Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review
Remote sensing (RS) has been widely used to monitor cyanobacterial blooms in inland water bodies. However, the accuracy of RS-based monitoring varies significantly depending on factors such as waterbody type, sensor characteristics, and analytical methods. This study comprehensively evaluates the cu...
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MDPI AG
2025-03-01
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| author | Jianyong Wu Yanni Cao Shuqi Wu Smita Parajuli Kaiguang Zhao Jiyoung Lee |
| author_facet | Jianyong Wu Yanni Cao Shuqi Wu Smita Parajuli Kaiguang Zhao Jiyoung Lee |
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| description | Remote sensing (RS) has been widely used to monitor cyanobacterial blooms in inland water bodies. However, the accuracy of RS-based monitoring varies significantly depending on factors such as waterbody type, sensor characteristics, and analytical methods. This study comprehensively evaluates the current capabilities and challenges of RS for cyanobacterial bloom monitoring, with a focus on achievable accuracy. We find that chlorophyll-a (Chl-a) and phycocyanin (PC) are the primary indicators used, with PC demonstrating greater accuracy and stability than Chl-a. Sentinel and Landsat satellites are the most frequently used RS data sources, while hyperspectral images, particularly from unmanned aerial vehicles (UAVs), have shown high accuracy in recent years. In contrast, the Medium-Resolution Imaging Spectrometer (MERIS) and Moderate-Resolution Imaging Spectroradiometer (MODIS) have exhibited lower performance. The choice of analytical methods is also essential for monitoring accuracy, with regression and machine learning models generally outperforming other approaches. Temporal analysis indicates a notable improvement in monitoring accuracy from 2021 to 2023, reflecting advances in RS technology and analytical techniques. Additionally, the findings suggest that a combined approach using Chl-a for large-scale preliminary screening, followed by PC for more precise detection, can enhance monitoring effectiveness. This integrated strategy, along with the careful selection of RS data sources and analytical models, is crucial for improving the accuracy and reliability of cyanobacterial bloom monitoring, ultimately contributing to better water management and public health protection. |
| format | Article |
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| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-03-01 |
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| spelling | doaj-art-70eb43293cbe494880d4cc942c8a72852025-08-20T02:06:13ZengMDPI AGRemote Sensing2072-42922025-03-0117591810.3390/rs17050918Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping ReviewJianyong Wu0Yanni Cao1Shuqi Wu2Smita Parajuli3Kaiguang Zhao4Jiyoung Lee5Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USADivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USADivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USADivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USASchool of Environment and Natural Resources, The Ohio State University, Columbus, OH 43210, USADivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USARemote sensing (RS) has been widely used to monitor cyanobacterial blooms in inland water bodies. However, the accuracy of RS-based monitoring varies significantly depending on factors such as waterbody type, sensor characteristics, and analytical methods. This study comprehensively evaluates the current capabilities and challenges of RS for cyanobacterial bloom monitoring, with a focus on achievable accuracy. We find that chlorophyll-a (Chl-a) and phycocyanin (PC) are the primary indicators used, with PC demonstrating greater accuracy and stability than Chl-a. Sentinel and Landsat satellites are the most frequently used RS data sources, while hyperspectral images, particularly from unmanned aerial vehicles (UAVs), have shown high accuracy in recent years. In contrast, the Medium-Resolution Imaging Spectrometer (MERIS) and Moderate-Resolution Imaging Spectroradiometer (MODIS) have exhibited lower performance. The choice of analytical methods is also essential for monitoring accuracy, with regression and machine learning models generally outperforming other approaches. Temporal analysis indicates a notable improvement in monitoring accuracy from 2021 to 2023, reflecting advances in RS technology and analytical techniques. Additionally, the findings suggest that a combined approach using Chl-a for large-scale preliminary screening, followed by PC for more precise detection, can enhance monitoring effectiveness. This integrated strategy, along with the careful selection of RS data sources and analytical models, is crucial for improving the accuracy and reliability of cyanobacterial bloom monitoring, ultimately contributing to better water management and public health protection.https://www.mdpi.com/2072-4292/17/5/918harmful algal bloomsremote sensingunmanned aerial vehiclechlorophyll-aphycocyaninsentinel |
| spellingShingle | Jianyong Wu Yanni Cao Shuqi Wu Smita Parajuli Kaiguang Zhao Jiyoung Lee Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review Remote Sensing harmful algal blooms remote sensing unmanned aerial vehicle chlorophyll-a phycocyanin sentinel |
| title | Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review |
| title_full | Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review |
| title_fullStr | Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review |
| title_full_unstemmed | Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review |
| title_short | Current Capabilities and Challenges of Remote Sensing in Monitoring Freshwater Cyanobacterial Blooms: A Scoping Review |
| title_sort | current capabilities and challenges of remote sensing in monitoring freshwater cyanobacterial blooms a scoping review |
| topic | harmful algal blooms remote sensing unmanned aerial vehicle chlorophyll-a phycocyanin sentinel |
| url | https://www.mdpi.com/2072-4292/17/5/918 |
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