Unmanned aerial system based spectroradiometer for monitoring harmful algal blooms: A new paradigm in water quality monitoring

Becker, R. H.; Sayers, Michael J.; Dehm, Dustin; Shuchman, Robert A.; Quintero, Kaydian; Bosse, Karl R.; Sawtell, Reid W.

doi:10.1016/j.jglr.2019.03.006

Cited by 65 publications

(41 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3, except that the LPR could be mounted on a UAS platform for obtaining airborne spectral data. Recent work has shown that spectra collected with the LPR compared well to ASD data, 44 with linear relationships with R 2 ¼ 0.941 to 0.992 between ASD and LPR-derived spectra over the same locations. To enable the collection of boatside spectra that would be comparable to the UAS-based spectra, these were both collected at nadir to provide a similarly shaped circular footprint.…”

Section: Sensing Designmentioning

confidence: 91%

Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection

Brooks

Grimm

Marcarelli

et al. 2019

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection," J.Abstract. The ability to differentiate a non-native aquatic plant, Myriophyllum spicatum (Eurasian watermilfoil or EWM), from other submerged aquatic vegetation (SAV) using spectral data collected at multiple scales was investigated as a precursor to mapping of EWM. Spectral data were collected using spectroradiometers for SAV taken out of the water, from the side of a boat directly over areas of SAV and from a lightweight portable radiometer system flown from an unmanned aerial system (UAS). EWM was spectrally different from other SAV when using 651 spectral bands collected in ultraviolet to near-infrared range of 350 to 1000 nm but does not provide a practical system for EWM mapping because this exceeds the capabilities of available airborne hyperspectral imaging systems. Using only six spectral bands corresponding to an available multispectral camera or eight wetlands-centric bands did not reliably differentiate EWM from other SAV and assemblages. However, a modified version of the normalized difference vegetation index (mNDVI), using a ratio of red-edge to red light, was significantly different among dominant vegetation groups. Also, averaging the full range of spectral to 65 10-nm wide bands, similar to available hyperspectral imaging systems, provided the ability to identify EWM separately from other SAV. The UAS-collected spectral data had the lowest remote sensing reflectance versus the out-of-water and boatside data, emphasizing the need to collect optimized data. The spectral data collected for this study support that with relatively clear and calm water, hyperspectral data, and mNDVI, it is likely that UASbased imaging can help with mapping and monitoring of EWM. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

show abstract

Section: Sensing Designmentioning

confidence: 91%

Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection

Brooks

Grimm

Marcarelli

et al. 2019

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

show abstract

“…Random Forest algorithms have proven successful in previous studies in complex, heterogeneous landscapes [19,85,86], demonstrating that this method can effectively reduce speckle and noise within imagery. To build on current work, future image analysis techniques that can be applied to benthic surveys in heterogeneous environments include aquatic vegetation indices, OBIA, structure from motion photogrammetry, and hyperspectral image capture [20,40,41,[86][87][88][89].…”

Section: Uav Monitoring Of Benthic Primary Producersmentioning

confidence: 99%

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

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

“…Satellite remote sensing has been used to roughly estimate TSS concentrations, however, it requires long-term in situ TSS measurements and has coarse spatial resolution that can only be applied to coastal areas, oceans, large rivers or large lakes [18,19]. Satellite remote sensing for water quality purposes also fails to address the inherent variability within a low-resolution pixel due to various factors, such as unsteady flows, sediment transport dynamics and wind influence [20]. Capturing images from a fixed camera would prove to be difficult and cumbersome for several reasons.…”

Section: Introductionmentioning

confidence: 99%

Measuring High Levels of Total Suspended Solids and Turbidity Using Small Unoccupied Aerial Systems (sUAS) Multispectral Imagery

Prior

O'Donnell

Brodbeck

et al. 2020

Drones

View full text Add to dashboard Cite

Due to land development, high concentrations of suspended sediment are produced from erosion after rain events. Sediment basins are commonly used for the settlement of suspended sediments before discharge. Stormwater regulations may require frequent sampling and monitoring of these basins, both of which are time and labor intensive. Potential remedies are small, unoccupied aerial systems (sUAS). The goal of this study was to demonstrate whether sUAS multispectral imagery could measure high levels of total suspended solids (TSS) and turbidity in a sediment basin. The sediment basin at the Auburn University Erosion and Sediment Control Testing Facility was used to simulate a local 2-year, 24-h storm event with a 30-min flow rate. Water samples were collected at three depths in two locations every 15 min for six hours with corresponding sUAS multispectral imagery. Multispectral pixel values were related to TSS and turbidity in separate models using multiple linear regressions. TSS and turbidity regression models had coefficients of determination (r2) values of 0.926 and 0.851, respectively. When water column measurements were averaged, the r2 values increased to 0.965 and 0.929, respectively. The results indicated that sUAS multispectral imagery is a viable option for monitoring and assessing sediment basins during high-concentration events.

show abstract

Unmanned aerial system based spectroradiometer for monitoring harmful algal blooms: A new paradigm in water quality monitoring

Cited by 65 publications

References 40 publications

Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection

Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection

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

Measuring High Levels of Total Suspended Solids and Turbidity Using Small Unoccupied Aerial Systems (sUAS) Multispectral Imagery

Contact Info

Product

Resources

About