Spectral separability among six southern tree species

Spectroradiometer data (350 to 2500 nm) were acquired in lots summer 1999 o ver various forest sites in Appomattox Buckingham State Forest, Virginia, t o assess the spectral differentiability among six major forestry tree speci es: loblolly pine (Pinus taeda), Virginia pine (Pinus virginiana), shortlea f pine (Pinus echinata), scarlet oak (Quercus coccinea), white oak (Quercus alba), and yellow poplar (Liriodendron tulipifera). Data were smoothed and curve shape was determined using first- and second-difference operators. S tepwise discriminant analysis was used to decrease the number of independen t variables, after which a canonical discriminant analysis and a normal dis criminant analysis were performed. Cross-validation accuracies varied from 99 percent to 100 percent (hardwood versus pine groups), 62 percent to 84 p ercent (within pine group), and 78 percent to 93 percent (within hardwood g roup). The second difference of a nine-point weighted average proved most a ccurate overall, with cross-validation accuracies of 84 percent (within pin e separability), 93 percent (within hardwood separability), and 100 percent (between group separability). Landsat simulation data had lower accuracies , varying from 93 percent to 96 percent (hardwood versus pine groups), 45 p ercent to 60 percent (within pine group), and 54 percent to 70 percent (wit hin hardwood group). The relatively low accuracies for Landsat simulation d ata indicate the need for high spectral resolution data for within group se parability. The variables significant in defining spectral separability wit hin and between groups were largely located in the visible (350- to 700-nm) and shortwave infrared I (700- to 1850-nm) regions of the spectrum, with m arkedly less representation in the shortwave infrared II(1700- to 2500-nm) region. Some wavelengths related to nitrogen concentration and O-H bond reg ions were evident, but not dominant.