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Get Free AccessEcosystem heterogeneity has been widely recognized as a key ecological feature, influencing several ecological functions, since it is strictly related to several ecological functions like 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.
Duccio Rocchini, Elisa Thouverai, Matteo Marcantonio, Martina Iannacito, Daniele Da Re, Michele Torresani, Giovanni Bacaro, Manuele Bazzichetto, Alessandra Bernardi, Giles Foody, Reinhard Furrer, David Kleijn, Stefano Larsen, Jonathan Lenoir, Marco Malavasi, Elisa Marchetto, Filippo Messori, Alessandro Montaghi, Vítězslav Moudrý, Babak Naimi, Carlo Ricotta, Micol Rossini, Francesco Santi, Maria J. Santos, Michael E. Schaepman, Fabian Schneider, Leila Schuh, Sonia Silvestri, Petra Šímová, Andrew K. Skidmore, Clara Tattoni, Enrico Tordoni, Saverio Vicario, Piero Zannini, Martin Wegmann (2021). rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back. bioRxiv (Cold Spring Harbor Laboratory), DOI: 10.1101/2021.02.09.430391.
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Type
Preprint
Year
2021
Authors
35
Datasets
0
Total Files
0
Language
English
Journal
bioRxiv (Cold Spring Harbor Laboratory)
DOI
10.1101/2021.02.09.430391
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