Using vertices of a triangular irregular network to calculate slope and aspect

ABSTRACT

Terrain derivative calculations from triangulated irregular network (TIN)-based digital elevation models (DEMs) have been extensively explored in geomorphometry. However, most calculation methods focus on the triangulation facets of TIN-based DEMs and ignore the vertices. In fact, these vertices are the original sampling points from the terrain surface and serve as the basis for triangulation. In this study, we argue that terrain derivative calculations using TIN-based DEMs should focus on the vertices. Employing examples with slope and aspect, we applied the TIN vertex-based method to a mathematical surface and a real topography using TIN-based DEMs with a range of sampling point densities. We performed a comparative analysis of the TIN vertex-based, TIN facet-based, and grid-based methods. Assessments on the mathematical surface showed that the TIN vertex-based method achieved the highest accuracy among the three methods. Error analysis for the real landform case indicated that the TIN vertex-based method performed slightly better than the grid-based method for slope calculation and slightly worse than the grid-based method for aspect calculation. Among the three methods, the TIN facet-based method was most sensitive to error. The TIN vertex-based method can provide a reference for the slope and aspect calculation based on point clouds.

KEYWORDS:

• Triangulated irregular network
• terrain derivatives
• digital elevation model
• point clouds

Acknowledgments

We would take to thank editors and two anonymous reviewers for the useful comments on the manuscript.

Data and codes availability statement

The codes, the mathematical surface, and test DEM data that support the findings of this study are available in‘‘figshar’’ repository with the public link ‘https://doi.org/10.6084/m9.figshare.13351994.v1ʹ.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Science Foundation of China [41930102,41971333,41571398]; Priority Academic Program Development of Jiangsu Higher Education Institutions [164320H116].

Notes on contributors

Guanghui Hu

Guanghui Hu is now a PhD student in Nanjing Normal University and interested in digital terrain analysis.

Chun Wang

Chun Wang is a professor of Nanjing University of Information Science & Technology and interested in UAV Photogrammetry.

Sijin Li

Sijin Li is now a PhD student in Nanjing Normal University and interested in geomorphology & remote sensing.

Wen Dai

Wen Dai is now a PhD student in Nanjing Normal University and interested in surface dynamics and gully mapping .

Liyang Xiong

Liyang Xiong is an associate professor of Nanjing Normal University and interested in GIScience & geomorphology.

Guoan Tang

Guoan Tang is a professor of Nanjing Normal University and interested in GIScience & geomorphology.

Josef Strobl

Josef Strobl is a professor of University of Salzburg and interested in GIScience.