Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities

The increasing availability of remote sensing data allows the quantification of biodiversity in space and time. In particular, spectral diversity, defined as the variability of electromagnetic radiation reflected from plants, can be assessed with remote sensing. Plant traits vary diurnally and seaso...

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Autores principales:	Christian Rossi, Mathias Kneubühler, Martin Schütz, Michael E. Schaepman, Rudolf M. Haller, Anita C. Risch
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Sentinel-2 Plant traits Alpha diversity Beta diversity Rao’s quadratic entropy Spectral diversity Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/6aff34b3f28140cf86081d8b5059ccef
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spelling	oai:doaj.org-article:6aff34b3f28140cf86081d8b5059ccef2021-12-01T04:59:16ZRemote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities1470-160X10.1016/j.ecolind.2021.108106https://doaj.org/article/6aff34b3f28140cf86081d8b5059ccef2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21007718https://doaj.org/toc/1470-160XThe increasing availability of remote sensing data allows the quantification of biodiversity in space and time. In particular, spectral diversity, defined as the variability of electromagnetic radiation reflected from plants, can be assessed with remote sensing. Plant traits vary diurnally and seasonally due to plant phenology and land management. This results in strong temporal variation of spectral diversity, which cannot be accurately represented by remotely sensed data collected at a single point in time. However, knowledge of how datasets sampled at multiple points in time should best be used to quantify spectral diversity is scarce. To address this issue, we first introduced a new approach using spatio-temporal spectral diversity based on the dissimilarity measure Rao's quadratic entropy index (RaoQ). Thereby, we demonstrated how RaoQ can be used to partition the total spectral diversity of a region (γSD) into additive alpha (αSD, within communities) and spatio-temporal beta (βSD; between communities) components, allowing the calculation of βSD from community mean spectral features, independent from αSD. Second, we illustrated our methodological approach with a case study in which βSD is calculated from Sentinel-2 satellite data at high temporal resolution for managed grasslands which differ across a large gradient of environmental properties. We were able to show differences in βSD and separate its components into phenological and management effects. Furthermore, the contribution of different plant communities to βSD was assessed, and the results were validated against a dataset of in-situ measured β diversity from plant surveys. Compared to spatial dissimilarities from distinct stages of the growing season, using spatio-temporal dissimilarities between communities produced a more accurate estimation of the uniqueness of a community. This study shows how to account for temporal variations in the spectral diversity of plant communities and demonstrates that this improves the estimation of plant biodiversity through remote sensing. Spectral diversity in space and time makes it possible to assess mechanisms that drive biodiversity and identify plant communities relevant for conservation purposes.Christian RossiMathias KneubühlerMartin SchützMichael E. SchaepmanRudolf M. HallerAnita C. RischElsevierarticleSentinel-2Plant traitsAlpha diversityBeta diversityRao’s quadratic entropySpectral diversityEcologyQH540-549.5ENEcological Indicators, Vol 130, Iss , Pp 108106- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Sentinel-2 Plant traits Alpha diversity Beta diversity Rao’s quadratic entropy Spectral diversity Ecology QH540-549.5
spellingShingle	Sentinel-2 Plant traits Alpha diversity Beta diversity Rao’s quadratic entropy Spectral diversity Ecology QH540-549.5 Christian Rossi Mathias Kneubühler Martin Schütz Michael E. Schaepman Rudolf M. Haller Anita C. Risch Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities
description	The increasing availability of remote sensing data allows the quantification of biodiversity in space and time. In particular, spectral diversity, defined as the variability of electromagnetic radiation reflected from plants, can be assessed with remote sensing. Plant traits vary diurnally and seasonally due to plant phenology and land management. This results in strong temporal variation of spectral diversity, which cannot be accurately represented by remotely sensed data collected at a single point in time. However, knowledge of how datasets sampled at multiple points in time should best be used to quantify spectral diversity is scarce. To address this issue, we first introduced a new approach using spatio-temporal spectral diversity based on the dissimilarity measure Rao's quadratic entropy index (RaoQ). Thereby, we demonstrated how RaoQ can be used to partition the total spectral diversity of a region (γSD) into additive alpha (αSD, within communities) and spatio-temporal beta (βSD; between communities) components, allowing the calculation of βSD from community mean spectral features, independent from αSD. Second, we illustrated our methodological approach with a case study in which βSD is calculated from Sentinel-2 satellite data at high temporal resolution for managed grasslands which differ across a large gradient of environmental properties. We were able to show differences in βSD and separate its components into phenological and management effects. Furthermore, the contribution of different plant communities to βSD was assessed, and the results were validated against a dataset of in-situ measured β diversity from plant surveys. Compared to spatial dissimilarities from distinct stages of the growing season, using spatio-temporal dissimilarities between communities produced a more accurate estimation of the uniqueness of a community. This study shows how to account for temporal variations in the spectral diversity of plant communities and demonstrates that this improves the estimation of plant biodiversity through remote sensing. Spectral diversity in space and time makes it possible to assess mechanisms that drive biodiversity and identify plant communities relevant for conservation purposes.
format	article
author	Christian Rossi Mathias Kneubühler Martin Schütz Michael E. Schaepman Rudolf M. Haller Anita C. Risch
author_facet	Christian Rossi Mathias Kneubühler Martin Schütz Michael E. Schaepman Rudolf M. Haller Anita C. Risch
author_sort	Christian Rossi
title	Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities
title_short	Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities
title_full	Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities
title_fullStr	Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities
title_full_unstemmed	Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities
title_sort	remote sensing of spectral diversity: a new methodological approach to account for spatio-temporal dissimilarities between plant communities
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6aff34b3f28140cf86081d8b5059ccef
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Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plant communities

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