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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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 11-12 (November - December 2016) . - pp 2302 - 2320 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 descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] fonction K de Ripley [Termes descripteurs IGN] interaction spatiale [Termes descripteurs IGN] plus proche voisin (algorithme) [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] sécurité civile [Termes descripteurs IGN] sécurité informatique Résumé : (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 [article]

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Efficient terrestrial laser scan segmentation exploiting data structure / Hamid Mahmoudabadi in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 135 - 150 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 descripteurs IGN] colorimétrie [Termes descripteurs IGN] densité d'information [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] modèle logique de données [Termes descripteurs IGN] plus proche voisin (algorithme) [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] système de coordonnées [Termes descripteurs IGN] télémétrie laser terrestre Résumé : (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 En ligne : http://dx.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 [article]

A method for finding a least-cost wide path in raster space / Takeshi Shirabe in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1469 - 1485 Titre : A method for finding a least-cost wide path in raster space Type de document : Article/Communication Auteurs : Takeshi Shirabe, Auteur Année de publication : 2016 Article en page(s) : pp 1469 - 1485 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes descripteurs IGN] chemin le moins coûteux (algorithme) [Termes descripteurs IGN] données maillées [Termes descripteurs IGN] traitement automatique de données Résumé : (Auteur) Given a grid of cells each having an associated cost value, a raster version of the least-cost path problem seeks a sequence of cells connecting two specified cells such that its total accumulated cost is minimized. Identifying least-cost paths is one of the most basic functions of raster-based geographic information systems. Existing algorithms are useful if the path width is assumed to be zero or negligible compared to the cell size. This assumption, however, may not be valid in many real-world applications ranging from wildlife corridor planning to highway alignment. This paper presents a method to solve a raster-based least-cost path problem whose solution is a path having a specified width in terms of Euclidean distance (rather than by number of cells). Assuming that all cell values are positive, it does so by transforming the given grid into a graph such that each node represents a neighborhood of a certain form determined by the specified path width, and each arc represents a possible transition from one neighborhood to another. An existing shortest path algorithm is then applied to the graph. This method is highly efficient, as the number of nodes in the transformed graph is not more than the number of cells in the given grid and decreases with the specified path width. However, a shortcoming of this method is the possibility of generating a self-intersecting path which occurs only when the given grid has an extremely skewed distribution of cost values. Numéro de notice : A2016-311 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1124435 En ligne : http://dx.doi.org/10.1080/13658816.2015.1124435 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80911 [article]

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The direction-constrained k nearest neighbor query dealing with spatio-directional objects / Min-Joong Lee in Geoinformatica [en ligne], vol 20 n° 3 (July - September 2016)  

Public [article]  inGeoinformatica [en ligne] > vol 20 n° 3 (July - September 2016) . - pp 471 – 502 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 descripteurs IGN] analyse coût-avantage [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] contrainte de direction [Termes descripteurs IGN] données massives [Termes descripteurs IGN] index spatial [Termes descripteurs IGN] objet géographique [Termes descripteurs IGN] plus proche voisin (algorithme) [Termes descripteurs IGN] requête spatiale Résumé : (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 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 [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)  

Public [article]  inRemote sensing of environment > vol 176 (April 2016) . - pp 282 - 294 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 descripteurs IGN] classification barycentrique [Termes descripteurs IGN] forêt [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] plus proche voisin (algorithme) Résumé : (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 [article]

Seamline determination for high resolution orthoimage mosaicking using watershed segmentation / Wang Mi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 2 (February 2016)

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Automatisation du nettoyage de nuages de points / Yohan Pensier (2016) 

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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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A hybrid link-node approach for finding shortest paths in road networks with turn restrictions / Qingquan Li in Transactions in GIS, vol 19 n° 6 (December 2015)  

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Multi-label class assignment in land-use modelling / Hichem Omrani in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)  

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A dilution-matching-encoding compaction of trajectories over road networks / Ranit Gotsman in Geoinformatica [en ligne], vol 19 n° 2 (April - June 2015)  

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Collaborative representation for hyperspectral anomaly detection / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

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Algorithmique : raisonner pour concevoir / Christophe Haro (2015)

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Algorithms for vision-based path following along previously taught paths / Deon George Sabatta (2015)  

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Python, les bases de l'algorithmique et de la programmation / Vincent Maille (2015) 

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