Robust badlands thalwegs network extraction from DTM for topological characterisation
2009
Thommeret, N. | Bailly, Jean-Stéphane | Puech, C. | Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP) ; Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS) | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF)
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE
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Afficher plus [+] Moins [-]anglais. This paper presents methods to extract badlands thalwegs network from regular grid DTM by combining a terrain morphology indices to a drainage algorithm. The computation of a continuous vector network will permit the study of the badlands spatial patterns. Thess methods aim at delineating a thalweg only where the DTM denotes a significant curvature with respect to DTM accuracy. It relies on three major steps. Firstly, discontinuous concave areas are detected from the DTM using morphological criteria; the plan curvature and the convergence index . Secondly, the concave convergence areas are connected using a drainage algorithm which provides continuous and tree-structured thick scheme. We assume that these areas present physical significance and corresponds to a gully floor area. Finally, the thick path is reduced to its main curve and vectorised to obtain a thalwegs network. The methods are applied on both virtual and actual cases DTM. The actual case is a LiDAR DTM of Draix Badlands (French Alps). The obtained networks are quantitatively compared both to the one obtained with usual drainage area criteria and to a reference network. The networks comparison shows the great potential of the converge index based method for thalweg network extraction.
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