Coastal acidification, distinct from ocean acidification, is influenced by localized factors such as nutrient runoff, freshwater input, and decomposition. This study estimates carbonate system parameters in the Western Mississippi Sound (WMS) using integrated uncrewed aircraft systems (UAS) and autonomous surface vessel (ASV) observations. During 2018 to 2022, high-ressolution UAS imagery and in 2021 in situ ASV data including pH, pCO2, SST, SSS, CDOM, and Chl-a were collected. Machine learning algorithms were developed to estimate pCO2 and total alkalinity (TA), with random forest models achieving high accuracy (R2 > 0.91). A CDOM-based model was developed to derive SSS, which, along with Chl-a, fed into time-series mapping of TA and pCO2. Results highlight the effectiveness of combining UAS and ASV data to produce fine-scale carbonate system maps. This approach supports improved monitoring of coastal acidification and can be extended to estimate additional parameters such as calcite and aragonite saturation states and DIC.
Chowdhury M. O. S., Dash P., Nur A. M., Islam M. S., Panda R. M., Turnage G., Hathcock L., Chesser G. D. J. & Moorhead R. J., in press. High-resolution mapping of carbonate system parameters over coastal waters using integrated uncrewed aircraft systems (UAS) and Autonomous Surface Vessel (ASV) observations. International Journal of Remote Sensing. Article (subscription required).
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