An alternative approach to transverse and profile terrain curvature

Abstract

Terrain curvature is one of the most important parameters of land surface topography. Well-established methods used in its measurement compute an index of plan or profile curvature for every single cell of a digital elevation model (DEM). The interpretation of these outputs may be delicate, especially when selected locations have to be analyzed. Furthermore, they involve a high level of simplification, contrasting with the complex and multiscalar nature of the surface curvature itself. In this paper, we present a new method to assess vertical transverse and profile curvature combining real-scale visualization and the possibility to measure these two terrain derivatives over a large range of scales. To this purpose, we implemented a GIS tool that extracts longitudinal and transverse elevation profiles from a high-resolution DEM. The performance of our approach was compared with some of the most commonly used methods (ArcMap, Redlands, CA, USA; ArcSIE, Landserf) by analyzing the terrain curvature around charcoal production sites in southern Switzerland. The different methods produced comparable results. While conventional methods quickly summarize terrain curvature in the form of a matrix of values, they involve a loss of information. The advantage of the new method lies in the possibility to measure and visualize the shape and size of the curvature, and to obtain a realistic representation of the average curvature for different subsets of spatial points. Moreover, the new method makes it possible to control the conditions in which the index of curvature is calculated.

Keywords:

• landforms
• concavity/convexity
• DEM
• elevation profiles
• geomorphometry
• morphometric variables

Acknowledgements

Our heartfelt thanks go to Matteo Minetti, Philippe Wäger, Joël Godat, Matthias von Rohr, Luca Pampuri, and Ferdinand Hermann for the field work, to Curtis Gautschi for the English revision of the manuscript, and to the reviewers for the remarks that helped us to improve the text.