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Impact of lidar nominal post-spacing on DEM accuracy and flood zone delineation / G.T. Raber in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 7 (July 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 7 (July 2007) . - pp 793 - 804 Titre : Impact of lidar nominal post-spacing on DEM accuracy and flood zone delineation Type de document : Article/Communication Auteurs : G.T. Raber, Auteur ; J.R. Jensen, Auteur Année de publication : 2007 Article en page(s) : pp 793 - 804 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] données lidar [Termes IGN] inondation [Termes IGN] lasergrammétrie [Termes IGN] modèle hydrographique [Termes IGN] modèle numérique de terrain [Termes IGN] plan de vol [Termes IGN] précision des données [Termes IGN] précision du positionnement [Termes IGN] prise de vue aérienne [Termes IGN] réseau hydrographique [Termes IGN] semis de points Résumé : (Auteur) Lidar data have become a major source of digital terrain information for use in many applications including hydraulic modeling and flood plane mapping. Based on established relationships between sampling intensity and error, nominal post-spacing likely contributes significantly to the error budget. Post-spacing is also a major cost factor during lidar data collection. This research presents methods for establishing a relationship between nominal post-spacing and its effects on hydraulic modeling for flood zone delineation. Lidar data collected at a low post-spacing (approximately 1 to 2 m) over a piedmont study area in North Carolina was systematically decimated to simulate datasets with sequentially higher post-spacing values. Using extensive first-order ground survey information, the accuracy of each DEM derived from these lidar datasets was assessed and reported. Hydraulic analyses were performed utilizing standard engineering practices and modeling software (HEC-RAS). All input variables were held constant in each model run except for the topographic information from the decimated lidar datasets. The results were compared to a hydraulic analysis performed on the un-decimated reference dataset. The sensitivity of the primary model outputs to the variation in nominal post-spacing is reported. The results indicate that base flood elevation does not statistically change over the post-spacing values tested. Conversely, flood zone boundary mapping was found to be sensitive to variations in post-spacing. Copyright ASPRS Numéro de notice : A2007-313 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.7.793 En ligne : http://dx.doi.org/10.14358/PERS.73.7.793 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28676 [article]

Building boundary tracing and regularization from airborne lidar point clouds / A. Sampath in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 7 (July 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 7 (July 2007) . - pp 805 - 812 Titre : Building boundary tracing and regularization from airborne lidar point clouds Type de document : Article/Communication Auteurs : A. Sampath, Auteur ; J. Shan, Auteur Année de publication : 2007 Article en page(s) : pp 805 - 812 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] correction géométrique [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] lasergrammétrie [Termes IGN] lissage de données [Termes IGN] Maryland (Etats-Unis) [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] Toronto Résumé : (Auteur) Building boundary is necessary for the real estate industry, flood management, and homeland security applications. The extraction of building boundary is also a crucial and difficult step towards generating city models. This study presents an approach to the tracing and regularization of building boundary from raw lidar point clouds. The process consists of a sequence of four steps: separate building and non-building lidar points; segment lidar points that belong to the same building; trace building boundary points; and regularize the boundary. For separation, a slope based 1D bi-directional filter is used. The segmentation step is a region-growing approach. By modifying a convex hull formation algorithm, the building boundary points are traced and connected to form an approximate boundary. In the final step, all boundary points are included in a hierarchical least squares solution with perpendicularity constraints to determine a regularized rectilinear boundary. Our tests conclude that the uncertainty of regularized building boundary tends to be linearly proportional to the lidar point spacing. It is shown that the regularization precision is at 18 percent to 21 percent of the lidar point spacing, and the maximum offset of the determined building boundary from the original lidar points is about the same as the lidar point spacing. Limitation of lidar data resolution and errors in previous filtering processes may cause artefacts in the final regularized building boundary. This paper presents the mathematical and algorithmic formulations along with stepwise illustrations. Results from Baltimore city, Toronto city, and Purdue University campus are evaluated. Copyright ASPRS Numéro de notice : A2007-314 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.7.805 En ligne : http://dx.doi.org/10.14358/PERS.73.7.805 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28677 [article]