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Given the ever-expanding usage of hyperspectral imagery in earth imaging applications and the proliferation of various types and capabilities of new and planned hyperspectral sensors, the need for rigorous calibration and characterization has become essential; especially when there is a requirement and need for using different sensors in performing change detection and other applications using temporal spatial/spectral signatures. This manuscript will cover an overview of the methodologies utilized and show results of spectral and radiometric calibration performed on the GHOSt payloads as well as the optical characterization specified by the empirically-derived system point spread function. An exemplar of this review would step through a radiometric calibration in acquiring near-nadir imagery of a RadCalNet site such as Railroad Valley, Nevada, obtaining near-coincident atmospheric characterization data from RadCalNet, transforming these data for use in a forward model, propagating to Top-of-the-Atmosphere (TOA) spectral radiance, deriving calibration coefficients, and presenting examples of before and after calibration imagery. Discussion includes challenges acquiring imagery and sufficient data to perform a calibration and various alternative community-accepted methods available. Spectral calibration of the GHOSt hyperspectral sensor will also be covered, from initial pre-launch calibration in the lab to methodology and results computed from gathered imagery over homogeneous areas in USGS pseudo-invariant sites. Optical characterization includes PSF/MTF information derived in the pre-launch in the lab and empirically derived PSFs from selected in-scene targets such as bridges, buildings, and other man-made target sets. The presentation of the calibration and characterization of this sensor payload, which has no onboard calibration or characterization additions, is expected to contribute to the continuing community discussion toward future accomplishment in hyperspectral and other types of satellite imagery standardization, quality assessment, and the expanding complementary use of imagery products.
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