of online public opinion propagation with the massive behavioral data and the methods of complex network. Numéro de notice : A2018-366 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-017-0311-4 En ligne : https://doi.org/10.1007/s10707-017-0311-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90731
in Geoinformatica > vol 22 n° 2 (April 2018) . - pp 311 - 334[article]All-sky search for long-duration gravitational wave transients in the first Advanced LIGO observing run / B.P. Abbott in Classical and Quantum Gravity, vol 35 n° 6 (March 2018)
PermalinkEuropean Forest Types: toward an automated classification / Francesca Giannetti in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkEvaluation of close-range photogrammetry image collection methods for estimating tree diameters / Martin Mokroš in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)
PermalinkGenerative street addresses from satellite imagery / İlke Demir in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)
PermalinkGRAPHOS – open‐source software for photogrammetric applications / Diego Gonzalez-Aguilera in Photogrammetric record, vol 33 n° 161 (March 2018)
PermalinkImage classification-based ground filtering of point clouds extracted from UAV-based aerial photos / Volkan Yilmaz in Geocarto international, vol 33 n° 3 (March 2018)
PermalinkQuality assessment and accessibility mapping in an image-based geocrowdsourcing testbed / Matthew T. Rice in Cartographica, vol 53 n° 1 (Spring 2018)
PermalinkSeasonal time-course of the above ground biomass production efficiency in beech trees (Fagus sylvatica L.) / Laura Heid in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkA spatio-temporal dataset of forest mensuration for the analysis of tree species structure and diversity in semi-natural mixed floodplain forests / Most Jannatul Fardusi in Annals of Forest Science, vol 75 n° 1 (March 2018)
PermalinkEPLA : efficient personal location anonymity / Dapeng Zhao in Geoinformatica, vol 22 n° 1 (January 2018)
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