Morphological convexity measures for terrestrial basins derived from digital elevation models - Lim, Sin Liang; Daya Sagar, B.S.; Chet Koo, Voon; Tien Tay, Lea (Elsevier Ltd, 2011)
Geophysical basins of terrestrial surfaces have been quantitatively characterized through a host of indices such as topological quantities (e.g. channel bifurcation and length ratios), allometric scaling exponents (e.g. fractal dimensions), and other geomorphometric parameters (channel density, Hack's and Hurst exponents). Channel density, estimated by taking the ratio between the length of channel network (L) and the area of basin (A) in planar form, provides a quantitative index that has hitherto been related to various geomorphologically significant processes. This index, computed by taking the planar forms of channel network and its corresponding basin, is a kind of convexity measure in the two-dimensional case. Such a measure - estimated in general as a function of basin area and channel network length, where the important elevation values of the topological region within a basin and channel network are ignored - fails to capture the spatial variability between homotopic basins possessing different altitude-ranges. Two types of convexity measures that have potential to capture the terrain elevation variability are defined as the ratio of (i) length of channel network function and area of basin function and ( ii) areas of basin and its convex hull functions. These two convexity measures are estimated in three data sets that include (a) synthetic basin functions, (b) fractal basin functions, and (c) realistic digital elevation models (DEMs) of two regions of peninsular Malaysia. It is proven that the proposed convexity measures are altitude-dependent and that they could capture the spatial variability across the homotopic basins of different altitudes. It is also demonstrated on terrestrial DEMs that these convexity measures possess relationships with other quantitative indexes such as fractal dimensions and complexity measures (roughness indexes). (C) 2010 Elsevier Ltd. All rights reserved.