Retrieval of the canopy leaf area index in the BOREAS flux tower sites using linear spectral mixture analysis

Abstract

This paper reports on the use of linear spectral mixture analysis for the retrieval of canopy leaf area index (LAI) in three flux tower sites in the Boreal Ecosystem-Atmosphere Study (BOREAS) southern study area: Old Black Spruce, Old Jack Pine, and Young Jack Pine (SOBS, SOJP, and SYJP). The data used were obtained by the Compact Airborne Spectrographic Imager (CASI) with a spatial resolution of 2 m in the winter of 1994. The convex geometry method was used to select the endmembers: sunlit crown, sunlit snow, and shadow. Along transects for these flux tower sites, the fraction of sunlit snow was found to have a higher correlation with the field-measured canopy LAI than the fraction of sunlit crown or the fraction of shadow. An empirical equation was obtained to describe the relation between canopy LAI and the fraction of sunlit snow. There is a strong correlation between the estimated LAI and the field-measured LAI along transects (with R 2 values of 0.54, 0.71, and 0.60 obtained for the SOBS, SYJP, and SOJP sites, respectively). The estimated LAI for the whole tower site is consistent with that obtained by the inversion of a canopy model in our previous study where values of 0.94, 0.92, and 0.63 were obtained for R 2 for the SOBS, SYJP and SOJP sites, respectively. The CASI 2-m summer data over the SOBS site was also employed to investigate the possibility of deriving canopy LAI from the summer data using linear mixture analysis. At a spatial resolution of 10 m, the correlation between the field-measured LAI and the estimated LAI along transects is small at R 2 less than 0.3, while R 2 increases to 0.6 at a spatial resolution of 30 m. The difficulty in canopy LAI retrieval from the summer data at a spatial resolution of 10 m is likely due to the variation of the understory reflectance across the scene, although spatial misregistration of the CASI data used may also be a possible contributing factor.