Multiscale Heterogeneity Map and Associated Scaling Profile for Landscape Analysis

Spatial heterogeneity, in the wide sense of pattern complexity and variability, appears to be one of the dominant causes of ecological functions and processes. The most widely used quantification of heterogeneity in environmental studies is based on 10 derived Shannon information theory indices. Yet, such heterogeneity index is not able to quantify the surface patterns of a landscape with a fully explicit scheme (understand, at each place and scale of the landscape). I propose to draw multiscale, averaged, heterogeneity maps to bypass this disadvantage and to capture the scaling behavior of the landscape. This multiscale map is associated to a heterogeneity profile averaging at 15 each scale the spatial information over the whole landscape. Confidence levels have been estimated on the basis of a simple neutral landscape model to detect significant heterogeneity fluctuations. This methodology is illustrated on both categorical (patchy) and numerical (point-data) real landscapes: a heterogeneous agricultural landscape in Brittany and a spring phytoplankton bloom in north Atlantic. Heterogeneity analyses of 20 both image types can simultaneously reveal subtle quantitative and qualitative features (gradients, boundaries, random or patchy patterns at successive scales) that would need otherwise combinations of many specific methods.