BRDF normalization of hyperspectral image data

• Published in: IEEE International Geoscience and Remote Sensing Symposium Vol. 4; pp. 2572 - 2574 vol.4
• Main Authors: White, H.P., Lixin Sun, Champagne, C.M., Staenz, K., Leblanc, S.G.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2002
• Subjects: Bidirectional control; Condition monitoring; Distribution functions; Geometry; Hyperspectral imaging; Hyperspectral sensors; Image sensors; Reflectivity; Scattering; Vegetation mapping
• ISBN: 9780780375369; 078037536X
• DOI: 10.1109/IGARSS.2002.1026614

Monitoring vegetative areas with airborne hyperspectral sensors is being more frequently used to relate at-canopy spectral reflectance to canopy condition. Increased application of these techniques is expected with the advent of space-borne hyperspectral systems (such as EO-1 Hyperion and CHRIS-PROBA). These studies are often limited by the non-Lambertian nature of vegetation reflectance, the well known bidirectional reflectance distribution function (BRDF), where varying solar and viewing geometry can result in significant variations in the observed remotely sensed signal due to canopy architectural properties. This is often noted as an increased brightening of the observed signal as the scattering angle between the Sun and sensor decreases. This is also true when attempting to compare images from different sensors, or from the same sensor taken at different times. Various studies have examined the sensitivity of broadband and hyperspectral vegetation indices (VIs) to BRDF. These studies often conclude that the choice of VI should be based on the solar/viewing geometry and vegetation specific to the image acquisition. No individual VI appears immune to the BRDF effect. Rather than attempt to define a technique with little sensitivity to view/solar geometry, the non-Lambertian reflectance characteristics can be used to normalize imagery to one view/solar geometry. Assuming consistent mean leaf and background reflectance, inversion of a semi-empirical model can be used to determine BRDF coefficients, which can then be applied to normalize the imagery to a specific viewing/solar geometry. If the model has coefficients that directly relate to canopy properties, then this process can also provide information directly relating canopy architectural and biophysical properties to the remotely sensed signals. One such model, FLAIR, has been successfully used to investigate canopy characteristics from broadband imagery. Application of this model to hyperspectral imagery of an agricultural area is being pursued, examining the usefulness of normalizing the BRDF before relating spectral reflectance to biophysical characteristics.