Optimization of Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery,in situ data with chemometrics to evaluate nutrients in the Shenandoah River,Virginia |
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| Authors: | Mbongowo J Mbuh |
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| Institution: | 1. Department of Geography and Geoinformation Science, University of North Dakota, Grand Forks, ND, USAMbongowo.mbuh@und.edu |
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| Abstract: | AbstractPhosphorus and nitrogen have a strong influence on water resource and remote sensing technology has demonstrated that water quality monitoring over a greater range of temporal and spatial scales can be used to overcome these constraints. This research was designed to demonstrate the feasibility of combining remotely-sensed water quality observation and chemometric techniques to estimate water quality in the Shenandoah River. We used Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery, combined with a partial least squares analysis to characterize the spatial distribution of nutrients in the Sheanadoah river. ARCHER retrievals for phosphorous with cross-validation show high sensitivity in estimating water quality in the Shenandoah River with the Bentonville in the South Fork, with an R2 of 0.93 sensitivity. Using the significance level of 0.05, data from the summer of 2014 showed that the p-value was 0.00 for both nitrogen and phosphorous. Results show retrieval method is transferable. |
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| Keywords: | Hyperspectral remote sensing field spectroscopy Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) water quality chemometrics |
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