Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications

Several methods for the analysis of remotely sensed reflectance data are compared, including empirical methods and scattering theories, both of which are important for solving remote sensing problems. The concept of the photon mean optical path length and the implications for use in modeling reflectance spectra are presented. It is shown that the mean optical path length in a particulate surface is in rough inverse proportion to the square root of the absorption coefficient. Thus, the stronger absorber a material is, the less photons will penetrate into the surface. The concept of apparent absorbance (‐In reflectance) is presented, and it is shown that absorption bands, which are Gaussian in shape when plotted as absorption coefficient (true absorbance) versus photon energy, are also Gaussians in apparent absorbance. However, the Gaussians in apparent absorbance have a smaller intensity and a width which is a factor of √2 larger. An apparent continuum in a reflectance spectrum is modeled as a mathematical function used to isolate a particular absorption feature for analysis. It is shown that a continuum should be removed by dividing it into the reflectance spectrum or subtracting it from the apparent absorbance and that the fitting of Gaussians to absorption features should be done using apparent absorbance versus photon energy. Kubelka‐Munk theory is only valid for materials with small total absorption and for bihemispherical reflectance, which are rarely encountered in geologic remote sensing. It is shown that the recently advocated bidirectional reflectance theories have the potential for use in deriving mineral abundance from a reflectance spectrum.