In situ hyperspectral data analysis for nutrient estimation of giant sequoia

Abstract

In this paper, some correlation analysis results between in situ hyperspectral data in the spectral range of approximately 350 nm - 900 nm and three foliage nutrient constituents (% of dry weight): total nitrogen (TN), total phosphorus (TP), and total potassium (TK), were reported. 240 hyperspectral measurements were taken using a PSD1000 spectrometer at a Giant sequoia plantation site, in California, in 1997. Foliage nutrient concentrations were measured from the same site. The potential of hyperspectral data for estimating foliage nutrient status was evaluated using univariate correlation and multivariate regression analysis methods with different types of predictors. Results show that the best foliage nutrient prediction was obtained with the PCA-based predictors in 4-term prediction models for all three nutrient constituents.