Digital images of landscape features may be captured in a sequence of successively coarsened resolutions. Hierarchy theory (see O’Neill et al. in M. G. Turner and R. H. Gardner 1991) suggests that patterns observed at any given resolution will, to some extent, weaken the patterns observed at finer resolutions and will themselves be constrained by coarser resolution patterns. Establishing the range of scales over which landscapes show hierarchically nested spatial patterns makes it possible to identify the scales at which fine-scale processes affect global scale patterns and vice versa. The selection of appropriate scales of measurement is fundamental to this process, and is generally guided by principles of hierarchy theory, since hierarchy incorporates relational links between nested levels. Bailey (1987) Landscape and Urban Planning 14 suggests a hierarchy of criteria for multi-scale ecosystem mapping and Tay et al. (2005) Geosci. & Rem. Sens. Letts, IEEE 2, 4 provide a simple framework to generate multi-scale digital elevation models and extract topologically significant multi-scale geophysical networks.