Water Quality Properties Derived from VIIRS Measurements in the Great Lakes

Refined empirical algorithms for chlorophyll-a (Chl-a) concentration, using the maximum ratio of normalized water-leaving radiance <i>nL<sub>w</sub></i>(<i>λ</i>) at the blue and green bands, and Secchi depth (SD) from <i>nL<sub>w</sub></i>...

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Main Authors: Seunghyun Son, Menghua Wang
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/10/1605
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spelling doaj-a12c7a30a910458d9b5ee86fbfc5373f2020-11-25T02:04:05ZengMDPI AGRemote Sensing2072-42922020-05-01121605160510.3390/rs12101605Water Quality Properties Derived from VIIRS Measurements in the Great LakesSeunghyun Son0Menghua Wang1National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E/RA3, 5830 University Research Court, College Park, MD 20740, USANational Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E/RA3, 5830 University Research Court, College Park, MD 20740, USARefined empirical algorithms for chlorophyll-a (Chl-a) concentration, using the maximum ratio of normalized water-leaving radiance <i>nL<sub>w</sub></i>(<i>λ</i>) at the blue and green bands, and Secchi depth (SD) from <i>nL<sub>w</sub></i>(<i>λ</i>) at 551 nm, <i>nL</i><sub>w</sub>(551), are proposed for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite in the Great Lakes. We demonstrated that water quality properties and phytoplankton production can be successfully monitored and assessed using the new regional Chl-a and SD algorithms, with reasonably accurate estimates of Chl-a and SD from the VIIRS-SNPP ocean color data in the Great Lakes. VIIRS-derived Chl-a and SD products using the proposed algorithms provide the temporal and spatial variabilities in the Great Lakes. Overall, Chl-a concentrations are generally low in lakes Michigan and Huron, while Chl-a data are highest in Lake Erie. The seasonal pattern shows that overall low Chl-a concentrations appear in winter and high values in June to September in the lakes. The distribution of SD in the Great Lakes is spatially and temporally different from that of Chl-a. The SD data are generally lower in summer and higher in winter in most of the Great Lakes. However, the highest SD in Lake Erie appears in summer, and lower values in winter. Significantly high values in Chl-a, and lower values in SD, in the nearshore regions, such as Thunder Bay, Saginaw Bay, and Whitefish Bay, can be related to the very shallow bathymetry and freshwater inputs from the land. The time series of VIIRS-derived Chl-a and SD data provide strong interannual variability in most of the Great Lakes.https://www.mdpi.com/2072-4292/12/10/1605Great Lakesremote sensingocean colorchlorophyll-aSecchi depthwater quality
collection DOAJ
language English
format Article
sources DOAJ
author Seunghyun Son
Menghua Wang
spellingShingle Seunghyun Son
Menghua Wang
Water Quality Properties Derived from VIIRS Measurements in the Great Lakes
Remote Sensing
Great Lakes
remote sensing
ocean color
chlorophyll-a
Secchi depth
water quality
author_facet Seunghyun Son
Menghua Wang
author_sort Seunghyun Son
title Water Quality Properties Derived from VIIRS Measurements in the Great Lakes
title_short Water Quality Properties Derived from VIIRS Measurements in the Great Lakes
title_full Water Quality Properties Derived from VIIRS Measurements in the Great Lakes
title_fullStr Water Quality Properties Derived from VIIRS Measurements in the Great Lakes
title_full_unstemmed Water Quality Properties Derived from VIIRS Measurements in the Great Lakes
title_sort water quality properties derived from viirs measurements in the great lakes
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-05-01
description Refined empirical algorithms for chlorophyll-a (Chl-a) concentration, using the maximum ratio of normalized water-leaving radiance <i>nL<sub>w</sub></i>(<i>λ</i>) at the blue and green bands, and Secchi depth (SD) from <i>nL<sub>w</sub></i>(<i>λ</i>) at 551 nm, <i>nL</i><sub>w</sub>(551), are proposed for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite in the Great Lakes. We demonstrated that water quality properties and phytoplankton production can be successfully monitored and assessed using the new regional Chl-a and SD algorithms, with reasonably accurate estimates of Chl-a and SD from the VIIRS-SNPP ocean color data in the Great Lakes. VIIRS-derived Chl-a and SD products using the proposed algorithms provide the temporal and spatial variabilities in the Great Lakes. Overall, Chl-a concentrations are generally low in lakes Michigan and Huron, while Chl-a data are highest in Lake Erie. The seasonal pattern shows that overall low Chl-a concentrations appear in winter and high values in June to September in the lakes. The distribution of SD in the Great Lakes is spatially and temporally different from that of Chl-a. The SD data are generally lower in summer and higher in winter in most of the Great Lakes. However, the highest SD in Lake Erie appears in summer, and lower values in winter. Significantly high values in Chl-a, and lower values in SD, in the nearshore regions, such as Thunder Bay, Saginaw Bay, and Whitefish Bay, can be related to the very shallow bathymetry and freshwater inputs from the land. The time series of VIIRS-derived Chl-a and SD data provide strong interannual variability in most of the Great Lakes.
topic Great Lakes
remote sensing
ocean color
chlorophyll-a
Secchi depth
water quality
url https://www.mdpi.com/2072-4292/12/10/1605
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