rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space : To the origin and back
2021
Rocchini, Duccio | Thouverai, Elisa | Marcantonio, Matteo | Iannacito, Martina | Da Re, Daniele | Torresani, Michele | Bacaro, Giovanni | Bazzichetto, Manuele | Bernardi, Alessandra | Foody, Giles M. | Furrer, Reinhard | Kleijn, David | Larsen, Stefano | Lenoir, Jonathan | Malavasi, Marco | Marchetto, Elisa | Messori, Filippo | Montaghi, Alessandro | Moudrý, Vítězslav | Naimi, Babak | Ricotta, Carlo | Rossini, Micol | Santi, Francesco | Santos, Maria J. | Schaepman, Michael E. | Schneider, Fabian D. | Schuh, Leila | Silvestri, Sonia | Ŝímová, Petra | Skidmore, Andrew K. | Tattoni, Clara | Tordoni, Enrico | Vicario, Saverio | Zannini, Piero | Wegmann, Martin
Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.
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