Some Thoughts on a New Form of Spatial Entropy and its Applications in Landscape Ecology

Abstract

Distinguishing different landscape patterns has been recognised among the primary concerns of quantitative landscape ecology. However, idea methods to compare different landscape patterns are still lacking. The overall aim of this study is to develop a new form of spatial entropy (Hs) to distinguish different landscape patterns. Hsis an entropy-related index based on information theory, and integrates proximity as a key spatial component into the measurement of spatial diversity. Proximity contains two aspects, i.e. total edge length and distance, and by including both aspects gives richer information about spatial pattern than metrics that only consider one aspect. From this point of view, Hsprovides a novel way to study the spatial structures of landscape patterns where both edge and distance relationships are relevant. The performances of Hs and other similar approaches are evaluated through typical distributions of landscape mosaics. Our results indicate that Hsis more flexible and objective in distinguishing and characterizing different landscape patterns. At the same time, we hope this metric will facilitate the exploration of interactions between landscape patterns and ecological processes.