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Auteur Fangzheng Lyu |
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A vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)
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Titre : A vector-based method for drainage network analysis based on LiDAR data Type de document : Article/Communication Auteurs : Fangzheng Lyu, Auteur ; Xinlin Ma, Auteur ; et al., Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse vectorielle
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] interpolation spatiale
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau hydrographique
[Termes IGN] semis de pointsRésumé : (auteur) Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. Numéro de notice : A2021-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104892 Date de publication en ligne : 24/07/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98733
in Computers & geosciences > vol 156 (November 2021)[article]