has been cited by the following article(s):
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[1]
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Chromaticity-Based Discrimination of Algal Bloom from Inland and Coastal Waters Using In Situ Hyperspectral Remote Sensing Reflectance
Water,
2024
DOI:10.3390/w16162276
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[2]
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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
Journal of Applied Remote Sensing,
2023
DOI:10.1117/1.JRS.17.044514
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[3]
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Mapping Benthic Algae and Cyanobacteria in River Channels from Aerial Photographs and Satellite Images: A Proof-of-Concept Investigation on the Buffalo National River, AR, USA
Remote Sensing,
2022
DOI:10.3390/rs14040953
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[4]
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Mapping Benthic Algae and Cyanobacteria in River Channels from Aerial Photographs and Satellite Images: A Proof-of-Concept Investigation on the Buffalo National River, AR, USA
Remote Sensing,
2022
DOI:10.3390/rs14040953
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[5]
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Monitoring PHB production in Synechocystis sp. with hyperspectral images
Water Science and Technology,
2022
DOI:10.2166/wst.2022.194
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[6]
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Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data
Remote Sensing of Environment,
2022
DOI:10.1016/j.rse.2022.113089
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