Benefits and Challenges of UAS Imagery for Eelgrass (Zostera marina) Mapping in Small Estuaries of the Canadian West Coast

Nahirnick, Natasha K.; Hunter, Paul; Costa, Maycira; Schroeder, Sarah; Sharma, Tara

doi:10.2112/jcoastres-d-18-00079.1

Cited by 18 publications

(20 citation statements)

References 48 publications

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“…), textural characteristics present in the high spatial resolution UAS imagery may help distinguish between the two classes and improve mapping confidence in comparison to other remote sensing platforms (Bryson et al., ; Nahirnick et al. in press; Fig. A and B).…”

Section: Discussionmentioning

confidence: 98%

“…; Nahirnick et al. in press). Our results indicated that optimal cloud cover conditions are either very low (<10%) or very high (>90%) (Table ), which provides consistent reflectance and radiometry (Nahirnick et al.…”

Section: Discussionmentioning

confidence: 98%

“…; Nahirnick et al. in press). Because image interpretation can be difficult in areas with sparse eelgrass, where eelgrass is intermixed with other macroalgae, or in areas of subtidal eelgrass, data from towed underwater video were used to aid image interpretation.…”

Section: Methodsmentioning

confidence: 98%

“…However, the application of UAS for mapping and monitoring submerged aquatic vegetation (SAV) has been limited by the challenges associated with the water overlying target benthic features and the environmental conditions at the time of image acquisition (Nahirnick et al. in press). As such, most research has been confined to clear shallow tropical waters (Ventura et al.…”

Section: Introductionmentioning

confidence: 99%

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Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS)

Nahirnick

Reshitnyk

Campbell

et al. 2018

Remote Sens Ecol Conserv

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There is growing interest in the use of Unoccupied Aerial Systems (UAS) for mapping and monitoring of seagrass habitats. UAS provide flexibility with timing of imagery capture, are relatively inexpensive, and obtain very high spatial resolution imagery compared to imagery acquired from sensors mounted on satellite or piloted aircraft. However, research to date has focused on UAS applications for exposed intertidal areas or clear tropical waters. In contrast, submerged seagrass meadows in temperate regions are subject to high cloud cover and water column turbidity, which may limit the application of UAS imagery for coastal habitat mapping. To test the constraints on UAS seagrass mapping, we examined the effects of five environmental conditions at the time of UAS image acquisition (sun angle, tidal height, cloud cover, Secchi depth and wind speed) and five site characteristics (eelgrass patchiness and density, presence and density of non‐eelgrass submerged aquatic vegetation, sediment tone, eelgrass deep edge and site exposure) at 26 eelgrass (Zostera marina) monitoring sites in British Columbia, Canada. Eelgrass was delineated in UAS orthomosaics using object‐based image analysis, combining image segmentation with manual classification. Each site was ranked according to the analysts’ confidence in the delineated eelgrass. Robust Linear Regression revealed sun angle and ‘theoretical visibility’ (an aggregate of tidal height, Secchi depth, and eelgrass deep edge conditions) to be the most important variables affecting mapping confidence. In general, ideal environmental conditions to obtain high confidence eelgrass mapping included: (1) sun angles below 40°; (2) positive theoretical visibility with Secchi depths >5 m; (3) cloud cover conditions of <10% or >90%; and (4) wind speeds less than 5 km h−1. Additionally, high mapping confidence was achieved for sites with dense, continuous, and homogeneous eelgrass meadows. The results of this analysis will guide implementation of UAS mapping technologies in coastal temperate regions.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 98%

Section: Methodsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS)

Nahirnick

Reshitnyk

Campbell

et al. 2018

Remote Sens Ecol Conserv

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“…A flight plan at high altitudes (above 100 m) is recommended to both avoid obstacles (such as trees, power lines, and bridges) and assist in the image stitching process in order to create orthomosaic maps of large swaths of the river. When generating orthomosaics, researchers should use real-time kinematic GPS, or have ground control points, secured markers or landmarks with known GPS locations, or slivers of land in the images to facilitate image stitching [40,107,108]. When target algal or macrophyte patches are identifiable at large spatial scales, or when higher spectral resolution is required to discern among taxa, high-resolution satellite imagery can be an alternative to UAV imagery [109].…”

Section: Recommendationsmentioning

confidence: 99%

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

et al. 2020

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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.

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Novel approach to large‐scale monitoring of submerged aquatic vegetation: A nationwide example from Sweden

Huber

Hansen

Nielsen

et al. 2021

Integr Envir Assess & Manag

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This article is part of the special series "The Future of Marine Environmental Monitoring and Planning." The series will take a sneak peek into the future of marine monitoring where integration of new monitoring technologies with advanced ecosystem modeling will make it possible to estimate real-time ecosystem status, improve model precision, and provide a robust basis for marine environmental assessments.

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Benefits and Challenges of UAS Imagery for Eelgrass (Zostera marina) Mapping in Small Estuaries of the Canadian West Coast

Cited by 18 publications

References 48 publications

Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS)

Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS)

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

Novel approach to large‐scale monitoring of submerged aquatic vegetation: A nationwide example from Sweden

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