On-bottom oyster aquaculture in Maryland, USA has witnessed record production and revenue within recent years. With the oyster industry’s growth and continued use of antiquated equipment from the early 1800s, there is an increasing need for advancement of culturing technologies that improve yield while reducing working hours and environmental impact. Remote operated vehicles (ROV) are increasingly being used to aid a variety of agricultural operations. Similarly, there is growing interest in utilizing ROV to provide oyster farmers with critical crop information, possibly improving their management and yield for greater profits.
The use of ROV to collect data is far from optimized and environmental conditions may constrain how they are used to collect data. For example, under low visibility, ROV pilots may want to position the system near the sediment-water interface of oyster leases where the animals reside to use optical sensors. However, ROV have been observed to disturb the bed and transport overlaying sediments while surveying on-bottom oyster leases, creating sediment plumes that diminish water quality and reduce light penetration. These plumes have the potential to negatively affect organisms, especially if the concentration of sediments is high and sustained for long periods of time. Importantly, the plumes may impede collection of image and water quality data, undermining their intended use. Research is needed to understand ROV impacts to aid their use and adoption within the aquaculture industry.
Our broader research team has developed sensing procedures for ROV to survey crop inventories, substrate characteristics, and water quality within on-bottom lease. We monitored sediment plumes created by a ROV collecting this crop/lease information. A DJI Phantom 4 unmanned aerial vehicle with a Micasense RedEdge MX Multispectral camera captured near-infrared (NIR) imagery of reflectance changes caused TSS presence at the water surface and a Nortek Signature1000 acoustic doppler current profiler to monitored backscatter intensity as an indirect indicator of TSS concentration throughout the water column. Together, we were able to measure changes in TSS caused by ROV induced sediment plumes before, during, and after impact. The resulting NIR imagery was used to create predictive maps of TSS throughout the water surface. Backscatter measures were used to create a time-series and 3-dimensional maps of TSS in the water column. Then TSS values within surface images, time series, and 3D maps were compared before, during, and after impact individually through analysis of variance. Information gathered from this study can be used to optimize ROV development for aquaculture applications to reduce water quality impact and improve sustainability measures of such technologies.