Mapping High Resolution Forest Chemistry with Aisa

In the current study, 2002 AVIRIS and 2006 AISA high resolution imagery were applied to the spectroscopic investigation of spatio-temporal variations in forest chemistry. Focused primarily on the foliar biochemistry of Douglas-fir (Pseudotsuga menziesii) stands within the Greater Victoria Watershed, Victoria, BC, Canada, samples were collected and relationships between chemistry and reflectance were established. Partial least-squares regression (PLS) was employed to estimate chemistry from canopy reflectance spectra. Data were stratified through the use of hyperspectral/LIDAR forest products, transformed to second order derivative imagery and chemistry maps generated from the PLS coefficients. Chemistry estimation achieved R 2 values ≥ 0.93 for both datasets. The PLS models applied to the hyperspectral imagery yielded two temporally discrete chemistry maps. Temporal and spatial differences were investigated. Conditions, anticipated to significantly impact forest chemistry, exhibited correspondence with spatial variations in the new forest information chemistry product.