Abstract
The causal relationship between species diversity and environmental (landscape) heterogeneity has been a long-lasting interest among ecologists. In fact, environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with higher environmental heterogeneity can host more species due to their higher number of available niches. In particular, entropy (also referred to as “heterogeneity”) measured by the spatial variation of remotely sensed spectral signals has been proposed as a proxy for species diversity. The aim of this book chapter is to review the main spatial algorithms for measuring landscape heterogeneity based on remote sensing.
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