Imaging spectroscopy and lightweight unmanned aerial vehicles (UAVs) have revolutionized remote sensing of vegetation, by providing high spectral and spatial resolution data. Comprehensive wetland monitoring should be based on reliable mapping of biophysical aquatic vegetation parameters, which in turn requires low bias in measured spectra, e.g. minimization of reflectance anisotropy. This study aims to quantitatively investigate how sensor scan direction and solar zenith angle (SZA) affect vegetation spectra over two dominant aquatic plants, Phragmites australis and Nuphar lutea, representing different functional types (i.e. emergent and floating) with divergent canopy structure and affinity with water, using data collected with a hyperspectral (400-1000 nm range) push-broom sensor mounted on a UAV. Anisotropy factor (ANIF), mean reflectance scatterplots and regression analysis were used for assessing the magnitude of spectral anisotropy at both pseudo-leaf and canopy scales. Our findings showed more accentuated anisotropic behaviour in the visible than near-infrared domain at SZA < 60 degrees as the scan direction approaches that of solar principal plane. The increase in reflectance in near-forward direction affects the spectra of floating-leaved N. lutea at both leaf and canopy scales, suggesting the presence of water (as a film over leaves or as canopy background) as a likely anisotropy driver. Backward hotspot is evident in canopy spectra of emergent P. australis, with driving mechanisms similar to terrestrial species (i.e. shadow-hiding). At SZA > 60 degrees, reflectance anisotropy appears to be negligible, independent of functional type and scan direction. This research underscores the importance of considering sun-target-sensor geometry in remote sensing studies on aquatic vegetation.

Effects of functional type and angular configuration on reflectance anisotropy of aquatic vegetation in ultra-high resolution hyperspectral imagery

Piaser E.
Primo
;
Berton A.;Caccia M.;Gallivanone F.;Villa P.
Ultimo
2024

Abstract

Imaging spectroscopy and lightweight unmanned aerial vehicles (UAVs) have revolutionized remote sensing of vegetation, by providing high spectral and spatial resolution data. Comprehensive wetland monitoring should be based on reliable mapping of biophysical aquatic vegetation parameters, which in turn requires low bias in measured spectra, e.g. minimization of reflectance anisotropy. This study aims to quantitatively investigate how sensor scan direction and solar zenith angle (SZA) affect vegetation spectra over two dominant aquatic plants, Phragmites australis and Nuphar lutea, representing different functional types (i.e. emergent and floating) with divergent canopy structure and affinity with water, using data collected with a hyperspectral (400-1000 nm range) push-broom sensor mounted on a UAV. Anisotropy factor (ANIF), mean reflectance scatterplots and regression analysis were used for assessing the magnitude of spectral anisotropy at both pseudo-leaf and canopy scales. Our findings showed more accentuated anisotropic behaviour in the visible than near-infrared domain at SZA < 60 degrees as the scan direction approaches that of solar principal plane. The increase in reflectance in near-forward direction affects the spectra of floating-leaved N. lutea at both leaf and canopy scales, suggesting the presence of water (as a film over leaves or as canopy background) as a likely anisotropy driver. Backward hotspot is evident in canopy spectra of emergent P. australis, with driving mechanisms similar to terrestrial species (i.e. shadow-hiding). At SZA > 60 degrees, reflectance anisotropy appears to be negligible, independent of functional type and scan direction. This research underscores the importance of considering sun-target-sensor geometry in remote sensing studies on aquatic vegetation.
2024
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA - Sede Secondaria Milano
Istituto di Geoscienze e Georisorse - IGG - Sede Pisa
Istituto di Bioimmagini e Fisiologia Molecolare - IBFM
Aquatic vegetation
spectral anisotropy
push-broom sensor
UAV imagery
wetlands
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/530472
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