The derivation of water volume reflectances from airborne MSS data using in situ water volume reflectances, and a combined optimization technique and radiative transfer model

Water volume reflectance images of three water cooling reservoirs were derived from airborne Daedalus DS-1260 multispectral scanner (MSS) data using a radiative transfer model to eliminate atmospheric effects and to derive downwell-ing irradiances. Sixty in situ water volume reflectances and the associated sensor and sun geometries were input into the radiative transfer model. Using the radiative transfer model to generate water volume reflectance values at each field site, an optimization procedure minimized the difference between modelled and in situ water volume reflectances resulting in optimized sensor brightness value to radiance conversion gain and bias factors, and optimized surface visual range and mean terrain background reflectance. Subsequently water volume reflectance images were derived at six wavelengths encompassing the blue to near-infrared using the optimized atmospheric parameters and conversion factors as inputs into the radiative transfer model. Modelled reflectance images were evaluated for accuracy by statistical comparison to the in situ reflectances, and for improved contrast by subjective comparison to the original images. Daedalus DS-1260 MSS bands 3, 4, 5, 7 and 8 modelled reflectances explained 19, 78, 86, 89 and 82 per cent, respectively of the in situ reflectance variances, while band 2 correlation was not significant (p<0.05). All generated reflectance image histograms showed dramatic improvement in contrast when compared with the histograms depicting variance within the original images.