“…Even though much of the early research in hyperspectral remote sensing was overwhelmingly focused on minerals, now there is substantial literature in characterization, monitoring, modeling, and mapping of vegetation and agricultural crops using ground-based, platform-mounted, airborne, Unmanned Aerial Vehicle (UAV) mounted, and spaceborne hyperspectral remote sensing (Swatantran et al, 2011;Atzberger, 2013;Schlemmer et al, 2013;Udelhoven et al, 2013;Zhang et al, 2013). The state-of-the-art in hyperspectral remote sensing of vegetation and agriculture shows significant enhancement over conventional remote sensing, leading to improved and targeted modeling and mapping of specific agricultural characteristics such as: (a) biophysical and biochemical quantities (Galvão, 2011;Clark and Roberts, 2012), (b) crop type\species , (c) management and stress factors such as nitrogen deficiency, moisture deficiency, or drought conditions (Delalieux et al, 2009;Gitelson, 2013;Slonecker et al, 2013), and (d) water use and water productivities . At the same time, overcoming Hughes' phenomenon or curse of dimensionality of data and data redundancy (Plaza et al, 2009) is of great importance to make rapid advances in a much wider utilization of hyperspectral data.…”