Remote sensing involves the acquisition of visible, near infrared, and short-wave infrared images in several broad wavelength bands and differentiating materials by their spectral reflectance signatures.

“Hyperspectral remote sensing is the definitive optical tool for increasing knowledge and understanding of the Earth's surface. Contiguous high-resolution spectrometry provides a new dimension in mapping capability because of the potential for quantitative measurement of surface biogeochemistry.” (John S. MacDonald, Susan L. Ustin, and Michael E. Schaepman. “The Contributions of Dr. Alexander F. H. Goetz to Imaging Spectroscopy.” Remote Sensing of Environment. September 2009: S2-S4.) 

Multispectral remote sensing involves the acquisition of visible, near infrared, and short-wave infrared images in several broad wavelength bands. Different materials reflect and absorb differently at different wavelengths. As such, it is possible to differentiate among materials by their spectral reflectance signatures as observed in these remotely sensed images, whereas direct identification is usually not possible. NASA’s Landsat, one of the more common multispectral imagers, is widely used for monitoring a wide range of landscape scale properties.

Hyperspectral imaging systems acquire images in over one hundred contiguous spectral bands. While multispectral imagery is useful to discriminate land surface features and landscape patterns, hyperspectral imagery allows for identification and characterization of materials. In addition to mapping distribution of materials, assessment of individual pixels is often useful for detecting unique objects in the scene.

Well-developed scientific application areas include geology and mineral exploration; forestry; marine, coastal zone, inland waters and wetlands; agriculture; ecology; urban; snow and ice; and atmosphere. There are also numerous military applications in camouflage, littoral zone mapping, and landmine detection. Hyperspectral sensors pose an advantage over multispectral sensors in their ability to identify and quantify molecular absorption. The high spectral resolution of a hyperspectral imager allows for detection, identification and quantification of surface materials, as well as inferring biological and chemical processes.

For these applications, ground truth signatures collected in the field and indexed in spectral libraries are critical for many methods of analysis. While image processing packages often include basic spectral libraries, application distinct libraries containing spectra of the specific materials occurring in the target field area greatly improves the accuracy of generated interpretations. Spectra of vegetation are influenced by such a wide range of environmental conditions that it makes it difficult to adequately represent this variability without the collection of site specific field spectra.