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Article

Application of UAV Imagery to Detect and Quantify Submerged Filamentous Algae and Rooted Macrophytes in a Non-Wadeable River

1
Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USA
2
Division of Biological Sciences and Flathead Lake Biological Station, University of Montana, Missoula, MT 59812, USA
3
Division of Agriculture and Natural Resources, University of California, Davis, CA 95618, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(20), 3332; https://doi.org/10.3390/rs12203332
Received: 31 August 2020 / Revised: 3 October 2020 / Accepted: 9 October 2020 / Published: 13 October 2020
(This article belongs to the Special Issue She Maps)
Imagery from unoccupied aerial vehicles (UAVs) is useful for mapping floating and emerged primary producers, as well as single taxa of submerged primary producers in shallow, clear lakes and streams. However, there is little research on the effectiveness of UAV imagery-based detection and quantification of submerged filamentous algae and rooted macrophytes in deeper rivers using a standard red-green-blue (RGB) camera. This study provides a novel application of UAV imagery analysis for monitoring a non-wadeable river, the Klamath River in northern California, USA. River depth and solar angle during flight were analyzed to understand their effects on benthic primary producer detection. A supervised, pixel-based Random Trees classifier was utilized as a detection mechanism to estimate the percent cover of submerged filamentous algae and rooted macrophytes from aerial photos within 32 sites along the river in June and July 2019. In-situ surveys conducted via wading and snorkeling were used to validate these data. Overall accuracy was 82% for all sites and the highest overall accuracy of classified UAV images was associated with solar angles between 47.5 and 58.72° (10:04 a.m. to 11:21 a.m.). Benthic algae were detected at depths of 1.9 m underwater and submerged macrophytes were detected down to 1.2 m (river depth) via the UAV imagery in this relatively clear river (Secchi depth > 2 m). Percent cover reached a maximum of 31% for rooted macrophytes and 39% for filamentous algae within all sites. Macrophytes dominated the upstream reaches, while filamentous algae dominated the downstream reaches closer to the Pacific Ocean. In upcoming years, four proposed dam removals are expected to alter the species composition and abundance of benthic filamentous algae and rooted macrophytes, and aerial imagery provides an effective method to monitor these changes. View Full-Text
Keywords: benthic mapping; drones; submerged aquatic vegetation; filamentous algae; macrophytes benthic mapping; drones; submerged aquatic vegetation; filamentous algae; macrophytes
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MDPI and ACS Style

Kislik, C.; Genzoli, L.; Lyons, A.; Kelly, M. Application of UAV Imagery to Detect and Quantify Submerged Filamentous Algae and Rooted Macrophytes in a Non-Wadeable River. Remote Sens. 2020, 12, 3332. https://doi.org/10.3390/rs12203332

AMA Style

Kislik C, Genzoli L, Lyons A, Kelly M. Application of UAV Imagery to Detect and Quantify Submerged Filamentous Algae and Rooted Macrophytes in a Non-Wadeable River. Remote Sensing. 2020; 12(20):3332. https://doi.org/10.3390/rs12203332

Chicago/Turabian Style

Kislik, Chippie, Laurel Genzoli, Andy Lyons, and Maggi Kelly. 2020. "Application of UAV Imagery to Detect and Quantify Submerged Filamentous Algae and Rooted Macrophytes in a Non-Wadeable River" Remote Sensing 12, no. 20: 3332. https://doi.org/10.3390/rs12203332

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