ABSTRACT
Hyperspectral imaging spectroscopy data will become increasingly available and important in advancing global studies pertaining to agriculture, water, food security, and climate variability. This chapter provides an overview of the significant advances that can be made by using hyperspectral sensors for reducing uncertainties in modeling, mapping, and monitoring global change studies. However, challenges exist in data access, data storage, data visualization, and analytical methodologies. Nevertheless, with the dawn of cloud computing, machine learning, and artificial intelligence, these challenges are slowly overcome. The chapter discusses these challenges and suggests solutions. Many hyperspectral imaging spectrometers are going to be launched into space (e.g. HyspIRI of NASA) that makes it feasible to collect extensive data of the Planet Earth in 100s of hyperspectral narrowbands along various portions of the electromagnetic spectrum.
