Deriving Vegetation Indices for 3D Canopy Chlorophyll Content Mapping Using Radiative Transfer Modelling

Leaf chlorophyll content is a major indicator of plant health and productivity. Optical remote sensing estimation of chlorophyll limits its retrievals to two-dimensional (2D) estimates, not allowing examination of its distribution within the canopy, although it exhibits large variation across the vertical profile. Multispectral and hyperspectral Terrestrial Laser Scanning (TLS) instruments can produce three-dimensional (3D) chlorophyll estimates but are not widely available. Thus, in this study, 14 chlorophyll vegetation indices were developed using six wavelengths employed in commercial TLS instruments (532 nm, 670 nm, 808 nm, 785 nm, 1064 nm, and 1550 nm). For this, 200 simulations were carried out using the novel bidirectional mode in the Discrete Anisotropic Radiative Transfer (DART) model and a realistic forest stand. The results showed that the Green Normalized Difference Vegetation Index (GNDVI) of the 532 nm and either the 808 nm or the 785 nm wavelengths were highly correlated to the chlorophyll content (R2 = 0.74). The Chlorophyll Index (CI) and Green Simple Ratio (GSR) of the same wavelengths also displayed good correlation (R2 = 0.73). This study was a step towards canopy 3D chlorophyll retrieval using commercial TLS instruments, but methods to couple the data from the different instruments still need to be developed.

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Publication Details

Journal
Forests
Published
2024-10-25
DOI
https://doi.org/10.3390/f15111878
Citations
5
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
2.29
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article

Deriving Vegetation Indices for 3D Canopy Chlorophyll Content Mapping Using Radiative Transfer Modelling

Magdalena Śmigaj, Rachel Gaulton, Ahmed Elsherif, Alexander Shenkin et al.
5 citations
Forests
Remote Sensing in Agriculture
2.29
article

Deriving Vegetation Indices for 3D Canopy Chlorophyll Content Mapping Using Radiative Transfer Modelling

Magdalena Śmigaj, Rachel Gaulton, Ahmed Elsherif, Alexander Shenkin, Jean‐Philippe Gastellu‐Etchegorry
article en
5 citations

Abstract

Leaf chlorophyll content is a major indicator of plant health and productivity. Optical remote sensing estimation of chlorophyll limits its retrievals to two-dimensional (2D) estimates, not allowing examination of its distribution within the canopy, although it exhibits large variation across the vertical profile. Multispectral and hyperspectral Terrestrial Laser Scanning (TLS) instruments can produce three-dimensional (3D) chlorophyll estimates but are not widely available. Thus, in this study, 14 chlorophyll vegetation indices were developed using six wavelengths employed in commercial TLS instruments (532 nm, 670 nm, 808 nm, 785 nm, 1064 nm, and 1550 nm). For this, 200 simulations were carried out using the novel bidirectional mode in the Discrete Anisotropic Radiative Transfer (DART) model and a realistic forest stand. The results showed that the Green Normalized Difference Vegetation Index (GNDVI) of the 532 nm and either the 808 nm or the 785 nm wavelengths were highly correlated to the chlorophyll content (R2 = 0.74). The Chlorophyll Index (CI) and Green Simple Ratio (GSR) of the same wavelengths also displayed good correlation (R2 = 0.73). This study was a step towards canopy 3D chlorophyll retrieval using commercial TLS instruments, but methods to couple the data from the different instruments still need to be developed.

ForestsVol. 15(11)
Centre National de la Recherche Scientifique (FR), Université Fédérale de Toulouse Midi-Pyrénées (FR), Northern Arizona University (US), Tanta University (EG), Centre d'Études Spatiales de la Biosphère (FR), Institut de Recherche pour le Développement (FR), Newcastle University (GB), Wageningen University & Research (NL)
Openalex Percentile: Top 12%
Remote Sensing in Agriculture
2.29
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