The Algorithmic Complexity of Landscapes

A method to evaluate the algorithmic complexity of landscapes is developed here, based on the notion of Kolmogorov complexity (or K-complexity). The K-complexity of a landscape is calculated from a string x of symbols representing the landscape's features (e.g. land use), whereby each symbol belongs to an alphabet L, and can be defined as the size of the shortest string y that fully describes x. K-complexity presents several useful aspects as a measure of landscape complexity: a) it is a direct measure of complexity and not a surrogate measure, well supported by the literature of Informatics; b) it is easy to apply to landscapes of ‘small' size’ c) it can be used to compare the complexity of two or more landscapes; d) it allows calculations of a landscape's changes in complexity with time; e) it can be a descriptor not only of the landscape's structural complexity, but also of its functional complexity; and f) it makes possible to distinguish two landscapes with the same diversity but with different complexity.