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Quality assessment of linear data / S. Seo in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 23 n°11-12 (november 2009) . - pp 1503 - 1525 Titre : Quality assessment of linear data Type de document : Article/Communication Auteurs : S. Seo, Auteur ; C. O'hara, Auteur Année de publication : 2009 Article en page(s) : pp 1503 - 1525 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] appariement géométrique [Termes IGN] données localisées [Termes IGN] objet géographique linéaire [Termes IGN] précision des données [Termes IGN] qualité des données [Termes IGN] zone tampon Résumé : (Auteur) This paper presents methods to evaluate the geometric quality of spatial data. Firstly, a point-based method is presented, adapting conventional assessment methods whereby common points between datasets are compared. In our approach, initial matches are established automatically and refined further through interactive editing. Second, a line-based method which uses correspondences between line segments is proposed. Here, the geometry of line segments in vector is transformed into a set of rasterized values so that their combination at each pixel can restore their original vector geometry. Matching is performed on rasterized line segments and their matching lengths and displacements are measured. Experimental results show that the line-based approach proposed is efficient to evaluate the geometric quality of spatial data without requirements of topological relationships among line features. Copyright Taylor & Francis Numéro de notice : A2009-518 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810802231456 En ligne : https://doi.org/10.1080/13658810802231456 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30147 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-09071	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-09072	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Parametric investigation of the performance of Lidar filters using different surface contexts / S. Seo in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 3 (March 2008)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 3 (March 2008) . - pp 343 - 362 Titre : Parametric investigation of the performance of Lidar filters using different surface contexts Type de document : Article/Communication Auteurs : S. Seo, Auteur ; C. O'hara, Auteur Année de publication : 2008 Article en page(s) : pp 343 - 362 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] données lidar [Termes IGN] filtrage du signal [Termes IGN] modèle numérique de terrain [Termes IGN] surface du sol Résumé : (Auteur) Lidar technology has provided an accurate and efficient way to obtain digital elevation models. While digital terrain models (DTMs) are essential products for three-dimensional spatial applications, extraction of ground points from a mixture of ground and non-ground points is not straightforward, and interactive classification of massive point data sets is prohibitive. To automate the filtering process, many algorithms have been proposed and demonstrated to produce satisfactory results when applied with suitably tuned parameters. For obtaining quality products using lidar filters, however, not only to figure out their optimal performance, but also to analyze the cause and effect relationships between filtering steps and their effects under variable conditions is important. Hence, this study examined the performance of three popular surface models for lidar data filtering: morphological operations, triangulation, and linear prediction. For the test, consistent setting of parameters was applied across considerably different landscape datasets. The strengths and weaknesses of the test filters were investigated by comparing the metrics of omission and commission errors and volumetric distortions, and by observing resulting DTMs and relevant surface profiles. Copyright ASPRS Numéro de notice : A2008-076 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.3.343 En ligne : https://doi.org/10.14358/PERS.74.3.343 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29071 [article]