MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA
Two remote-sensing optical algorithms for the retrieval of the water quality components (WQCs) in the Albemarle-Pamlico Estuarine System (APES) were developed and validated for chlorophyll a (Chl). Both algorithms were semi-empirical because they incorporated some elements of optical processes in th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-04-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/3/4/684/ |
| _version_ | 1818283756134334464 |
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| author | Hans W. Paerl Leonid G. Sokoletsky Ross S. Lunetta Michael S. Wetz |
| author_facet | Hans W. Paerl Leonid G. Sokoletsky Ross S. Lunetta Michael S. Wetz |
| author_sort | Hans W. Paerl |
| collection | DOAJ |
| description | Two remote-sensing optical algorithms for the retrieval of the water quality components (WQCs) in the Albemarle-Pamlico Estuarine System (APES) were developed and validated for chlorophyll a (Chl). Both algorithms were semi-empirical because they incorporated some elements of optical processes in the atmosphere, water, and air/water interface. One incorporated a very simple atmospheric correction and modified quasi-single-scattering approximation (QSSA) for estimating the spectral Gordon’s parameter, and the second estimated WQCs directly from the top of atmosphere satellite radiance without atmospheric corrections. A modified version of the Global Meteorological Database for Solar Energy and Applied Meteorology (METEONORM) was used to estimate directional atmospheric transmittances. The study incorporated in situ Chl data from the Ferry-Based Monitoring (FerryMon) program collected in the Neuse River Estuary (n = 633) and Pamlico Sound (n = 362), along with Medium Resolution Imaging Spectrometer (MERIS) satellite imagery collected (2006–2009) across the APES; providing quasi-coinciding samples for Chl algorithm development and validation. Results indicated a coefficient of determination (R2) of 0.70 and mean-normalized root-mean-squares errors (NRMSE) of 52% in the Neuse River Estuary and R2 = 0.44 (NRMSE = 75 %) in the Pamlico Sound—without atmospheric corrections. The simple atmospheric correction tested provided on performance improvements. Algorithm performance demonstrated the potential for supporting long-term operational WQCs satellite monitoring in the APES. |
| first_indexed | 2024-12-13T00:41:58Z |
| format | Article |
| id | doaj.art-e773827c155c43f79813f6532e4d68f2 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T00:41:58Z |
| publishDate | 2011-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e773827c155c43f79813f6532e4d68f22022-12-22T00:05:07ZengMDPI AGRemote Sensing2072-42922011-04-013468470710.3390/rs3040684MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USAHans W. PaerlLeonid G. SokoletskyRoss S. LunettaMichael S. WetzTwo remote-sensing optical algorithms for the retrieval of the water quality components (WQCs) in the Albemarle-Pamlico Estuarine System (APES) were developed and validated for chlorophyll a (Chl). Both algorithms were semi-empirical because they incorporated some elements of optical processes in the atmosphere, water, and air/water interface. One incorporated a very simple atmospheric correction and modified quasi-single-scattering approximation (QSSA) for estimating the spectral Gordon’s parameter, and the second estimated WQCs directly from the top of atmosphere satellite radiance without atmospheric corrections. A modified version of the Global Meteorological Database for Solar Energy and Applied Meteorology (METEONORM) was used to estimate directional atmospheric transmittances. The study incorporated in situ Chl data from the Ferry-Based Monitoring (FerryMon) program collected in the Neuse River Estuary (n = 633) and Pamlico Sound (n = 362), along with Medium Resolution Imaging Spectrometer (MERIS) satellite imagery collected (2006–2009) across the APES; providing quasi-coinciding samples for Chl algorithm development and validation. Results indicated a coefficient of determination (R2) of 0.70 and mean-normalized root-mean-squares errors (NRMSE) of 52% in the Neuse River Estuary and R2 = 0.44 (NRMSE = 75 %) in the Pamlico Sound—without atmospheric corrections. The simple atmospheric correction tested provided on performance improvements. Algorithm performance demonstrated the potential for supporting long-term operational WQCs satellite monitoring in the APES.http://www.mdpi.com/2072-4292/3/4/684/water qualityoptical retrieval algorithmsMERIS imageryestuary system |
| spellingShingle | Hans W. Paerl Leonid G. Sokoletsky Ross S. Lunetta Michael S. Wetz MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA Remote Sensing water quality optical retrieval algorithms MERIS imagery estuary system |
| title | MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA |
| title_full | MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA |
| title_fullStr | MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA |
| title_full_unstemmed | MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA |
| title_short | MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA |
| title_sort | meris retrieval of water quality components in the turbid albemarle pamlico sound estuary usa |
| topic | water quality optical retrieval algorithms MERIS imagery estuary system |
| url | http://www.mdpi.com/2072-4292/3/4/684/ |
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