Analysis of spectral absorption features in hyperspectral imagery

By F. Meer. 2004

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Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network (2015, neutral): “For this reason, hyperspectral data are used in a wide range of applications such as agriculture [3], mineralogy [4], surveillance [5], astronomy [7], and environmental sciences [9], [10].”
Deep Learning-Based Classification of Hyperspectral Data (2014, background): “An incomplete list includes agriculture [3], mineralogy [4], surveillance [5], physics [6], astronomy [7], chemical imaging [8], and environmental sciences [9], [10].”
Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data (2011, methodology): “CR is most often used in spectral data analysis to identify the geological composition of materials and to quantify vegetation biochemistry (Huang et al., 2004; Kruse & Lefkoff, 1993; Mutanga & Skidmore, 2004; van der Meer, 2004).”