Lookup NU author(s): Dr Rachel Gaulton
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Vegetation moisture content is an important early indicator of forest drought stress, disease and fire risk. Existing remote sensing techniques to measure biochemical properties of vegetation, such as Equivalent Water Thickness (EWT), are limited by an inability to differentiate canopy and understorey properties and are influenced by variations in canopy structure. By providing a range-resolved estimate of reflectance, laser scanner measurements have the potential to overcome these limitations. Dual-wavelength laser scanning can provide an active measurement of reflectance from which spectral indices can be derived that are insensitive to range, incidence angle and scattering area of the target within the laser beam, factors that make exploiting single-wavelength laser scanner intensity data difficult. This study demonstrates the potential of dual-wavelength laser scanning for measurement of leaf biochemical properties, through determining the relationship between a laser-scanner-derived spectral index, using near infrared (1063 nm) and middle infrared (1545 nm) wavelengths, and the EWT of individual leaves. The suitability and sensitivity of the index is tested using a leaf optical properties model (PROSPECT-5) and the method is tested experimentally under laboratory conditions using the Salford Advanced Laser Canopy Analyser. A strong relationship (R2 = 0.8, RMSE = 0.0069 g cm− 2) was found between a normalised ratio of the two wavelengths and measured EWT of leaf samples. The relationship corresponds well to that predicted by modelling. However, the experimental data also revealed significant spatial variability in the index value across individual leaves, suggesting heterogeneity in moisture distribution at within-leaf scales. The study suggests significant potential for using dual-wavelength and multispectral laser scanning for measuring vegetation biochemical properties.
Author(s): Gaulton R, Danson FM, Ramirez FA, Gunawan O
Publication type: Article
Publication status: Published
Journal: Remote Sensing of Environment
Print publication date: 01/05/2013
ISSN (print): 0034-4257
ISSN (electronic): 1879-0704
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