Title :
Four-scale linear model for anisotropic reflectance (FLAIR) for plant canopies. II. validation and inversion with CASI POLDER, and PARABOLA data at BOREAS
Author :
White, H. Peter ; Miller, John R. ; Chen, Jing M.
Author_Institution :
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ont., Canada
fDate :
5/1/2002 12:00:00 AM
Abstract :
For pt.I see ibid., vol.39, no.5, p.1072-83 (2001). To address the need for a flexible model of the bidirectional reflectance distribution function (BRDF) that is also suitable for inversion, the FLAIR Model (Four-Scale Linear Model for AnIsotropic Reflectance) has been developed H. P. White et al. (2001). Based on the more detailed Four-Scale Model J. M. Chen et al. (1997), FLAIR is a linear kernel-like model, developed with the aim of not being limited to specific canopy characteristics or view/illumination geometry, while maintaining a direct relationship between canopy architectural properties and model coefficients. Having been previously demonstrated to have the ability to capture the bi-directional patterns in both forward and inverse modes of calculation, this paper examines the FLAIR model in describing the boreal canopy by applying FLAIR to multiangular data sets obtained by various sensors during BOREAS 1994. Effects of sensor field of view, ranges of view/solar illumination geometry, and multiple sensor use on BRDF derivation and inversion for canopy parameter retrieval are considered
Keywords :
geophysical techniques; vegetation mapping; BRDF; FLAIR; bidirectional reflectance distribution function; boreal canopy; flexible model; four scale linear model for anisotropic reflectance; geophysical measurement technique; illumination geometry; inversion; light scattering; linear kernel-like model; multiangular data; optical remote sensing; plant canopy; validation; vegetation mapping; view geometry; Anisotropic magnetoresistance; Bidirectional control; Geometry; Layout; Lighting; Mathematical model; Reflectivity; Remote monitoring; Sensor phenomena and characterization; Solid modeling;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2002.1010891