High-resolution grid digital elevation models (DEMs) are increasingly used by scientists and engineers to describe the current state and evolution of Earth and planetary topography. These data, however, are commonly altered by depression filling and grid coarsening procedures. Alteration of observed topographic data may cause significant information loss and limit the capabilities of models. This study shows that physically meaningful thalweg and ridge networks can be extracted automatically from any unaltered high-resolution grid DEM, and that these networks can be used as bases for terrain partitioning. The slopeline network connecting grid cell centers is used to identify ridge points as those grid cell border midpoints and vertices that are not crossed by slopelines. From each ridge point, the average length of the two slopelines extending on the opposite slopes of the ridge until they rejoin is then computed. Based on these lengths, exorheic and endorheic basins are identified. Thalwegs of exorheic and endorheic basins are finally connected through spilling saddles to form the thalweg network. The related ridge network is identified based on neighboring relationships between ridge points. Thalweg and ridge networks are hierarchized using the well-known concept of drainage area and an extended concept of dispersal area to inform terrain partitioning at any level of detail. Observed topographic features are well reproduced by extracted networks. The impact of preserving depressions over mountain areas is evaluated, and the benefits from unstructured terrain partitioning based on thalweg and ridge networks in the description of flood plain inundation are illustrated.

Thalweg and Ridge Network Extraction From Unaltered Topographic Data as a Basis for Terrain Partitioning / Moretti, Giovanni; Orlandini, Stefano. - In: JOURNAL OF GEOPHYSICAL RESEARCH. EARTH SURFACE. - ISSN 2169-9003. - 128:4(2023), pp. 1-25. [10.1029/2022JF006943]

Thalweg and Ridge Network Extraction From Unaltered Topographic Data as a Basis for Terrain Partitioning

Giovanni Moretti;Stefano Orlandini
2023

Abstract

High-resolution grid digital elevation models (DEMs) are increasingly used by scientists and engineers to describe the current state and evolution of Earth and planetary topography. These data, however, are commonly altered by depression filling and grid coarsening procedures. Alteration of observed topographic data may cause significant information loss and limit the capabilities of models. This study shows that physically meaningful thalweg and ridge networks can be extracted automatically from any unaltered high-resolution grid DEM, and that these networks can be used as bases for terrain partitioning. The slopeline network connecting grid cell centers is used to identify ridge points as those grid cell border midpoints and vertices that are not crossed by slopelines. From each ridge point, the average length of the two slopelines extending on the opposite slopes of the ridge until they rejoin is then computed. Based on these lengths, exorheic and endorheic basins are identified. Thalwegs of exorheic and endorheic basins are finally connected through spilling saddles to form the thalweg network. The related ridge network is identified based on neighboring relationships between ridge points. Thalweg and ridge networks are hierarchized using the well-known concept of drainage area and an extended concept of dispersal area to inform terrain partitioning at any level of detail. Observed topographic features are well reproduced by extracted networks. The impact of preserving depressions over mountain areas is evaluated, and the benefits from unstructured terrain partitioning based on thalweg and ridge networks in the description of flood plain inundation are illustrated.
2023
6-apr-2023
128
4
1
25
Thalweg and Ridge Network Extraction From Unaltered Topographic Data as a Basis for Terrain Partitioning / Moretti, Giovanni; Orlandini, Stefano. - In: JOURNAL OF GEOPHYSICAL RESEARCH. EARTH SURFACE. - ISSN 2169-9003. - 128:4(2023), pp. 1-25. [10.1029/2022JF006943]
Moretti, Giovanni; Orlandini, Stefano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1303586
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