Canopy assessment of biochemical features by ground-based hyperspectral data for an invasive species, giant reed (Arundo donax).

This study explored the potential use of hyperspectral data in the non-destructive assessment of chlorophyll, carbon, and nitrogen content of giant reed at the canopy level. We found that pseudoabsorption and derivatives of original hyperspectral data were able to describe the relationship between spectral data and measured biochemical characteristics. Based on correlogram analyses of ground-based hyperspectral data, we found that derivatives of pseudoabsorption were the best predictors of chlorophyll, carbon, and nitrogen content of giant reed canopies. Within the visible region, spectral data significantly correlated with chlorophyll content at both 461 nm and 693 nm wavelengths. Within the near-infrared region, carbon levels correlated with hyperspectral data at five causal wavelengths: 1038 nm, 1945 nm, 1132 nm, 1525 nm, and 1704 nm. The best spectral wavelength for estimating nitrogen content was 1542 nm. Such relationships between nutrient content and spectral data were best represented by exponential functions in most situations.