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Auteur Lianbin Deng |
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Progressive TIN densification with connection analysis for urban Lidar data / Tao Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 3 (March 2021)
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Titre : Progressive TIN densification with connection analysis for urban Lidar data Type de document : Article/Communication Auteurs : Tao Wang, Auteur ; Lianbin Deng, Auteur ; Yuhong Li, Auteur ; Hao Peng, Auteur Année de publication : 2021 Article en page(s) : pp 205 - 213 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] pente
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular NetworkRésumé : (Auteur) Urban lidar data are advantageous for capturing the terrain surface of built-up areas, which can be directly used to provide digital surface models. Cloud points are classified into ground points to obtain digital terrain models. This study proposes a method to improve the progressive triangulated irregular network (TIN ) densification method using a TIN connection analysis algorithm, namely, connection analysis via slope analysis. The proposed method comprises five steps: selection of seed points, connection and slope analysis, increasing the seed points, construction of the TIN model of the seed points, and an iterative construction of the final TIN. Seven data sets from the International Society for Photogrammetry and Remote Sensing Working Group are used to test whether the proposed method can preserve discontinuities of landscapes and reduce omission and total errors by an average of 9% and 5%, respectively; achieving such results can reduce the amount of workload required for result modification during posttreatment, thus decreasing costs. Numéro de notice : A2021-243 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.3.207 Date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.14358/PERS.87.3.207 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97291
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 3 (March 2021) . - pp 205 - 213[article]Exemplaires(1)
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