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Ajouter le résultat dans votre panierA framework for group converging pattern mining using spatiotemporal trajectories / Bin Zhao in Geoinformatica, vol 24 n° 4 (October 2020)
[article]
Titre : A framework for group converging pattern mining using spatiotemporal trajectories Type de document : Article/Communication Auteurs : Bin Zhao, Auteur ; Xintao Liu, Auteur ; Jinping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 745 - 776 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] base de données d'objets mobiles
[Termes IGN] base de données spatiotemporelles
[Termes IGN] comportement
[Termes IGN] convergence
[Termes IGN] exploration de données géographiques
[Termes IGN] jointure spatiale
[Termes IGN] objet mobile
[Termes IGN] reconnaissance de formesRésumé : (Auteur) A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents such as serious stampedes. However, most of existing literature put too much emphasis on the second stage, only a few of them is dedicated to the first stage. In this paper, we propose a novel group pattern, namely converging, which refers to a group of moving objects converging from different directions during a certain period before gathered. To discover efficiently such converging patterns, we develop a framework for converging pattern mining (CPM) by examining how moving objects form clusters and the process of the “cluster containment”. The framework consists of three phases: snapshot cluster discovery phase, cluster containment join phase, and converging detection phase. As cluster containment mining is the key step, we develop three algorithms to discover cluster containment matches: a containment-join-algorithm, called SSCCJ, by using spatial proximity; a signature tree-based cluster-containment-join-algorithm, called STCCJ, which takes advantage of the cluster containment relations and signature techniques to filter enormous unqualified candidates in an efficient and effective way; and third, to keep the advantages of the above algorithms while avoiding their flaws, we further propose a signature quad-tree based cluster-containment-join algorithm, called SQTCCJ, which can identify efficiently matches by considering cluster spatial proximity as well as containment relations simultaneously. To assess the proposed methods, we redefine two evaluation metrics based on the concept of “Precision and Recall” in the field of information retrieval and the characteristics of converging patterns. We also propose a new indicator for measuring the duration of the converging stage in a group event. Finally, the effectiveness of the CPM and the efficiency of the mining algorithms are evaluated using three types of trajectory datasets, and the results show that the SQTCCJ algorithm demonstrates a superior performance. Numéro de notice : A2020-494 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00404-z Date de publication en ligne : 25/04/2020 En ligne : https://doi.org/10.1007/s10707-020-00404-z Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96114
in Geoinformatica > vol 24 n° 4 (October 2020) . - pp 745 - 776[article]Road network simplification for location-based services / Abdeltawab M. Hendawi in Geoinformatica, vol 24 n° 4 (October 2020)
[article]
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 IGN] algorithme de Douglas-Peucker
[Termes IGN] appariement de cartes
[Termes IGN] appariement de données localisées
[Termes IGN] appariement de graphes
[Termes IGN] carte routière
[Termes IGN] compression de données
[Termes IGN] modèle de Markov caché
[Termes IGN] réseau routier
[Termes IGN] service fondé sur la position
[Termes IGN] simplification de contour
[Termes 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 > vol 24 n° 4 (October 2020) . - pp 801 - 826[article]A novel spectral–spatial based adaptive minimum spanning forest for hyperspectral image classification / Jing Lv in Geoinformatica, vol 24 n° 4 (October 2020)
[article]
Titre : A novel spectral–spatial based adaptive minimum spanning forest for hyperspectral image classification Type de document : Article/Communication Auteurs : Jing Lv, Auteur ; Huimin Zhang, Auteur ; Ming Yang, Auteur ; Wanqi Yang, Auteur Année de publication : 2020 Article en page(s) : pp 827 - 848 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre aléatoire minimum
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification pixellaire
[Termes IGN] image hyperspectrale
[Termes IGN] segmentation d'imageRésumé : (Auteur) The classification methods based on minimum spanning forest (MSF) have yielded impressive results for hyperspectral image. However, previous methods exist several drawbacks, i.e., marker selection methods are easily affected by boundary noise pixels, dissimilarity measure methods between pixels are inaccurate, and also image segmentation process is not robust, since they have not effectively utilized spatial information. To this end, in this paper, novel gradient-based marker selection technique, dissimilarity measures, and adaptive connection weighting method are proposed by making full use of spatial information in hyperspectral image. Concretely, for a given hyperspectral image, a pixel-wise classification is firstly performed, and meanwhile the gradient map is generated by a morphology-based algorithm. Secondly, the most reliable pixels are selected as the markers from the classification map, and then the boundary noise pixels are excluded from the marker map by using the gradient map. Thirdly, several new dissimilarity measures are proposed by incorporating gradient information or probability information of pixels. Furthermore, in the growth procedure of MSF, the connection weighting between pixels is adjusted adaptively to improve the robustness of the MSF algorithm. Finally, when building the final classification map by using the majority voting rule, the labels of the training samples are used to dominate the label prediction. Experimental results are performed on two hyperspectral image sets Indian Pines and University of Pavia with different resolutions and contexts. The proposed approach yields higher classification accuracies compared to previously proposed classification methods, and provides accurate segmentation maps. Numéro de notice : A2020-496 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00403-0 Date de publication en ligne : 11/05/2020 En ligne : https://doi.org/10.1007/s10707-020-00403-0 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96117
in Geoinformatica > vol 24 n° 4 (October 2020) . - pp 827 - 848[article]JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases / Angeol A. Frozza in Geoinformatica, vol 24 n° 4 (October 2020)
[article]
Titre : JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases Type de document : Article/Communication Auteurs : Angeol A. Frozza, Auteur ; Ronaldo dos S. Mello, Auteur Année de publication : 2020 Article en page(s) : pp 987 - 1019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données localisées
[Termes IGN] données massives
[Termes IGN] format JSON
[Termes IGN] intégration de données
[Termes IGN] interopérabilité
[Termes IGN] NoSQL
[Termes IGN] système d'information géographique
[Termes IGN] système de gestion de base de donnéesRésumé : (Auteur) The large volume and variety of data produced in the current Big Data era lead companies to seek solutions for the efficient data management. Within this context, NoSQL databases rise as a better alternative to the traditional relational databases, mainly in terms of scalability and availability of data. A usual feature of NoSQL databases is to be schemaless, i.e., they do not impose a schema or have a flexible schema. This is interesting for systems that deal with complex data, such as GIS. However, the lack of a schema becomes a problem when applications need to perform processes such as data validation, data integration, or data interoperability, as there is no pattern for schema representation in NoSQL databases. On the other hand, the JSON language stands out as a standard for representing and exchanging data in document NoSQL databases, and JSON Schema is a schema representation language for JSON documents that it is also leading to become a standard. However, it does not include spatial data types. From this limitation, this paper proposes an extension to JSON Schema, called JS4Geo, that allows the definition of schemas for geographic data. We demonstrate that JS4Geo is able to represent schemas of any NoSQL data model, as well as other standards for geographic data, like GML and KML. We also present a case study that shows how a data integration system can benefit of JS4Geo to define local schemas for geographic datasets and generate an integrated global schema. Numéro de notice : A2020-497 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00415-w Date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s10707-020-00415-w Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96118
in Geoinformatica > vol 24 n° 4 (October 2020) . - pp 987 - 1019[article]