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Density-based clustering for data containing two types of points / Tao Pei in International journal of geographical information science IJGIS, vol 29 n° 2 (February 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 2 (February 2015) . - pp 175 - 193 Titre : Density-based clustering for data containing two types of points Type de document : Article/Communication Auteurs : Tao Pei, Auteur ; Weiyi Wang, Auteur ; Hengcai Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 175 - 193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse en composantes indépendantes [Termes IGN] classification par seuillage sur la limite la plus proche [Termes IGN] densité d'information [Termes IGN] échelle d'intensité [Termes IGN] groupe [Termes IGN] taxi [Termes IGN] transport routier Résumé : (Auteur) When only one type of point is distributed in a region, clustered points can be seen as an anomaly. When two different types of points coexist in a region, they overlap at different places with various densities. In such cases, the meaning of a cluster of one type of point may be altered if points of the other type show different densities within the same cluster. If we consider the origins and destinations (OD) of taxicab trips, the clustering of both in the morning may indicate a transportation hub, whereas clustered origins and sparse destinations (a hot spot where taxis are in short supply) could suggest a densely populated residential area. This cannot be identified by previous clustering methods, so it is worthwhile studying a clustering method for two types of points. The concept of two-component clustering is first defined in this paper as a group containing two types of points, at least one of which exhibits clustering. We then propose a density-based method for identifying two-component clusters. The method is divided into four steps. The first estimates the clustering scale of the point data. The second transforms the point data into the 2D density domain, where the x and y axes represent the local density of each type of point around each point, respectively. The third determines the thresholds for extracting the clusters, and the fourth generates two-component clusters using a density-connectivity mechanism. The method is applied to taxicab trip data in Beijing. Three types of two-component clusters are identified: high-density origins and destinations, high-density origins and low-density destinations, and low-density origins and high-density destinations. The clustering results are verified by the spatial relationship between the cluster locations and their land-use types over different periods of the day. Numéro de notice : A2015-577 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.955027 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.955027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77839 [article]

Hierarchical recovery of digital terrain models from single and multiple return lidar data / Y. Hu in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 4 (April 2005)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 4 (April 2005) . - pp 425 - 433 Titre : Hierarchical recovery of digital terrain models from single and multiple return lidar data Type de document : Article/Communication Auteurs : Y. Hu, Auteur ; V. Tao, Auteur Année de publication : 2005 Article en page(s) : pp 425 - 433 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] approche hiérarchique [Termes IGN] classification par seuillage sur la limite la plus proche [Termes IGN] convolution (signal) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] interpolation [Termes IGN] lasergrammétrie [Termes IGN] modèle numérique de terrain Résumé : (Auteur) A hierarchical terrain recovery approach for generating digital terrain models (DTM) from single and multiple returns lidar data is presented in this paper. The algorithm can intelligently discriminate between terrain and non-terrain points by using adaptive and robust filtering and interpolation techniques. It processes the image pyramid, bottom-up and top-down, to estimate high-quality terrain surfaces from lidar data with varying point densities and scene complexities. Using road and vegetation information, the algorithm is able to adaptively adjust thresholds to be suited to process changing contents in a large scene. The algorithms have been tested extensively using multiple medium - and high - resolution lidar datasets. The worst-case error is below 25 cm Linear Error (LE) 90 comparing the derived DTMs and the raw range images on bare surfaces when testing several lidar datasets. Copyright ASPRS Numéro de notice : A2005-589 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : https://doi.org/10.14358/PERS.71.4.425 En ligne : https://doi.org/10.14358/PERS.71.4.425 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27724 [article]

Tree cover discrimination in panchromatic aerial imagery of Pinyon-Juniper woodlands / J.J. Anderson in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 9 (September 2004) . - pp 1063 - 1068 Titre : Tree cover discrimination in panchromatic aerial imagery of Pinyon-Juniper woodlands Type de document : Article/Communication Auteurs : J.J. Anderson, Auteur ; N.S. Cobby, Auteur Année de publication : 2004 Article en page(s) : pp 1063 - 1068 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] classification non dirigée [Termes IGN] classification par seuillage sur la limite la plus proche [Termes IGN] couvert végétal [Termes IGN] détection de contours [Termes IGN] forêt [Termes IGN] image numérisée [Termes IGN] photographie aérienne [Termes IGN] photographie panchromatique [Termes IGN] Pinus (genre) Résumé : (Auteur) Responding to an increasing interest in studying vegetation changes over time, we review current methods of processing black and white digital aerial photographs in order to classify tree cover in pinyon-juniper woodlands. Besides applying commonly used clustering and supervised maxim likelihood methods, we have developed a new classifier, nearest edge thresholding, which is unsupervised and based on the principals of edge detection and density slicing. Comparison of the three methods' abilities to predict field values at plot scales of 100 m2 to 900 m2 shows this new method is better or comparable to others at all scales, can be easily applied to digital imagery, and has high correspondence with ground-truthed field values of tree cover. Numéro de notice : A2004-348 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.70.9.1063 En ligne : http://dx.doi.org/10.14358/PERS.70.9.1063 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26875 [article]