Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used...

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Autores principales:	Megan M. Coffer, Blake A. Schaeffer, Wilson B. Salls, Erin Urquhart, Keith A. Loftin, Richard P. Stumpf, P. Jeremy Werdell, John A. Darling
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Satellite remote sensing Cyanobacteria Inland waters Water quality Clustering analysis Indicator Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/2584a1e91cd9425f809b806665dcdc10
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spelling	oai:doaj.org-article:2584a1e91cd9425f809b806665dcdc102021-12-01T04:54:00ZSatellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales1470-160X10.1016/j.ecolind.2021.107822https://doaj.org/article/2584a1e91cd9425f809b806665dcdc102021-09-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21004878https://doaj.org/toc/1470-160XCyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.Megan M. CofferBlake A. SchaefferWilson B. SallsErin UrquhartKeith A. LoftinRichard P. StumpfP. Jeremy WerdellJohn A. DarlingElsevierarticleSatellite remote sensingCyanobacteriaInland watersWater qualityClustering analysisIndicatorEcologyQH540-549.5ENEcological Indicators, Vol 128, Iss , Pp 107822- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Satellite remote sensing Cyanobacteria Inland waters Water quality Clustering analysis Indicator Ecology QH540-549.5
spellingShingle	Satellite remote sensing Cyanobacteria Inland waters Water quality Clustering analysis Indicator Ecology QH540-549.5 Megan M. Coffer Blake A. Schaeffer Wilson B. Salls Erin Urquhart Keith A. Loftin Richard P. Stumpf P. Jeremy Werdell John A. Darling Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales
description	Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.
format	article
author	Megan M. Coffer Blake A. Schaeffer Wilson B. Salls Erin Urquhart Keith A. Loftin Richard P. Stumpf P. Jeremy Werdell John A. Darling
author_facet	Megan M. Coffer Blake A. Schaeffer Wilson B. Salls Erin Urquhart Keith A. Loftin Richard P. Stumpf P. Jeremy Werdell John A. Darling
author_sort	Megan M. Coffer
title	Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales
title_short	Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales
title_full	Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales
title_fullStr	Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales
title_full_unstemmed	Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales
title_sort	satellite remote sensing to assess cyanobacterial bloom frequency across the united states at multiple spatial scales
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/2584a1e91cd9425f809b806665dcdc10
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Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales

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