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Automatic filtering and 2D modeling of airborne laser scanning building point cloud / Fayez Tarsha-Kurdi in Transactions in GIS, Vol 25 n° 1 (February 2021)  

Public [article]  inTransactions in GIS > Vol 25 n° 1 (February 2021) . - pp 164 - 188 Titre : Automatic filtering and 2D modeling of airborne laser scanning building point cloud Type de document : Article/Communication Auteurs : Fayez Tarsha-Kurdi, Auteur ; Mohammad Awrangjeb, Auteur ; Nosheen Munir, Auteur Année de publication : 2021 Article en page(s) : pp 164 - 188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme de filtrage [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] empreinte [Termes IGN] modélisation 2D [Termes IGN] semis de points [Termes IGN] toit Résumé : (Auteur) This article suggests a new approach to automatic building footprint modeling using exclusively airborne LiDAR data. The first part of the suggested approach is the filtering of the building point cloud using the bias of the Z‐coordinate histogram. This operation aims to detect the points of roof class from the building point cloud. Hence, eight rules for histogram interpretation are suggested. The second part of the suggested approach is the roof modeling algorithm. It starts by detecting the roof planes and calculating their adjacency matrix. Hence, the roof plane boundaries are classified into four categories: (1) outer boundary; (2) inner plane boundaries; (3) roof detail boundaries; and (4) boundaries related to the missing planes. Finally, the junction relationships of roof plane boundaries are analyzed for detecting the roof vertices. With regard to the resulting accuracy quantification, the average values of the correctness and the completeness indices are employed in both approaches. In the filtering algorithm, their values are respectively equal to 97.5 and 98.6%, whereas they are equal to 94.0 and 94.0% in the modeling approach. These results reflect the high efficacy of the suggested approach. Numéro de notice : A2021-187 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12685 Date de publication en ligne : 11/09/2020 En ligne : https://doi.org/10.1111/tgis.12685 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97154 [article]

Contribution of two plane detection to recognition of intact and damaged buildings in Lidar data / M. Rehor in Photogrammetric record, vol 23 n° 124 (December 2008 - February 2009)  

Public [article]  inPhotogrammetric record > vol 23 n° 124 (December 2008 - February 2009) . - pp 441 - 456 Titre : Contribution of two plane detection to recognition of intact and damaged buildings in Lidar data Type de document : Article/Communication Auteurs : M. Rehor, Auteur ; Hans Peter Bähr, Auteur ; Fayez Tarsha-Kurdi, Auteur ; Tania Landes, Auteur ; Pierre Grussenmeyer, Auteur Année de publication : 2008 Conférence : ISPRS 2007, High-Resolution Earth Imaging for Geospatial Information workshop 29/05/2007 01/06/2007 Hanovre Allemagne Article en page(s) : pp 441 - 456 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] bati [Termes IGN] détection automatique [Termes IGN] données lidar [Termes IGN] risque majeur [Termes IGN] segmentation d'image Résumé : (Auteur) In the field of disaster management the detection and classification of building damage play an important role. Airborne lidar data is very suitable as a basis for damage analyses because it can be acquired for large areas directly after a disaster. In building damage classification methods, plane surfaces extracted from post-event lidar data are often used as one input. Various different algorithms exist for automatic plane detection from lidar data, of which two are presented in this paper and applied to lidar data of undamaged and damaged buildings. Finally, the suitability of these two algorithms for a more detailed building damage classification is studied and analysed. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2008-422 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2008.00501.x En ligne : https://doi.org/10.1111/j.1477-9730.2008.00501.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29493 [article]