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Spatial co-location pattern mining of facility points-of-interest improved by network neighborhood and distance decay effects / Wenhao Yu in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)
[article]
Titre : Spatial co-location pattern mining of facility points-of-interest improved by network neighborhood and distance decay effects Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur ; Tinghua Ai, Auteur ; Yakun He, Auteur ; Shivei Shao, Auteur Année de publication : 2017 Article en page(s) : pp 280 - 296 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] co-positionnement
[Termes IGN] contrainte relationnelle
[Termes IGN] exploration de données
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] point d'intérêt
[Termes IGN] réseau routierRésumé : (auteur) The aim of mining spatial co-location patterns is to find the corresponding subsets of spatial features that have strong spatial correlation in the real world. This is an important technology for the extraction and comprehension of implicit knowledge in large spatial databases. However, existing methods of co-location mining consider events as taking place in a homogeneous and isotropic context in Euclidean space, whereas the physical movement in an urban space is usually constrained by a road network. Furthermore, previous works do not take the ‘distance decay effect’ of spatial interactions into account, which may reduce the effectiveness of the result. Here we propose an improved spatial co-location pattern mining method, including the network-constrained neighborhood and addition of a distance-decay function, to find the spatial dependence between network phenomena (e.g. urban facilities). The underlying idea is to utilize a model function in the interest measure calculation to weight the contribution of a co-location to the overall interest measure instance inversely proportional to the separation distance. Our approach was evaluated through extensive experiments using facility points-of-interest data sets. The results show that the network-constrained approach is a more effective method than the traditional one in network-structured space. The proposed approach can also be applied to other human activities (e.g. traffic accidents) constrained by a street network. Numéro de notice : A2017-033 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1194423 En ligne : http://dx.doi.org/10.1080/13658816.2016.1194423 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84026
in International journal of geographical information science IJGIS > vol 31 n° 1-2 (January - February 2017) . - pp 280 - 296[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017011 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017012 RAB Revue Centre de documentation En réserve L003 Disponible 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)
[article]
Titre : Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test Type de document : Article/Communication Auteurs : Moshen Kalantari, Auteur ; Bamshad Yaghmaei, Auteur ; Somaye Ghezelbash, Auteur Année de publication : 2016 Article en page(s) : pp 2302 - 2320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] fonction K de Ripley
[Termes IGN] interaction spatiale
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] protection civile
[Termes IGN] regroupement de données
[Termes IGN] sécurité informatiqueRésumé : (Auteur) The present study examined and compared spatio–temporal interaction of the theft of car parts, shop burglary and motorcycle theft in the central business district (CBD) of the city of Zanjan in Iran. The Knox test was selected to detect spatio–temporal interaction. This test has been criticized as being subjective because the selection of critical distances is arbitrary; thus, a method is proposed to detect critical distances in the Knox test using the mean distance, natural breaks classification of nearest neighbour (NN) distance and Ripley’s k function. Results show obvious differences between the spatio-temporal clusters of the three sets of crimes. They also indicate that changing the spatial cut-offs within a cluster creates different temporal patterns. Of the three criteria for determining critical distances, NN classification based on natural breaks showed more interactions than the other methods. Numéro de notice : A2016-754 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1174867 En ligne : http://dx.doi.org/10.1080/13658816.2016.1174867 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82415
in International journal of geographical information science IJGIS > vol 30 n° 11-12 (November - December 2016) . - pp 2302 - 2320[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016061 RAB Revue Centre de documentation En réserve L003 Disponible Efficient terrestrial laser scan segmentation exploiting data structure / Hamid Mahmoudabadi in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Efficient terrestrial laser scan segmentation exploiting data structure Type de document : Article/Communication Auteurs : Hamid Mahmoudabadi, Auteur ; Michael J. Olsen, Auteur ; Sinisa Todorovic, Auteur Année de publication : 2016 Article en page(s) : pp 135 - 150 Note générale : Bibliogaphie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] colorimétrie
[Termes IGN] densité d'information
[Termes IGN] intensité lumineuse
[Termes IGN] modèle logique de données
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] système de coordonnées
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) New technologies such as lidar enable the rapid collection of massive datasets to model a 3D scene as a point cloud. However, while hardware technology continues to advance, processing 3D point clouds into informative models remains complex and time consuming. A common approach to increase processing efficiently is to segment the point cloud into smaller sections. This paper proposes a novel approach for point cloud segmentation using computer vision algorithms to analyze panoramic representations of individual laser scans. These panoramas can be quickly created using an inherent neighborhood structure that is established during the scanning process, which scans at fixed angular increments in a cylindrical or spherical coordinate system. In the proposed approach, a selected image segmentation algorithm is applied on several input layers exploiting this angular structure including laser intensity, range, normal vectors, and color information. These segments are then mapped back to the 3D point cloud so that modeling can be completed more efficiently. This approach does not depend on pre-defined mathematical models and consequently setting parameters for them. Unlike common geometrical point cloud segmentation methods, the proposed method employs the colorimetric and intensity data as another source of information. The proposed algorithm is demonstrated on several datasets encompassing variety of scenes and objects. Results show a very high perceptual (visual) level of segmentation and thereby the feasibility of the proposed algorithm. The proposed method is also more efficient compared to Random Sample Consensus (RANSAC), which is a common approach for point cloud segmentation. Numéro de notice : A2016-781 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82477
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 135 - 150[article]The direction-constrained k nearest neighbor query dealing with spatio-directional objects / Min-Joong Lee in Geoinformatica, vol 20 n° 3 (July - September 2016)
[article]
Titre : The direction-constrained k nearest neighbor query dealing with spatio-directional objects Type de document : Article/Communication Auteurs : Min-Joong Lee, Auteur ; Dong-Wan Choi, Auteur ; SangYeon Kim, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 471 – 502 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse coût-avantage
[Termes IGN] classification barycentrique
[Termes IGN] données massives
[Termes IGN] index spatial
[Termes IGN] objet géographique
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] requête spatialeRésumé : (auteur) Finding k nearest neighbor objects in spatial databases is a fundamental problem in many geospatial systems and the direction is one of the key features of a spatial object. Moreover, the recent tremendous growth of sensor technologies in mobile devices produces an enormous amount of spatio-directional (i.e., spatially and directionally encoded) objects such as photos. Therefore, an efficient and proper utilization of the direction feature is a new challenge. Inspired by this issue and the traditional k nearest neighbor search problem, we devise a new type of query, called the direction-constrained k nearest neighbor (DCkNN) query. The DCkNN query finds k nearest neighbors from the location of the query such that the direction of each neighbor is in a certain range from the direction of the query. We develop a new index structure called MULTI, to efficiently answer the DCkNN query with two novel index access algorithms based on the cost analysis. Furthermore, our problem and solution can be generalized to deal with spatio-circulant dimensional (such as a direction and circulant periods of time such as an hour, a day, and a week) objects. Experimental results show that our proposed index structure and access algorithms outperform two adapted algorithms from existing kNN algorithms. Numéro de notice : A2016-378 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0245-2 En ligne : http://dx.doi.org/10.1007/s10707-016-0245-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81145
in Geoinformatica > vol 20 n° 3 (July - September 2016) . - pp 471 – 502[article]A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data / Gherardo Chirici in Remote sensing of environment, vol 176 (April 2016)
[article]
Titre : A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Matteo Mura, Auteur ; Daniel McInerney, Auteur ; Nicolas Py , Auteur ; Erkki Tomppo, Auteur ; Lars T. Waser, Auteur ; Davide Travaglini, Auteur ; Ronald E. McRoberts, Auteur Année de publication : 2016 Article en page(s) : pp 282 - 294 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] plus proche voisin, algorithme duRésumé : (auteur) The k-Nearest Neighbors (k-NN) technique is a popular method for producing spatially contiguous predictions of forest attributes by combining field and remotely sensed data. In the framework of Working Group 2 of COST Action FP1001, we reviewed the scientific literature for forestry applications of k-NN. Information available in scientific publications on this topic was used to populate a database that was then used as the basis for a meta-analysis. We extracted qualitative and quantitative information from 260 experimental tests described in 148 scientific papers. The papers represented a geographic range of 26 countries and a temporal range from 1981 to 2013. Firstly, we describe the literature search and the information extracted and analyzed. Secondly, we report the results of the meta-analysis, especially with respect to estimation accuracies reported for k-NN applications for different configurations, different forest environments, and different input information. We also provide a summary of results that may reasonably be expected for those planning a k-NN application using remotely sensed data from different sensors and for different forest attributes. Finally, we identify some methodological publications that have advanced the state of the science with respect to k-NN. Numéro de notice : A2016--196 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.02.001 Date de publication en ligne : 13/02/2016 En ligne : https://doi.org/10.1016/j.rse.2016.02.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91859
in Remote sensing of environment > vol 176 (April 2016) . - pp 282 - 294[article]PermalinkMulti-label class assignment in land-use modelling / Hichem Omrani in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)PermalinkCollaborative representation for hyperspectral anomaly detection / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkA rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images / Zahra Ziaei in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkRestoration of information obscured by mountainous shadows through Landsat TM/ETM+ images without the use of DEM data : A new method / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkBlind evaluation of location based queries using space transformation to preserve location privacy / Ali Khshgozaran in Geoinformatica, vol 17 n° 4 (October 2013)PermalinkPermalinkContinuous aggregate nearest neighbor queries / H. Elmongui in Geoinformatica, vol 17 n° 1 (January 2013)PermalinkA query integrity assurance scheme for accessing outsourced spatial databases / W. Ku in Geoinformatica, vol 17 n° 1 (January 2013)PermalinkPNN query processing on compressed trajectories / S. Shang in Geoinformatica, vol 16 n° 3 (July 2012)PermalinkGeneralized network Voronoi diagrams: concepts, computational methods, and applications / Atsuyuki Okabe in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)PermalinkSegmentation of airborne laser scanning data using a slope adaptative neighbourhood / S. Filin in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 2 (April 2006)PermalinkQuery processing in spatial databases containing obstacles / Jun Zhang in International journal of geographical information science IJGIS, vol 19 n° 10 (november 2005)PermalinkPermalinkBDA 2004, 20èmes journées Bases de Données Avancées / Jacques Le Maitre (2004)PermalinkKunnittaiset metsävaratiedot 1990–94 / Erkki Tomppo in Metsätieteen aikakauskirja, vol 1998 n° 4B ([01/12/1998])PermalinkComputational methods for generalization of cartographic data in a raster environment / Lars Schylberg (1993)Permalink