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Road network simplification for location-based services / Abdeltawab M. Hendawi in Geoinformatica [en ligne], vol 24 n° 4 (October 2020)
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Titre : Road network simplification for location-based services Type de document : Article/Communication Auteurs : Abdeltawab M. Hendawi, Auteur ; John A. Stankovic, Auteur ; Ayman Taha, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 801 - 826 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de Douglas-Peucker
[Termes descripteurs IGN] appariement de données localisées
[Termes descripteurs IGN] appariement de graphes
[Termes descripteurs IGN] carte routière
[Termes descripteurs IGN] compression de données
[Termes descripteurs IGN] Hidden Markov Model (HMM)
[Termes descripteurs IGN] Map Matching
[Termes descripteurs IGN] réseau routier
[Termes descripteurs IGN] service fondé sur la position
[Termes descripteurs IGN] simplification de contour
[Termes descripteurs IGN] stockage de données
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Road-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of memory and disks, and (b) reduces the I/O and communication overhead. There are several road network compression techniques proposed in the literature. These techniques are evaluated by their compression ratios. However, none of these techniques takes into consideration the possibility that the generated compressed data can be used directly in Map-matching operation which is an essential component for all location-aware services. Map-matching matches a measured latitude and longitude of an object to an edge in the road network graph. In this paper, we propose a novel simplification technique, named COMA, that (1) significantly reduces the size of a given road network graph, (2) achieves high map-matching quality on the simplified graph, and (3) enables the generated compressed road network graph to be used directly in map-matching and location-based applications without a need to decompress it beforehand. COMA smartly deletes those nodes and edges that will not affect the graph connectivity nor causing much of ambiguity in the map-matching of objects’ location. COMA employs a controllable parameter; termed a conflict factor C, whereby location aware services can trade the compression gain with map-matching accuracy at varying granularity. We show that the time complexity of our COMA algorithm is O(|N|log|N|). Intensive experimental evaluation based on a real implementation and data demonstrates that COMA can achieve about a 75% compression-ratio while preserving high map-matching quality. Road Network, Simplification, Compression, Spatial, Location, Performance, Accuracy, Efficiency, Scalability. Numéro de notice : A2020-495 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00406-x date de publication en ligne : 01/05/2020 En ligne : https://doi.org/10.1007/s10707-020-00406-x Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96115
in Geoinformatica [en ligne] > vol 24 n° 4 (October 2020) . - pp 801 - 826[article]Hub Labels on the database for large-scale graphs with the COLD framework / Alexandros Efentakis in Geoinformatica [en ligne], vol 21 n° 4 (October - December 2017)
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Titre : Hub Labels on the database for large-scale graphs with the COLD framework Type de document : Article/Communication Auteurs : Alexandros Efentakis, Auteur ; Christodoulos Efstathiades, Auteur ; Dieter Pfoser, Auteur Année de publication : 2017 Article en page(s) : pp 703 - 732 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] base de données localisées
[Termes descripteurs IGN] chemin le plus court (algorithme)
[Termes descripteurs IGN] compression de données
[Termes descripteurs IGN] graphe
[Termes descripteurs IGN] plus proche voisin (algorithme)
[Termes descripteurs IGN] SQLRésumé : (Auteur) Shortest-path computation on graphs is one of the most well-studied problems in algorithmic theory. An aspect that has only recently attracted attention is the use of databases in combination with graph algorithms, so-called distance oracles, to compute shortest-path queries on large graphs. To this purpose, we propose a novel, efficient, pure-SQL framework for answering exact distance queries on large-scale graphs, implemented entirely on an open-source database engine. Our COLD framework (COmpressed Labels on the Database) can answer multiple distance queries (vertex-to-vertex, one-to-many, k-Nearest Neighbors, Reverse k-Nearest Neighbors, Reverse k-Farthest Neighbors and Top-k Range) not handled by previous methods, rendering it a complete database solution for a variety of practical large-scale graph applications. Our experimentation shows that COLD outperforms existing approaches (including popular graph databases) in terms of query time and efficiency, while requiring significantly less storage space than these methods. Numéro de notice : A2017-601 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0287-5 En ligne : https://doi.org/10.1007/s10707-016-0287-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86909
in Geoinformatica [en ligne] > vol 21 n° 4 (October - December 2017) . - pp 703 - 732[article]Traitement des nuages de points sous PostGIS / Ludovic Delauné in Géomatique expert, n° 113 (novembre - décembre 2016)
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Titre : Traitement des nuages de points sous PostGIS Type de document : Article/Communication Auteurs : Ludovic Delauné, Auteur Année de publication : 2016 Article en page(s) : pp 19 - 20 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes descripteurs IGN] compression de données
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] format LAS
[Termes descripteurs IGN] PostGIS
[Termes descripteurs IGN] semis de points
[Termes descripteurs IGN] stockage de donnéesRésumé : (Auteur) [Introduction] Les nuages de points issus des survols laser sont une description remarquablement précise de notre environnement, à partir de laquelle il est possible de dériver un nombre important de données. Cette richesse est en partie liée à leur densité : un équipement de type LIDAR relève jusqu'à deux millions de points par seconde. Cela signifie sept milliards par heure, ces points étant caractérisés par des coordonnées d'espace (x, y, z) plus - accessoirement - des informations de couleurs et/ou de réflectance. Tout cela donne des fichiers qui peuvent facilement atteindre plusieurs téra-octets. D'où la question : comment les stocker pour les exploiter efficacement ? [...] Numéro de notice : A2016-960 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83617
in Géomatique expert > n° 113 (novembre - décembre 2016) . - pp 19 - 20[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 265-2016061 SL Revue Centre de documentation Revues en salle Disponible IFN-001-P001918 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt SPLZ: An efficient algorithm for single source shortest path problem using compression method / Jingwei Sun in Geoinformatica [en ligne], vol 20 n° 1 (January - March 2016)
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Titre : SPLZ: An efficient algorithm for single source shortest path problem using compression method Type de document : Article/Communication Auteurs : Jingwei Sun, Auteur ; Guangzhong Sun, Auteur Année de publication : 2016 Article en page(s) : pp 1 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes descripteurs IGN] algorithme de la plus proche paire
[Termes descripteurs IGN] chemin le plus court (algorithme)
[Termes descripteurs IGN] compression de données
[Termes descripteurs IGN] réseau routier
[Termes descripteurs IGN] traitement de données localiséesRésumé : (auteur) Efficient solution of the single source shortest path (SSSP) problem on road networks is an important requirement for numerous real-world applications. This paper introduces an algorithm for the SSSP problem using compression method. Owning to precomputing and storing all-pairs shortest path (APSP), the process of solving SSSP problem is a simple lookup of a little data from precomputed APSP and decompression. APSP without compression needs at least 1TB memory for a road network with one million vertices. Our algorithm can compress such an APSP into several GB, and ensure a good performance of decompression. In our experiment on a dataset about Northwest USA (with 1.2 millions vertices), our method can achieve about three orders of magnitude faster than Dijkstra algorithm based on binary heap. Numéro de notice : A2016-365 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article En ligne : http://dx.doi.org/10.1007/s10707-015-0229-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81128
in Geoinformatica [en ligne] > vol 20 n° 1 (January - March 2016) . - pp 1 - 18[article]Compression strategies for LiDAR waveform cube / Grzegorz Jóźków in ISPRS Journal of photogrammetry and remote sensing, vol 99 (January 2015)
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Titre : Compression strategies for LiDAR waveform cube Type de document : Article/Communication Auteurs : Grzegorz Jóźków, Auteur ; Charles K. Toth, Auteur ; Mihaela Quirk, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1 - 13 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes descripteurs IGN] compression de données
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] forme d'onde pleineRésumé : (Auteur) Full-waveform LiDAR data (FWD) provide a wealth of information about the shape and materials of the surveyed areas. Unlike discrete data that retains only a few strong returns, FWD generally keeps the whole signal, at all times, regardless of the signal intensity. Hence, FWD will have an increasingly well-deserved role in mapping and beyond, in the much desired classification in the raw data format. Full-waveform systems currently perform only the recording of the waveform data at the acquisition stage; the return extraction is mostly deferred to post-processing. Although the full waveform preserves most of the details of the real data, it presents a serious practical challenge for a wide use: much larger datasets compared to those from the classical discrete return systems. Atop the need for more storage space, the acquisition speed of the FWD may also limit the pulse rate on most systems that cannot store data fast enough, and thus, reduces the perceived system performance. This work introduces a waveform cube model to compress waveforms in selected subsets of the cube, aimed at achieving decreased storage while maintaining the maximum pulse rate of FWD systems. In our experiments, the waveform cube is compressed using classical methods for 2D imagery that are further tested to assess the feasibility of the proposed solution. The spatial distribution of airborne waveform data is irregular; however, the manner of the FWD acquisition allows the organization of the waveforms in a regular 3D structure similar to familiar multi-component imagery, as those of hyper-spectral cubes or 3D volumetric tomography scans. This study presents the performance analysis of several lossy compression methods applied to the LiDAR waveform cube, including JPEG-1, JPEG-2000, and PCA-based techniques. Wide ranges of tests performed on real airborne datasets have demonstrated the benefits of the JPEG-2000 Standard where high compression rates incur fairly small data degradation. In addition, the JPEG-2000 Standard-compliant compression implementation can be fast and, thus, used in real-time systems, as compressed data sequences can be formed progressively during the waveform data collection. We conclude from our experiments that 2D image compression strategies are feasible and efficient approaches, thus they might be applied during the acquisition of the FWD sensors. Numéro de notice : A2014-633 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://www.sciencedirect.com/science/article/pii/S0924271614002536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75059
in ISPRS Journal of photogrammetry and remote sensing > vol 99 (January 2015) . - pp 1 - 13[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2015011 RAB Revue Centre de documentation En réserve 3L Disponible Compression of trajectory data: a comprehensive evaluation and new approach / Jonathan Muckell in Geoinformatica, vol 18 n° 3 (July 2014)
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PermalinkPermalinkPermalinkVariable-resolution compression of vector data / B. Yang in Geoinformatica, vol 12 n° 3 (September - November 2008)
PermalinkA compression format and tools for GNSS observation data / Y. Hatanaka in Bulletin of the Geographical survey institute, vol 55 n° 1 (01/03/2008)
PermalinkPermalinkData compression and OGC standards: "GML becoming the geospatial language of the web" / S. Bacharach in Geoinformatics, vol 9 n° 8 (01/12/2006)
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