Effect of Time Window on Satellite and Ground-Based Data for Estimating Chlorophyll-a in Reservoirs

Algal blooms in freshwater ecosystems can negatively impact aquatic and human health. Satellite remote sensing of chlorophyll a (Chl-a) is often used to help determine the severity of algal blooms. However, satellite revisit flyover schedules may not match the erratic nature of algal blooms. Studies...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-02, Vol.14 (4), p.846
Main Authors: Kayastha, Priya, Dzialowski, Andrew R., Stoodley, Scott H., Wagner, Kevin L., Mansaray, Abubakarr S.
Format: Article
Language:English
Subjects:
Algae
Algal blooms
Algorithms
Aquatic ecosystems
Chlorophyll
chlorophyll-a
Cyanobacteria
Daytime
Eutrophication
Flyovers
Freshwater ecosystems
ground-based data
Laboratories
Landsat
Landsat satellites
Multiple regression models
Optical properties
Regression analysis
Remote sensing
reservoir
Reservoirs
resolution
satellite data
Satellites
Schedules
Statistical analysis
time window
Water quality
Watersheds
Windows (intervals)
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Summary:Algal blooms in freshwater ecosystems can negatively impact aquatic and human health. Satellite remote sensing of chlorophyll a (Chl-a) is often used to help determine the severity of algal blooms. However, satellite revisit flyover schedules may not match the erratic nature of algal blooms. Studies have paired satellite and ground-based data that were not collected on the same day, assuming Chl-a concentrations did not change significantly by the flyover date. We determined the effects of an increasing time window between satellite overpass dates and field-based collection of Chl-a on algorithms for Landsat 5, Landsat 8, and Sentinel-2, using 14 years (2006–2020) of Chl-a data from 10 Oklahoma reservoirs. Multiple regression models were built, and selected statistics were used to rank the time windows. The Sentinel-2 results showed strong relationships between Chl-a and satellite data collected up to a ±5-day window. The strength of these relationships decreased beyond a ±3-day time window for Landsat 8 and a ±1-day time window for Landsat 5. Our results suggest that the time window between field sampling and satellite overpass can impact the use of satellite data for Chl-a monitoring in reservoirs. Furthermore, longer time windows can be used with higher resolution (spatial, spectral) satellites.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14040846