Hyperspectral Remote Sensing of Pasture Quality: Analysis and Prediction

Analysis of data from imaging spectrometers to determine vegetation parameters is a new and emerging field of science. Hyperspectral remote sensing using field spectra, HyMap and Hyperion images are here used to study the feed quality of pastures. Both environmental and economical benefits can be achieved from predictive relationships between hyperspectral data and pasture quality parameters. The research described in this book provides assessments of different analysis methods, including advantages and limitations of different approaches as well as recommendations for future investigations. The work was carried out at three study sites in Victoria, Australia. Results show that there is a clear potential for hyperspectral remote sensing to provide important inputs to management decision system as pasture quality is the third crucial component needed after biomass and growth rate. The book gives both a thourough background to hyperspectral analysis of vegetation to date and a comprehensive introduction to hyperspectral remote sensing of pastures. It should therefore be very of great interest to both students and professionals in the fields of remote sensing and agronomy.