Hyperspectral remote sensing of conifer chemistry and moisture

The chemical and moisture composition of conifer foliage in the Greater Victoria Watershed District (GVWD), Vancouver Island, Canada, was explored using hyperspectral remote sensing data. Imagery acquired from the airborne sensor Advanced Visible/Infrared Imaging Spectrometer (AVIRIS) were evaluated along with sampled foliar chemical and moisture measurements to provide insight into ecological processes occurring within the watershed. Concentrations of nitrogen, total chlorophyll and moisture were used to provide an analysis of the forest canopy, comprised of Coastal Douglas-fir and Western Redcedar. The AVIRIS data were processed to correct atmospheric and geometric distortion. The AVIRIS data were used to investigate the relationship between the hyperspectral imagery and the sampled chemical data. A total of 45 plots in the GVWD were samples from a helicopter. These samples provided both organic and inorganic analysis of the forest canopy. A Partial Least Squares regression was used to analyze the relationship between the data sets in order to extract chemical constituents in the forest canopy. Results indicate that the regression equation explains 81%, 79% and 70% of the variation in nitrogen, total chlorophyll and moisture, respectively. An analysis of the chemical characteristics of the canopy can provide insight into factors controlling growth such as nutrient levels and water deficiencies at the foliar level.