Seagrass Restoration Is Possible: Insights and Lessons From Australia and New Zealand

Frontiers in Marine Science, Journal Year: 2020, Volume and Issue: 7

Published: Aug. 14, 2020

Seagrasses are important marine ecosystems situated throughout the world's coastlines. They facing declines around world due to global and local threats such as rising ocean temperatures, coastal development pollution from sewage outfalls agriculture. Efforts have been made reduce seagrass loss through reducing regional stressors, active restoration. Seagrass restoration is rapidly maturing but improved practices needed enhance success of future programs. Major gaps in knowledge remain, especially our understanding how restore tropical species Australia. Prior research efforts provided valuable insights into factors influencing outcomes there now several examples successful large-scale A variety tools techniques recently developed that will improve efficiency, cost effectiveness, scalability This review describes emerging for restoration, key considerations programs, highlights benefits increased collaboration, Traditional Owner (First Nation) stakeholder engagement. Combined, these lessons approaches show possible should be directed at upscaling future. critical conservation this ecosystem ecological communities they support.

Language: Английский

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Ultra-High-Resolution Mapping of Posidonia oceanica (L.) Delile Meadows through Acoustic, Optical Data and Object-based Image Classification

Journal of Marine Science and Engineering, Journal Year: 2020, Volume and Issue: 8(9), P. 647 - 647

Published: Aug. 22, 2020

In this study, we present a framework for seagrass habitat mapping in shallow (5–50 m) and very water (0–5 by combining acoustic, optical data Object-based Image classification. The combination of satellite multispectral images-acquired from 2017 to 2019, together with Unmanned Aerial Vehicle (UAV) photomosaic maps, high-resolution multibeam bathymetry/backscatter underwater photogrammetry data, provided insights on the short-term characterization distribution Posidonia oceanica (L.) Delile, 1813 meadows Calabrian Tyrrhenian Sea. We used supervised Analysis (OBIA) processing classification technique create thematic map P. bathymetry, backscatter drone images that can be as model marine coastal areas. As part work, within SIC CARLIT project, field application was carried out Site Community Importance (SCI) Cirella Island Calabria (Italy); different multiscale techniques have been performed integrated: acoustic were processed classified OBIA algorithms, i.e., k-Nearest Neighbors’ algorithm (k-NN), Random Tree (RT) Decision (DT). These combinations shown reliable tool obtain maps preliminary habitats. time-lapse comparisons aimed quantify changes seabed coverage, such those caused anthropogenic impacts (e.g., trawl fishing activities boat anchoring) assess blue carbon sinks might useful future habitats conservation strategies.

Language: Английский

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Semantic segmentation of seagrass habitat from drone imagery based on deep learning: A comparative study

Ecological Informatics, Journal Year: 2021, Volume and Issue: 66, P. 101430 - 101430

Published: Sept. 21, 2021

Language: Английский

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Unmanned Aerial Vehicles (UAVs) for Monitoring Macroalgal Biodiversity: Comparison of RGB and Multispectral Imaging Sensors for Biodiversity Assessments

Remote Sensing, Journal Year: 2019, Volume and Issue: 11(19), P. 2332 - 2332

Published: Oct. 8, 2019

Developments in the capabilities and affordability of unmanned aerial vehicles (UAVs) have led to an explosion their use for a range ecological agricultural remote sensing applications. However, ubiquity visible light cameras aboard readily available UAVs may be limiting application these devices fine-scale, high taxonomic resolution monitoring. Here we compare RGB multispectral deployed assessing intertidal shallow subtidal marine macroalgae resolution. Our results show that diverse spectral profiles naturally lend themselves habitat classification. Furthermore, biodiversity assessments, particularly habitats, are enhanced using six-band discrete wavelength sensors (81% accuracy, Cohen’s Kappa) compared three-band broad channel (79% 10 classes. Combining band signals narrow further improved accuracy classification with combined 90% (Cohen’s Kappa). Despite notable improvements imaging, were highly capable rivaled classifying habitats. High spatial scale monitoring turbid exposed rocky reefs presents unique set challenges, but limitations more traditional methods can overcome by targeting ideal conditions UAVs.

Language: Английский

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Passive remote sensing technology for mapping bull kelp (Nereocystis luetkeana): A review of techniques and regional case study

Global Ecology and Conservation, Journal Year: 2019, Volume and Issue: 19, P. e00683 - e00683

Published: June 15, 2019

The distribution and abundance of the canopy-forming kelp Nereocystis luetkeana is increasing concern for environmental management conservation in coastal regions due to its importance as a foundation species. Mapping forests aids understanding their health, productivity, response conditions. Remote sensing using satellites an increasingly accessible tool mapping nearshore habitats allowing applications such long-term monitoring large- small-scale surveys. This paper provides review passive optical remote techniques detection floating macro-algae, adapts these detecting luetkeana, demonstrating application through comprehensive case study, from imagery acquisition map validation. with associated study communicates non-remote experts road use technology habitats.

Language: Английский

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Using a UAV-Mounted Multispectral Camera for the Monitoring of Marine Macrophytes

Frontiers in Marine Science, Journal Year: 2021, Volume and Issue: 8

Published: Sept. 3, 2021

Marine macrophytes constitute one of the most productive ecosystems on planet, as well threatened by anthropogenic activities and climate change. Their monitoring is therefore essential, which has experienced a fast methodological evolution in recent years, from traditional situ sampling to use satellite remote sensing, subsequently sensors mounted unmanned aerial vehicles (UAV). This study aims advance these through UAV equipped with 10-band multispectral camera, using different algorithms [i.e., maximum likelihood classifier (MLC), minimum distance (MDC), spectral angle (SAC)], Bay Cádiz Natural Park (southern Spain) case study. The results obtained MLC confirm suitability this technique for detecting differentiating seagrass meadows range 0–2 m depth efficiency tool studying marine coastal areas. We inferred existence cover 25452 2 Cymodocea nodosa , macroalgae species such Caulerpa prolifera covering 22172 Santibañez (inner Cádiz).

Language: Английский

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Using Unoccupied Aerial Vehicles (UAVs) to Map Seagrass Cover from Sentinel-2 Imagery

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(3), P. 477 - 477

Published: Jan. 20, 2022

Seagrass habitats are ecologically valuable and play an important role in sequestering storing carbon. There is, thus, a need to estimate seagrass percentage cover diverse environments support of climate change mitigation, marine spatial planning coastal zone management. In situ approaches accurate but time-consuming, expensive may not represent the larger units collected by satellite imaging. Hence, there is for consistent methodology that uses point-based field surveys deliver high-quality mapping at large scales. Here, we develop three-step approach combines (quadrats), aerial (unoccupied vehicle—UAV) data map Turneffe Atoll, Belize, largest atoll northern hemisphere. First, optical bands four UAV images were used calculate cover, combination with data. The calculated from was then training validation datasets Sentinel-2 pixels. Next, non-seagrass areas identified removed object-based classification, followed pixel-based regression cover. Using this approach, mapped using UAVs (R2 = 0.91 between observed distributions) 0.73). This work provides first openly available explorable across where approximately 242 km2 above 10% located. We offers 30 times more than traditional methods, therefore presenting substantial reduction cost-per-point Furthermore, increase helps map, suitable resolving trends deteriorating, stable or recovering 10 m2 resolution underpin evidence-based management conservation seagrass.

Language: Английский

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Drone-Based Characterization of Seagrass Habitats in the Tropical Waters of Zanzibar

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(3), P. 680 - 680

Published: Jan. 31, 2022

Unmanned automatic systems (UAS) are increasingly being applied as an alternative to more costly time-consuming traditional methods for mapping and monitoring marine shallow-water ecosystems. Here, we demonstrate the utility of combining aerial drones with in situ imagery characterize habitat conditions nine seagrass-dominated areas on Unguja Island, Zanzibar. We object-based image analysis a maximum likelihood algorithm drone images derive cover maps important seagrass parameters: composition; species; horizontal- depth-percent covers, seascape fragmentation. mapped sites covering 724 ha, categorized into seagrasses (55%), bare sediment (31%), corals (9%), macroalgae (5%). An average six species were found, 20% “dense cover” (40–70%). achieved high map accuracy types (87%), (80%), (76%). In all sites, observed clear decreases covers depths ranging from 30% at 1–2 m, 1.6% 4–5 m depth. The depth dependency varied significantly among species. Areas associated low also had fragmented distribution pattern, scattered populations. was correlated negatively (r2 = 0.9, p < 0.01) sea urchins. A multivariate similarity (ANOSIM) biotic features, derived data, suggested that could be organized three different coastal types. This study demonstrates robustness characterizing complex tropical waters. recommend adopting drones, combined photos, establishing suite data relevant ecosystem Western Indian Ocean (WIO).

Language: Английский

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A Multi-Satellite Mapping Framework for Floating Kelp Forests

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(5), P. 1276 - 1276

Published: Feb. 25, 2023

Kelp forests provide key habitat on the Pacific Coast of Canada; however, long-term changes in their distribution and abundance remain poorly understood. With advances satellite technology, floating kelp can now be monitored across large-scale areas. We present a methodological framework using an object-based image analysis approach that enables combination imagery from multiple satellites at different spatial resolutions temporal coverage, to map with canopy through time. The comprises four steps: (1) compilation quality assessment; (2) preprocessing; (3) object-oriented classification; (4) accuracy assessment. Additionally, impact resolution detectability is described. Overall, this workflow was successful producing accurate maps forests, global scores between 88% 94%. When comparing detectability, lower were less reliable detecting small high slope Based analysis, we suggest removing areas (11.4%) time series analyses high- medium-resolution error, case up 7%, considered when low–mid

Language: Английский

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Location optimization of unmanned aerial vehicle (UAV) drone port for coastal zone management: The case of Guangdong coastal zone in China

Ocean & Coastal Management, Journal Year: 2025, Volume and Issue: 262, P. 107576 - 107576

Published: Feb. 12, 2025

Language: Английский

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