Measuring Rao's Q diversity index from remote sensing: An open source solution |
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Institution: | 1. Center for Environmental Management of Military Lands, Colorado State University, Fort Collins, CO 80523-1490, United States;2. Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany;3. Department of Disturbance Ecology, Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, D-95440 Bayreuth, Germany;4. Department of Biogeography, Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, D-95440 Bayreuth, Germany;1. School of Natural Resources, University of Nebraska, Lincoln, NE 68583, USA;2. Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada;3. Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada;4. Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA |
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Abstract: | Measuring biodiversity is a key issue in ecology to guarantee effective indicators of ecosystem health at different spatial and time scales. However, estimating biodiversity from field observations might present difficulties related to costs and time needed. Moreover, a continuous data update for biodiversity monitoring purposes might be prohibitive. From this point of view, remote sensing represents a powerful tool since it allows to cover wide areas in a relatively low amount of time. One of the most common indicators of biodiversity is Shannon's entropy H′, which is strictly related to environmental heterogeneity, and thus to species diversity. However, Shannon's entropy might show drawbacks once applied to remote sensing data, since it considers relative abundances but it does not explicitly account for distances among pixels’ numerical values. In this paper we propose the use of Rao's Q applied to remotely sensed data, providing a straightforward R-package function to calculate it in 2D systems. We will introduce the theoretical rationale behind Rao's index and then provide applied examples based on the proposed R function. |
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Keywords: | Biodiversity Heterogeneity Landscape metrics Remote sensing Spatial ecology Shannon's entropy |
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