ABSTRACT

Pasturelands cover extensive areas of noniced land in the world and are distributed across diverse ecosystems. This land-cover type has economic importance for livestock production and provides environmental and ecological services. The ability to accurately measure the biophysical and biochemical properties of grass contributes to the estimation of pasture quantity and quality and improvement of management strategies. Hyperspectral data provide a large number of narrowbands and its derivatives, including spectral features, reflectance indices, and spectral transformation data, have been found to be well correlated with vegetation biophysical and biochemical attributes. Recently, hyperspectral remote sensing data, from both field and imaging spectrometers, have been used to estimate pasture attributes including biomass, nutrients, and leaf area index. Spectral absorption features in grass spectra indicate the contents of key constituents of forage as well as its health conditions that can potentially provide useful information for the efficient management of livestock. Technical approaches to the estimation and prediction of pasture attributes using hyperspectral remote sensing have made significant progress recently. This chapter presents a review of hyperspectral remote sensing of pastures covering issues from basic spectral characteristics of pastures to the state of the art of hyperspectral remote sensing of pasturelands, highlighting recent advances made using field-based and imaging spectrometers.