MEASURING SPATIAL DIVERSITY IN A FREE ALGORITHMIC ENVIRONMENT
Estimating complexity is complex. This is particularly true when the complexity of the environment at different spatial scales (from global to regional) is taken into account, due to the difficulty of finding adequate proxies of landscape diversity. One of the most powerful tools to be used is spectral diversity, i.e. the diversity of reflectance values recorded by remotely sensed imagery. Indices based on compositional and structural diversity are routinely used, but scientists are mainly relying on black box-based (blind) calculations. Bruce Hapke, rearranging the well known Murphy’s law in his “Theory of Reflectance and Emittance Spectroscopy” (Cambridge University Press), stresses that:
“The equation you need the most contains a typographical error […]”
This can be hardly solved when the code used for building equations is not explicitly available.
In this study we provide a new GRASS GIS script (r.diversity) which incorporates the mostly used measures of diversity (including the Shannon index, the Simpson index, the Pielou index, etc.) together with their derivatives and new measures proposed in recent scientific papers.
We hope that scientists relying on such measures will adopt this open source script in GRASS GIS for future development of challenging but straightforward measures of diversity derived from remotely sensed imagery.
Duccio Rocchini - Fondazione Edmund Mach
Luca Delucchi - Fondazione Edmund Mach
Carlo Ricotta - Universita “La Sapienza” di Roma
Cristina Castellani - Fondazione Edmund Mach
Roberto Zorer - Fondazione Edmund Mach
Markus Neteler - Fondazione Edmund Mach