Atmospheric characterization using space-based hyperspectral imaging systems

The detection and subsequent quantification of certain effluent pollutants into the atmosphere can assist policy makers in formulating effective guidelines for public safety and environmental quality standards. This process is complicated by the fact that the atmospheric varies in radiometric properties not necessarily represented by data gathered with radiosonde devices. This work discusses a hyperspectral processing approach that addresses this complication and proposes the use of in-situ atmospheric radiometric measurements to negate uncertainty associated with atmospheric spectral transmission. Specifically, This work describes an algorithm called MBAR (Model-Based Atmospheric Retrieval) that characterizes three atmospheric line-of-sight properties: transmission, upwelling, and downwelling radiance. It is the uncertainty in these properties that often impact the fidelity associated with the detection and quantification process.