Mapping canopy parameter in a Mediterranean grassland with airborne hyperspectral imagery

The canopy chlorophyll content is one of the prime parameters that characterize the grassland status and hence an important information for grassland's management. Hyperspectral remote sensing with narrow and continuous spectral bands is potentially more sensitive to specific vegetation variables such as the amount of greenness (LAI) and canopy chlorophyll content. In this study, mapping of canopy chlorophyll content is investigated in a Mediterranean grassland using hyperspectral images. HyMap airborne images were acquired over Majella National Park, Italy, in July 2005. In situ measurements of canopy chlorophyll content were collected in parallel with the acquisition of the imagery. We compared the use of different statistical models such as narrow band vegetation indices and partial least squares regression for estimating the parameter of interest. The results of the study demonstrate that the canopy chlorophyll content can be estimated using different statistical models with reasonable accuracies (Cross validated RMSE= 0.17).