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Hyperspectral remote sensing provides great potential to monitor and study biodiversity of tropical forests through species identification and mapping. In this study, five species were selected to examine crown-level spectral variation within and between species using HYperspectral Digital Collection Experiment (HYDICE) data collected over La Selva, Costa Rica. Spectral angle was used to evaluate the spectral variation in reflectance, first derivative and wavelet-transformed spectral domains. Results indicated that intra-crown spectral variation does not always follow a normal distribution and can vary from crown to crown, therefore presenting challenges to statistically define the spectral variation within species using conventional classification approaches that assume normal distributions. Although derivative analysis has been used extensively in hyperspectral remote sensing of vegetation, our results suggest that …