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Tagliabue, Giulia [Author]; Panigada, Cinzia [Author]; Celesti, Marco [Author]; Cogliati, Sergio [Author]; Colombo, Roberto [Author]; Migliavacca, Mirco [Author]; Rascher, Uwe [Author]; Rocchini, Duccio [Author]; Schüttemeyer, Dirk [Author]; Rossini, Micol [Author]

Sun–induced fluorescence heterogeneity as a measure of functional diversity

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  • Media type: E-Article
  • Title: Sun–induced fluorescence heterogeneity as a measure of functional diversity
  • Contributor: Tagliabue, Giulia [Author]; Panigada, Cinzia [Author]; Celesti, Marco [Author]; Cogliati, Sergio [Author]; Colombo, Roberto [Author]; Migliavacca, Mirco [Author]; Rascher, Uwe [Author]; Rocchini, Duccio [Author]; Schüttemeyer, Dirk [Author]; Rossini, Micol [Author]
  • imprint: Elsevier Science, 2020
  • Published in: Remote sensing of environment 247, 111934 - (2020). doi:10.1016/j.rse.2020.111934
  • Language: English
  • DOI: https://doi.org/10.1016/j.rse.2020.111934
  • ISSN: 1879-0704; 0034-4257
  • Origination:
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  • Description: Plant functional diversity, defined as the range of plant chemical, physiological and structural properties within plants, is a key component of biodiversity which controls the ecosystem functioning and stability. Monitoring its variations across space and over time is critical in ecological studies. So far, several reflectance-based metrics have been tested to achieve this objective, yielding different degrees of success. Our work aimed at exploring the potential of a novel metric based on far-red sun-induced chlorophyll fluorescence (F760) to map the functional diversity of terrestrial ecosystems. This was achieved exploiting high-resolution images collected over a mixed forest ecosystem with the HyPlant sensor, deployed as an airborne demonstrator of the forthcoming ESA-FLEX satellite. A reference functional diversity map was obtained applying the Rao's Q entropy metric on principal components calculated on key plant functional trait maps retrieved from the hyperspectral reflectance cube. Based on the spectral variation hypothesis, which states that the biodiversity signal is encoded in the spectral heterogeneity, two moving window-based approaches were tested to estimate the functional diversity from continuous spectral data: i) the Rao's Q entropy metric calculated on the normalized difference vegetation index (NDVI) and ii) the coefficient of variation (CV) calculated on hyperspectral reflectance. Finally, a third moving window approach was used to estimate the functional diversity based on F760 heterogeneity quantified through the calculation of the Rao's Q entropy metric.Results showed a strong underestimation of the functional diversity using the Rao's Q index based on NDVI and the CV of reflectance. In both cases, a weak correlation was found against the reference functional diversity map (r2 = 0.05, p < .001 and r2 = 0.04, p < .001, respectively). Conversely, the Rao's Q index calculated on F760 revealed similar patterns as the ones observed in the reference map and a better correlation (r2 = ...
  • Access State: Open Access