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


Abstract

1. 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.
2. 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.
3. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

Abstract

1. 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.
2. 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.
3. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

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32 citations in Web of Science®
29 citations in Scopus®
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47 downloads since deposited on 06 Aug 2021
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
07 Faculty of Science > Institute of Mathematics
07 Faculty of Science > Institute for Computational Science
08 Research Priority Programs > Global Change and Biodiversity
Dewey Decimal Classification:340 Law
610 Medicine & health
510 Mathematics
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Physical Sciences > Ecological Modeling
Uncontrolled Keywords:Ecological Modelling, Ecology, Evolution, Behavior and Systematics
Language:English
Date:1 June 2021
Deposited On:06 Aug 2021 09:58
Last Modified:26 May 2024 01:42
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:2041-210X
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1111/2041-210x.13583
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)