Using Spectral Information at the Nir Water Absorption Features to Estimate Canopy Water Content and Biomass

Biomass is one of the key biophysical variables of interest in vegetation studies and it can be defined in terms of fresh matter weight or dry matter weight. Biogeochemical processes, such as photosynthesis, evaporation and net primary production, are directly related to foliar water and are moreover commonly limited by water stress. Therefore, canopy water content is important for the understanding of the terrestrial ecosystem functioning. Spectral information related to the water absorption features at 970 nm and 1200 nm offer interesting possibilities for deriving information on leaf and canopy water content. In the present work, hyperspectral reflectance data representing a range of canopies were simulated at the leaf level using the PROSPECT model and at the canopy level using the combined PROSPECT+SAILH model. Derivative spectra close to the absorption features at about 970 nm and 1200 nm showed a strong predictive power for the leaf and canopy water content (CWC). Ratio indices defining the absorption features had a smaller predictive power. The feasibility of using information from the water absorption features in the near-infrared (NIR) region of the spectrum was tested by estimating CWC and biomass for two quite different test sites. The first site was a homogeneously managed agricultural field with a grass/clover mixture and with very little variation within the field. The other site was a very heterogeneous natural area in the floodplain Millingerwaard along the river Waal in the Netherlands. Spectral information at both test sites was obtained with an ASD FieldSpec spectrometer during the summer of 2004. At the Millingerwaard site also a flight with the HyMap airborne imaging spectrometer was performed. Individual spectral bands and traditional vegetation indices based on red and NIR spectral bands yielded moderate estimates for biomass and CWC. Ratio indices and the continuum removal method describing the absorption features yielded good results. Best results were obtained for the derivative spectra. Highest correlation with CWC was obtained for the derivative spectrum at about 950 nm, meaning at the slope of the first water absorption feature. Promising results in estimating CWC and biomass for various vegetation types were not only obtained for field spectroradiometer data, but also for airborne imaging spectrometer data, indicating the potential for upscaling to larger areas.