Abstract
A surface network is a topological data structure formed by a set of thalwegs and ridges on a digital terrain model. Its computation relies on the detection of saddles on the terrain. Hence, computation methods must guarantee enough saddles are detected but also that no improper conflicts between ridges and thalwegs are created, leading to an inconsistent network. This paper presents a new approach that maximizes the number of saddles and ensures this topological consistency for high-resolution terrain models represented by a raster grid. The grid is triangulated in order to preserve saddles and to facilitate thalweg and ridge computation. It does not require any user parameter and lines remain aligned with triangulation edges, avoiding numerical errors. The method also includes a coherent partitioning of the terrain into hills and dales. A case study shows that the surface network computation can be achieved in reasonable time and hence can be applied to the analysis of large terrain models.
Highlights
In environment science, geomorphometry is an essential tool for terrain modeling and analysis
Www.josis.org ridges and thalwegs do not necessarily correspond to lines connecting to saddles and peaks or pits and are instead regions characterized by their relief
The paper introduced a new approach for computing a surface network over a raster digital terrain models (DTM)
Summary
Geomorphometry is an essential tool for terrain modeling and analysis. One main objective of geomorphometry is to provide a classification of the land surface into significant elements. A seminal work in this direction is [17]. The authors describe a method to detect pits, peaks, passes, ridges, and thalwegs (or ravines) on a terrain model. For that purpose, they rely on the Morse theory which provides a mathematical definition of each element. New methods were developed in two directions.
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