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Mapping functional diversity of canopy physiological traits using UAS imaging spectroscopy

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    SYSNO ASEP0584944
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleMapping functional diversity of canopy physiological traits using UAS imaging spectroscopy
    Author(s) Cimoli, E. (IT)
    Lucieer, A. (AU)
    Malenovský, Z. (AU)
    Woodgate, W. (AU)
    Janoutová, Růžena (UEK-B) RID, ORCID, SAI
    Turner, D. (AU)
    Haynes, R.S. (AU)
    Phinn, S. (AU)
    Article number113958
    Source TitleRemote Sensing of Environment. - : Elsevier - ISSN 0034-4257
    Roč. 302, MAR (2024)
    Number of pages25 s.
    Languageeng - English
    CountryNL - Netherlands
    Keywordsphotochemical reflectance index ; band vegetation indexes ; chlorophyll content ; spectral diversity ; carotenoid content ; species richness ; soil properties ; forest ; leaf ; biodiversity ; Remote sensing ; Hyperspectral ; uav ; Drone ; Airborne ; Satellite ; Spectral vegetation indices ; Trait probability density ; Biodiversity
    Subject RIVGK - Forestry
    OECD categoryRemote sensing
    Method of publishingOpen access
    Institutional supportUEK-B - RVO:86652079
    UT WOS001155814600001
    EID SCOPUS85181763719
    DOI10.1016/j.rse.2023.113958
    AnnotationPlant functional diversity (FD) is a component of biodiversity linking plant functional traits to ecosystem processes (e.g., photosynthesis) and services (e.g., gross primary production). Development of remote sensing capabilities to monitor forest FD across various spatio-temporal scales is critical, especially in view of increasing global climate and anthropogenic pressures. Here, we focus on investigating the capability of unoccupied aerial systems (UAS), acquiring imaging spectroscopy data of high spatial (pixel size <= 0.1 m) and spectral (band-width < 5 nm between 400 and 1000 nm) resolutions, to map two trait-based FD metrics, namely, richness and divergence, of two open sclerophyll forests at the plot-scale (<0.2 km(2)). An emerging scalable kernel-based trait probability density (TPD) approach was implemented to compute spatially explicit metrics of FD at different areal extents and pixel sizes through spatially resampled products. Narrow-band spectral indices were utilized as proxies of selected plant functional traits, including photoprotective zeaxanthin-to-antheraxanthin transformation ratio (VAZ), and foliar pigments of chlorophylls and anthocyanins (C-ab and C-ant). The combination of high-resolution imagery and TPDs presents a suitable alternative to the traditional need for taxonomic information and alleviates pixel-based spectral mixing issues known to affect pixel-based FD metrics. A moving kernel (6 x 6 m) applied to UAS data, allowed to capture fine and medium-scale drivers of functional richness and divergence, including within-crown and complex branching variance, topography, sun aspect, and speciation. For the same kernel size, functional richness computed from coarsened pseudo-airborne products (pixel size of 2 m) was found to be 57-68% of that derived from UAS products. Functional divergence did not portray substantial differences across scales and resolutions, even though this metric further emphasized the complexity of the surveyed open-forest sclerophyll sites. UAS have the potential to become an efficient tool for monitoring FD linked with ecosystem processes at key monitoring sites, and for the validation and support of large-scale but less detailed airborne and satellite products. Finally, this study highlights the sensitivity of FD metrics to variations in scale, resolution, and TPD parametrization suggesting that more research is needed to standardize remote sensing protocols for the quantification of FD across spatial and temporal scales.
    WorkplaceGlobal Change Research Institute
    ContactNikola Šviková, svikova.n@czechglobe.cz, Tel.: 511 192 268
    Year of Publishing2025
    Electronic addresshttps://www.sciencedirect.com/science/article/pii/S0034425723005102?via%3Dihub
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