Validation of Airborne Hyperspectral Imagery from Laboratory Panel Characterization to Image Quality Assessment: Implications for an Arctic Peatland Surrogate Simulation Site
Calibration/validation (cal/val) practices applied to airborne hyperspectral imagery of Arctic regions were developed and assessed as an integrated up-scaling methodology that considers: (i) calibration of a laboratory reflectance reference panel; (ii) cross-calibration of multiple field panels; (iii) quality assurance checks of field spectroscopy data; and, (iv) comparison of results with airborne hyperspectral imagery. Overall errors of up to 27% were reduced to <4% using these methods. Calibration results of the laboratory panel provided an improvement of 1% in the visible, near and lower shortwave infrared regions with respect to best estimates achievable using manufacturer supplied calibration data. This improvement was transferred to field panels using an in-house cross-calibration approach that also allowed panels to be assessed for degradation that occurs during field deployment. Comparison of the field spectroscopy results of four cal/val targets with hyperspectral imagery following atmospheric correction identified discrepancies from 1% to 4% (absolute) between 450 nm and 1050 nm, with errors as high as 27% at lower wavelengths. Application of scene-based refinements using two cal/val targets reduced this error across the entire spectral range (<4%) with the most significant improvements below 500 nm. These methods also have important implications to satellite image analysis, especially in Arctic and northern regions.
1.Natl Res Council Canada, Aerosp Res Ctr, Flight Res Lab, Ottawa, ON, Canada 2.McGill Univ, Dept Geog, Appl Remote Sensing Lab, Montreal, PQ, Canada
Recommended Citation:
Soffer, Raymond J.,Ifimov, Gabriela,Arroyo-Mora, Juan Pablo,et al. Validation of Airborne Hyperspectral Imagery from Laboratory Panel Characterization to Image Quality Assessment: Implications for an Arctic Peatland Surrogate Simulation Site[J]. CANADIAN JOURNAL OF REMOTE SENSING,2019-01-01