Application of imaging spectroscopy to mapping canopy nitrogen in the forests of the central appalachian mountains using hyperion and aviris

Abstract

Earth Observing 1 (EO-1) Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery were used to predict canopy nitrogen (N) concentration for mixed oak forests of Green Ridge State Forest in Maryland. Nitrogen concentration was estimated for 27 ground plots using leaf samples of the dominant tree species from each plot that were dried, ground and analyzed in the laboratory for foliar N concentration. Foliar N data were composited based on relative species composition to determine overall canopy N concentration for the plot. Hyperion and AVIRIS images were converted to surface reflectance and related to canopy N using partial least squares (PLS) regression of first-derivative reflectance for wavelengths reported in the literature to be associated with N absorption features. The PLS model for Hyperion employed four factors and accounted for 97.8% of the variation in N concentrations and 40.4% of the variation in the spectral data whereas the AVIRIS model used three factors accounting for 84.9% of the variation in N and 72.4% of the variation in the spectral information. In the area of overlap between the AVIRIS and Hyperion images, >70% of the estimates from the two sensors were within 0.25%N of each other, indicating a very close fit between the models generated using data from Hyperion and AVIRIS. This research indicates the applicability of hyperspectral data in general and Hyperion data in particular for mapping canopy nitrogen concentration.