The Glacial Meltwater Turbidity Algorithm (GaMTA): Adaptation of single-band algorithm retrieving turbidity to satellite and UAV dataset from highly glaciated Antarctic region

Wójcik-Długoborska, Kornelia Anna; Bialik, Robert J.

doi:10.1016/j.rsma.2022.102798

Cited by 3 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Plumes, naturally generated or invoked by human activity, have been studied by multiple researchers for many years. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] Johansen et al released two different dyes in a Red Sea location to study coastal water flow dynamics. The group tracked the dye plumes with an unmanned aerial vehicle (UAV) and high spatial-resolution SkySat satellite imagery using object detection, region growing, and AI methods.…”

Section: Introductionmentioning

confidence: 99%

“…Among different researchers' work on glacial water plumes, Wójcik et al 14 utilized multispectral sensor data from a UAV and adapted a single-band algorithm to estimate turbidity and then compared it to satellite and UAV imagery in glacial locations. 15 This study investigates the spread of the plume and the plume speed using UAV imagery and video from a single campaign lasting over 20 min. UAV video and single-frame imagery were analyzed to estimate the plume spread and speed over the seagrass beds, influenced by the wind and outgoing tide.…”

Section: Introductionmentioning

confidence: 99%

“…Plumes, naturally generated or invoked by human activity, have been studied by multiple researchers for many years 1 – 19 Johansen et al. released two different dyes in a Red Sea location to study coastal water flow dynamics.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Plume motion characterization in unmanned aerial vehicle aerial video and imagery

Mehrubeoglu,

Cammarata,

Zhang

et al. 2024

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

Sediment plumes are generated from both natural and human activities in benthic environments, increasing the turbidity of the water and reducing the amount of sunlight reaching the benthic vegetation. Seagrasses, which are photosynthetic bioindicators of their environment, are threatened by chronic reductions in sunlight, impacting entire aquatic food chains. Our research uses unmanned aerial vehicle (UAV) aerial video and imagery to investigate the characteristics of sediment plumes generated by a model of anthropogenic disturbance. The extent, speed, and motion of the plumes were assessed as these parameters may pertain to the potential impacts of plume turbidity on seagrass communities. In a case study using UAV video, the turbidity plume was observed to spread more than 200 ft over 20 min of the UAV campaign. The directional speed of the plume was estimated to be between 10.4 and 10.6 ft/min. This was corroborated by observation of the greatest plume turbidity and sediment load near the location of the disturbance and diminishing with distance. Further temporal studies are necessary to determine any longterm impacts of human activity-generated sediment plumes on seagrass beds.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Plume motion characterization in unmanned aerial vehicle aerial video and imagery

Mehrubeoglu,

Cammarata,

Zhang

et al. 2024

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

show abstract

“…Plume, naturally generated or invoked by human activity, have been studied by multiple researchers for many years [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] . Johansen et al released two different dyes in a Red Sea location to study coastal water flow dynamics.…”

Section: Introductionmentioning

confidence: 99%

“…Yang et al simulated interactions between a moving plate and sediment plume 12 whereas Iles explored sediment plume motion and evolution in MODIS satellite imagery 13 . Among different researchers' work on glacial water plumes, Wójcik et al utilized multispectral sensor data from a UAV 14 , and adapted a single-band algorithm to estimate turbidity and compare to satellite and UAV imagery in glacial locations 15 .…”

Section: Introductionmentioning

confidence: 99%

Plume motion characterization in UAV aerial video and imagery

Mehrübeoğlu

Cammarata

Zhang

et al. 2023

Real-Time Image Processing and Deep Learning 2023

View full text Add to dashboard Cite

Sediment plumes are generated from both natural and human activities in benthic environments, increasing the turbidity of the water and reducing the amount of sunlight reaching the benthic vegetation. Seagrasses, which are photosynthetic bioindicators of their environment, are threatened by chronic reductions in sunlight, impacting entire aquatic food chains. This research uses UAV aerial video and imagery to investigate the characteristics of sediment plumes generated by a model of anthropogenic disturbance. The extent, speed and motion of the plumes were assessed as these parameters may pertain to the potential impacts of plume turbidity on seagrass communities. In a case study using UAV video, the turbidity plume was observed to spread over 250 feet over 20 minutes of the UAV campaign. The directional speed of the plume was estimated to be between 10.4 and 10.6 ft/min. This was corroborated by observation of greatest plume turbidity and sediment load near the location of disturbance and diminishing with distance. Further temporal studies are necessary to determine long-term, if any, impacts of human activity-generated sediment plumes on seagrass beds.

show abstract

Suspended Sediment Concentration Estimation along Turbid Water Outflow Using a Multispectral Camera on an Unmanned Aerial Vehicle

Lee,

Baek,

Shin

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Optical remote sensing using unmanned aerial vehicles (UAVs) is proposed to monitor changes in marine environments effectively. Optical measurements were performed using a UAV multispectral camera (RedEdge, five spectral wavelengths of 475, 560, 668, 717, and 842 nm) with high spatial (5 cm) and temporal (1 s) resolutions to monitor the rapidly changing suspended sediment concentration (SSC) in the Saemangeum coastal area on the western coast of Korea. To develop the SSC algorithm, optical field, and water sample measurements were obtained from outside (11 stations) and inside (three stations) regions separated by a seawall, accounting for 100 measurements from 2018 to 2020. Accordingly, the remote sensing reflectance (Rrs) was estimated at each sampling station and used to develop the SSC algorithm based on multiple linear regression. The algorithm reasonably estimated the SSC with an R2 and root mean square error of 0.83 and 4.27 (mg L−1), respectively. Continuous individual UAV measurements over the coastal area of Saemangeum were combined to generate a wider SSC map. For the UAV observational data, the atmospheric influence at each altitude was reduced to the surface altitude level using a relative atmospheric correction technique. The SSC map enabled front monitoring of SSC fluctuations caused by discharge water due to the sluice gate opening. These results demonstrated the usability of the UAV-based SSC algorithm and confirmed the possibility of monitoring rapid SSC fluctuations.

show abstract

The Glacial Meltwater Turbidity Algorithm (GaMTA): Adaptation of single-band algorithm retrieving turbidity to satellite and UAV dataset from highly glaciated Antarctic region

Cited by 3 publications

References 21 publications

Plume motion characterization in unmanned aerial vehicle aerial video and imagery

Plume motion characterization in unmanned aerial vehicle aerial video and imagery

Plume motion characterization in UAV aerial video and imagery

Suspended Sediment Concentration Estimation along Turbid Water Outflow Using a Multispectral Camera on an Unmanned Aerial Vehicle

Contact Info

Product

Resources

About