Sensors 2015, 15(3), 6152-6173; https://doi.org/10.3390/s150306152
Expected Improvements in the Quantitative Remote Sensing of Optically Complex Waters with the Use of an Optically Fast Hyperspectral Spectrometer—A Modeling Study
Remote Sensing Division, Naval Research Laboratory, 4555 Overlook Ave. SW, Washington, DC 20375, USA
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Academic Editor: Assefa M. Melesse
Received: 23 December 2014 / Revised: 2 March 2015 / Accepted: 3 March 2015 / Published: 13 March 2015
(This article belongs to the Section Remote Sensors)
Abstract
Using simulated data, we investigated the effect of noise in a spaceborne hyperspectral sensor on the accuracy of the atmospheric correction of at-sensor radiances and the consequent uncertainties in retrieved water quality parameters. Specifically, we investigated the improvement expected as the F-number of the sensor is changed from 3.5, which is the smallest among existing operational spaceborne hyperspectral sensors, to 1.0, which is foreseeable in the near future. With the change in F-number, the uncertainties in the atmospherically corrected reflectance decreased by more than 90% across the visible-near-infrared spectrum, the number of pixels with negative reflectance (caused by over-correction) decreased to almost one-third, and the uncertainties in the retrieved water quality parameters decreased by more than 50% and up to 92%. The analysis was based on the sensor model of the Hyperspectral Imager for the Coastal Ocean (HICO) but using a 30-m spatial resolution instead of HICO’s 96 m. Atmospheric correction was performed using Tafkaa. Water quality parameters were retrieved using a numerical method and a semi-analytical algorithm. The results emphasize the effect of sensor noise on water quality parameter retrieval and the need for sensors with high Signal-to-Noise Ratio for quantitative remote sensing of optically complex waters. View Full-TextKeywords:
F-number; Dyson; HICO; sensor noise; atmospheric correction; coastal waters; water quality; signal-to-noise ratio (SNR); hyperspectral; remote sensing
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Moses, W.J.; Bowles, J.H.; Corson, M.R. Expected Improvements in the Quantitative Remote Sensing of Optically Complex Waters with the Use of an Optically Fast Hyperspectral Spectrometer—A Modeling Study. Sensors 2015, 15, 6152-6173.