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Surface network extraction from high resolution digital terrain models
- Source :
- Journal of Spatial Information Science, Vol 2021, Iss 22, Pp 33-59 (2021)
- Publication Year :
- 2021
- Publisher :
- Journal of Spatial Information Science, 2021.
-
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.
- Subjects :
- Computer science
Computation
surface network
Geography, Planning and Development
Terrain
data structure
thalweg
Computers in Earth Sciences
Digital elevation model
ComputingMethodologies_COMPUTERGRAPHICS
Geography (General)
geography
geography.geographical_feature_category
ridge
morse-smale complex
geomorphometry
computer.file_format
Grid
Data structure
digital terrain modeling
Geomorphometry
Ridge
digital elevation model
G1-922
Raster graphics
Algorithm
computer
Information Systems
Subjects
Details
- ISSN :
- 1948660X
- Database :
- OpenAIRE
- Journal :
- Journal of Spatial Information Science
- Accession number :
- edsair.doi.dedup.....63c7842c30317495cdae90df0adaabd8