A Review of Atmospheric Correction Techniques for Hyperspectral Remote Sensing of Land Surfaces and Ocean Color

The concept of imaging spectrometry, or hyperspectral imaging, was originated from the NASA Jet Propulsion Laboratory in the early 1980s. Different types of imaging spectrometers have been built. Scientific data have been collected with these instruments from aircraft and satellite platforms. Because imaging spectrometer data contain absorption and scattering effects from atmospheric gases and aerosols, the atmospheric effects must be removed in order to use the data for quantitative remote sensing of land surfaces and ocean color. Over the years, the atmospheric correction algorithms have evolved from the earlier empirical line method and flat field method to more recent methods based on rigorous radiative transfer modeling. We will give an overview of hyperspectral atmospheric correction algorithms developed during the past two decades. Issues related to spectral smoothing will be discussed. Suggestions for improvements to the present atmospheric correction algorithms will be given.