Airborne hyperspectral remote sensing to assess spatial distribution of water quality characteristics in large rivers: The Mississippi River and its tributaries in Minnesota

Aircraft-mounted hyperspectral spectrometers were used to collect imagery with high spatial and spectral resolution for use in measuring optically active water quality characteristics of major rivers of Minnesota. Ground-based sampling undertaken concurrent with image acquisition provided calibration data for chlorophyll, suspended solids, turbidity and other measures of water clarity. Our approach identified the spectral characteristics that distinguish waters dominated by several inherent optical properties (IOPs), and we used those characteristics to develop models to map water quality characteristics in optically complex waters. For phytoplankton related variables (volatile suspended solids (VSS) and chlorophyll a (chl a)), the ratios of the scattering peak at the red edge (similar to 700 nm) with the reflectance troughs caused by chlorophyll absorption at similar to 670 nm and other plant pigment absorption peaks at 592 and 620 nm all were strong predictors of chl a and VSS (r(2) values of 0.73-0.94). The scattering peak at similar to 700 nm was a strong predictor of variables related to water clarity (total suspended solids (TSS), turbidity and turbidity tube (T-tube)) (r(2) values of 0.77-0.93). For mineral-based variables (nonvolatile suspended solids (NVSS) and the ratio NVSS:TSS), combinations of the TSS and chl a relationships described above were strong predictors (r(2) values of 0.73-0.97) and the most robust because this model corrects for the scattering of phytoplankton at similar to 700 nm. Application of the methods to quantify spatial variations in water quality for stretches of the Mississippi River and its tributaries indicate that hyperspectral imagery can be used to distinguish and map key variables under complex IOP conditions, particularly to separate and map inorganic suspended sediments independently of chlorophyll levels. (C) 2012 Elsevier Inc. All rights reserved.