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Investigating small unoccupied aerial systems (sUAS) multispectral imagery for total suspended solids and turbidity monitoring in small streams

Authors :
Prior, Elizabeth M.
O'Donnell, Frances C.
Brodbeck, Christian
Runion, G. Brett
Shepherd, Stephanie L.
Prior, Elizabeth M.
O'Donnell, Frances C.
Brodbeck, Christian
Runion, G. Brett
Shepherd, Stephanie L.
Publication Year :
2021

Abstract

Small unoccupied aerial systems (sUAS) are increasingly used for field data collection and remote sensing purposes. Their ease of use, ability to carry sensors, low cost, precise manoeuvrability and navigation makes them versatile tools. The goal of this study is to investigate if sUAS multispectral imagery can be utilized to measure turbidity and total suspended solids (TSS) of small streams. sUAS multispectral imagery and water samples at varying depths were collected before and after rain events on three sampling dates in 2019 from Moores Creek in Lanett, Alabama (AL), United States of America (USA), which was restored in 2017. The water samples were processed for TSS and turbidity and related to pixel values from the multispectral imagery. Linear regression was used to develop models for TSS and turbidity. The models were then tested on Moores Mill Creek in Chewacla State Park, AL, USA. For Lanett, TSS and turbidity regression models for low flows had coefficients of determination (R-2) values of 0.77 and 0.78, respectively. During high flows, different single bands and band ratios were required for comparableR(2)values, suggesting separate models may be needed for high and low flow events. When the Lanett models were applied to Chewacla State Park, predicted TSS and turbidity were not comparable to measured values indicating that location-specific models may be required. Future research should incorporate depth as a variable since streambed visibility likely impacts results, along with other modelling and data analysis methods, such as machine learning.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1245741682
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1080.01431161.2020.1798546