Improving spatial monitoring of dredging operations : a small unmanned aerial system application to map turbidity

Wilkens, Justin L.; Suedel, Burton C.; Davis, Austin; Corbino, Jeffrey

doi:10.21079/11681/28978

Cited by 1 publication

(2 citation statements)

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“…This study effectively highlights how a standard multispectral drone sensor provides useful data for water quality applications associated with localized turbidity events during marine dredging. While monitoring turbidity plumes using traditional methods (i.e., on the water sampling) has proven to be an effective method in numerous situations, the high-resolution aerial view from a drone can increase ability to detect patchily distributed plumes, quantify extent, and track how a plume may move or dissipate over time [17]. The drone-based automated workflow presented in this study was successful in measuring turbidity ranging from 1-72 FNU and the larger-scale view from the drone highlighted how quickly surface turbidity plumes dissipated.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, by flying at lower elevations, drones can significantly increase spatial resolution. Applications for UAS in water quality monitoring are becoming increasingly prevalent, including trophic state mapping [13], eutrophication [14], water pollution [15], chlorophyll a concentration [16], and turbidity [17][18]. However, there remains a considerable knowledge gap in the application of multispectral drone sensors designed for terrestrial mapping to water quality monitoring.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating Dredge-Induced Turbidity using Drone Imagery

Hayes¹,

Puckett²,

Deaton³

et al. 2022

Preprint

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While maintenance dredging of port access channels is often required to maintain navigability, it can result in increased turbidity, sediment plumes, and associated reductions in water quality. Unoccupied aircraft systems (UAS, or drones) are increasingly applied to study water quality due to their high spatial and temporal resolutions. In this study, we investigated the use of drone imagery to monitor turbidity in the Morehead City Harbor, North Carolina, USA, during channel maintenance by hopper dredge. Drone flights were conducted concurrently with in-situ sampling during active dredging and post-dredging. Multispectral drone images were radiometrically calibrated, converted to reflectance and then turbidity using two separate processing methods and a single-band (red; 620nm-700nm) generic turbidity retrieval algorithm, and then compared to in-situ measurements. The method of using average reflectance to retrieve a single turbidity measurement per drone image produced agreeable results when compared to the in-situ measurements (R2 = 0.84). This method was then used to generate turbidity maps and extract surface plumes. While this could be considered a limited validation, the results indicate that realistic values can be obtained from drone imagery for low and high turbidity concentrations (1-72 FNU), making drones a viable option for monitoring surface turbidity associated with dredging.

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Section: Discussionmentioning

confidence: 99%