Partitioning plant spectral diversity into alpha and beta components

Laliberté, Étienne; Schweiger, Anna K.; Legendre, Pierre

doi:10.1101/742080

Cited by 15 publications

(15 citation statements)

References 48 publications

(23 reference statements)

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“…The proposed rasterdiv package is a powerful tool for monitoring spatial and temporal variation of ecosystems' properties (Rocchini et al, 2018), given the intrinsic relationship (sensu Laliberté et al, 2019) between the spatial variation of ecosystems and that of the spectral signal from pixel values . No single measure can provide a full description of all the different aspects of ecosystem heterogeneity.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2021

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Section: Resultsmentioning

confidence: 99%

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

et al. 2021

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“…Metrics grounded in information theory ensure to make use of relative abundance of pixel values given the same richness in the moving window of analysis. However, distance metrics also allow the relative dispersion in the spectral space of the cloud of pixels in a certain area to be accounted for (Laliberté et al, 2020). The proposed parameterization of the Rao’s

Q

explicitly considers the dispersion of pixel values in a spectral space (and their relative abundance) by allowing the whole dimensionality of diversity to be captured.…”

Section: Resultsmentioning

confidence: 99%

From zero to infinity: Minimum to maximum diversity of the planet by spatio‐parametric Rao’s quadratic entropy

Rocchini

Marcantonio

et al. 2021

Global Ecol. Biogeogr.

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Aim The majority of work done to gather information on the Earth's biodiversity has been carried out using in‐situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannon’s information theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Rao’s quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, that is they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Rao’s quadratic entropy by proposing its parameterization for the first time. Innovation The parametric Rao’s quadratic entropy, coded in R, (a) allows the representation of the whole continuum of potential diversity indices in one formula, and (b) starting from the Rao’s quadratic entropy, allows the explicit use of distances among pixel reflectance values, together with relative abundances. Main conclusions The proposed unifying measure is an integration between abundance‐ and distance‐based algorithms to map the continuum of diversity given a satellite image at any spatial scale. Being part of the rasterdiv R package, the proposed method is expected to ensure high robustness and reproducibility.

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“…The proposed package is a powerful tool for monitoring spatial and temporal variation of ecosystems’ properties (Rocchini et al, 2018), given the intrinsic relationship ( sensu Laliberté et al, 2019)between the spatial variation of ecosystems and that of the spectral signal from pixel values (Rocchini et al, 2019). No single measure can provide a full description of all the different aspects of ecosystem heterogeneity.…”

Section: Resultsmentioning

confidence: 99%

rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

Rocchini

Thouverai

Marcantonio³

et al. 2021

Preprint

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Ecosystem 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.

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Partitioning plant spectral diversity into alpha and beta components

Abstract: Type of article: Methods 15Number of words: 152 (abstract), 5062 (main text, excluding abstract, acknowledgements 16references, table and figure legends).

Cited by 15 publications

References 48 publications

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

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

From zero to infinity: Minimum to maximum diversity of the planet by spatio‐parametric Rao’s quadratic entropy

rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

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