Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmos...
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| Format: | Article |
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MDPI AG
2016-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/16/10/1749 |
| _version_ | 1828136635939684352 |
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| author | Tara Blakey Assefa Melesse Michael C. Sukop Georgio Tachiev Dean Whitman Fernando Miralles-Wilhelm |
| author_facet | Tara Blakey Assefa Melesse Michael C. Sukop Georgio Tachiev Dean Whitman Fernando Miralles-Wilhelm |
| author_sort | Tara Blakey |
| collection | DOAJ |
| description | This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning. |
| first_indexed | 2024-04-11T18:06:17Z |
| format | Article |
| id | doaj.art-5a573351baed4088a41885993559183c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:06:17Z |
| publishDate | 2016-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5a573351baed4088a41885993559183c2022-12-22T04:10:18ZengMDPI AGSensors1424-82202016-10-011610174910.3390/s16101749s16101749Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFSTara Blakey0Assefa Melesse1Michael C. Sukop2Georgio Tachiev3Dean Whitman4Fernando Miralles-Wilhelm5Department of Earth and Environment, Florida International University, Miami, FL 33199, USADepartment of Earth and Environment, Florida International University, Miami, FL 33199, USADepartment of Earth and Environment, Florida International University, Miami, FL 33199, USAGIT Consulting, Coral Gables, FL 33134, USADepartment of Earth and Environment, Florida International University, Miami, FL 33199, USAEarth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USAThis study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning.http://www.mdpi.com/1424-8220/16/10/1749chl-awater qualityeutrophicationoptically shallowbottom reflectanceSeaWiFSocean color remote sensingvalidationmodelingalgorithms |
| spellingShingle | Tara Blakey Assefa Melesse Michael C. Sukop Georgio Tachiev Dean Whitman Fernando Miralles-Wilhelm Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS Sensors chl-a water quality eutrophication optically shallow bottom reflectance SeaWiFS ocean color remote sensing validation modeling algorithms |
| title | Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS |
| title_full | Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS |
| title_fullStr | Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS |
| title_full_unstemmed | Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS |
| title_short | Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS |
| title_sort | developing benthic class specific chlorophyll a retrieving algorithms for optically shallow water using seawifs |
| topic | chl-a water quality eutrophication optically shallow bottom reflectance SeaWiFS ocean color remote sensing validation modeling algorithms |
| url | http://www.mdpi.com/1424-8220/16/10/1749 |
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