Victoria Stengel, Jessica M. Trevino, Tyler V. King, Scott D. Ducar, Stephen A. Hundt, Konrad C. Hafen, Christopher J. Churchill
{"title":"近实时卫星检测和监测水生藻类和蓝藻:如何将叶绿素 a 指数和水质采样相结合应用于得克萨斯州北部水库","authors":"Victoria Stengel, Jessica M. Trevino, Tyler V. King, Scott D. Ducar, Stephen A. Hundt, Konrad C. Hafen, Christopher J. Churchill","doi":"10.1117/1.JRS.17.044514","DOIUrl":null,"url":null,"abstract":"Abstract. Aquatic algae and cyanobacteria can impair water-quality and pose risks to human and animal health. Several metrics of in-situ water-quality, including chlorophyll-a, phycocyanin, turbidity, Secchi depth, phytoplankton taxonomy, and hyperspectral reflectance, were collected in coordination with Sentinel-2 satellite overpasses to ascertain water-quality conditions and calibrate satellite detection and estimation of chlorophyll-a concentration. The performance of multiple satellite chlorophyll-a detection indices was evaluated by comparing satellite imagery to field observations of chlorophyll-a concentrations. Seventeen chlorophyll-a spectral indices were implemented using the ACOLITE atmosphere correction; the top performing indices were selected for further evaluation using the Sen2Cor and MAIN atmosphere corrections. The Moses three-band spectral index delivered the strongest linear agreement with field measurements of chlorophyll-a concentration across all reservoir sampling sites (R2 = 0.70). Compared to open-water sites, the Moses three-band spectral index delivered better linear agreement with chlorophyll-a field measurements at inlet sites where there was a greater abundance of near surface aquatic chlorophyll-a concentrations, and the overall chlorophyll-a hyperspectral reflectance signal was stronger. Chlorophyll-a concentration estimates were implemented in a cloud-computation remote sensing platform designed for regional scale remote sensing analysis to map spatiotemporal patterns of aquatic chlorophyll-a across 10 study reservoirs located primarily in north Texas.","PeriodicalId":54879,"journal":{"name":"Journal of Applied Remote Sensing","volume":"37 1","pages":"044514 - 044514"},"PeriodicalIF":1.4000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Near real-time satellite detection and monitoring of aquatic algae and cyanobacteria: how a combination of chlorophyll-a indices and water-quality sampling was applied to north Texas reservoirs\",\"authors\":\"Victoria Stengel, Jessica M. Trevino, Tyler V. King, Scott D. Ducar, Stephen A. Hundt, Konrad C. Hafen, Christopher J. 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The Moses three-band spectral index delivered the strongest linear agreement with field measurements of chlorophyll-a concentration across all reservoir sampling sites (R2 = 0.70). Compared to open-water sites, the Moses three-band spectral index delivered better linear agreement with chlorophyll-a field measurements at inlet sites where there was a greater abundance of near surface aquatic chlorophyll-a concentrations, and the overall chlorophyll-a hyperspectral reflectance signal was stronger. 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Near real-time satellite detection and monitoring of aquatic algae and cyanobacteria: how a combination of chlorophyll-a indices and water-quality sampling was applied to north Texas reservoirs
Abstract. Aquatic algae and cyanobacteria can impair water-quality and pose risks to human and animal health. Several metrics of in-situ water-quality, including chlorophyll-a, phycocyanin, turbidity, Secchi depth, phytoplankton taxonomy, and hyperspectral reflectance, were collected in coordination with Sentinel-2 satellite overpasses to ascertain water-quality conditions and calibrate satellite detection and estimation of chlorophyll-a concentration. The performance of multiple satellite chlorophyll-a detection indices was evaluated by comparing satellite imagery to field observations of chlorophyll-a concentrations. Seventeen chlorophyll-a spectral indices were implemented using the ACOLITE atmosphere correction; the top performing indices were selected for further evaluation using the Sen2Cor and MAIN atmosphere corrections. The Moses three-band spectral index delivered the strongest linear agreement with field measurements of chlorophyll-a concentration across all reservoir sampling sites (R2 = 0.70). Compared to open-water sites, the Moses three-band spectral index delivered better linear agreement with chlorophyll-a field measurements at inlet sites where there was a greater abundance of near surface aquatic chlorophyll-a concentrations, and the overall chlorophyll-a hyperspectral reflectance signal was stronger. Chlorophyll-a concentration estimates were implemented in a cloud-computation remote sensing platform designed for regional scale remote sensing analysis to map spatiotemporal patterns of aquatic chlorophyll-a across 10 study reservoirs located primarily in north Texas.
期刊介绍:
The Journal of Applied Remote Sensing is a peer-reviewed journal that optimizes the communication of concepts, information, and progress among the remote sensing community.