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  5. rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back

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Article
English
2021

rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back

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English
2021
Methods in Ecology and Evolution
Vol 12 (6)
DOI: 10.1111/2041-210x.13583

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Giles Foody
Giles Foody

University Of Nottingham

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Duccio Rocchini
Elisa Thouverai
Matteo Marcantonio
+32 more

Abstract

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.

How to cite this publication

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. Methods in Ecology and Evolution, 12(6), pp. 1093-1102, DOI: 10.1111/2041-210x.13583.

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Publication Details

Type

Article

Year

2021

Authors

35

Datasets

0

Total Files

0

Language

English

Journal

Methods in Ecology and Evolution

DOI

10.1111/2041-210x.13583

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