A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens)
A multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N) dependent parameterizations of the spectral backscattering coefficients, bb(λ), obtained from in situ measurements. There was a strong relationship...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2016/1780986 |
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| author | Lingling Jiang Lin Wang Xinyu Zhang Yanlong Chen Deqi Xiong |
| author_facet | Lingling Jiang Lin Wang Xinyu Zhang Yanlong Chen Deqi Xiong |
| author_sort | Lingling Jiang |
| collection | DOAJ |
| description | A multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N) dependent parameterizations of the spectral backscattering coefficients, bb(λ), obtained from in situ measurements. There was a strong relationship between bb(λ) and N, with a minimum regression coefficient of 0.97 at 488 nm and a maximum value of 0.98 at other bands. The cell density calculated by the multiband inversion model was similar to the field measurements of the coastal waters (the average relative error was only 8.9%), but it could not accurately discern the red tide from mixed pixels, and this led to overestimation of the area affected by the red tide. While the single-band inversion model is less precise than the former model in the high chlorophyll water, it could eliminate the impact of the suspended sediments and make more accurate estimates of the red tide area. We concluded that the two models both have advantages and disadvantages; these methods lay the foundation for developing a remote sensing forecasting system for red tides. |
| format | Article |
| id | doaj-art-810ee3c591f14b08b7395840f2a5c01e |
| institution | OA Journals |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-810ee3c591f14b08b7395840f2a5c01e2025-08-20T02:08:53ZengWileyAdvances in Meteorology1687-93091687-93172016-01-01201610.1155/2016/17809861780986A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens)Lingling Jiang0Lin Wang1Xinyu Zhang2Yanlong Chen3Deqi Xiong4College of Environmental Science and Engineering, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, ChinaNational Marine Environmental Monitoring Center, No. 42 Linghe Road, Dalian 116023, ChinaNavigation College, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, ChinaNational Marine Environmental Monitoring Center, No. 42 Linghe Road, Dalian 116023, ChinaCollege of Environmental Science and Engineering, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, ChinaA multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N) dependent parameterizations of the spectral backscattering coefficients, bb(λ), obtained from in situ measurements. There was a strong relationship between bb(λ) and N, with a minimum regression coefficient of 0.97 at 488 nm and a maximum value of 0.98 at other bands. The cell density calculated by the multiband inversion model was similar to the field measurements of the coastal waters (the average relative error was only 8.9%), but it could not accurately discern the red tide from mixed pixels, and this led to overestimation of the area affected by the red tide. While the single-band inversion model is less precise than the former model in the high chlorophyll water, it could eliminate the impact of the suspended sediments and make more accurate estimates of the red tide area. We concluded that the two models both have advantages and disadvantages; these methods lay the foundation for developing a remote sensing forecasting system for red tides.http://dx.doi.org/10.1155/2016/1780986 |
| spellingShingle | Lingling Jiang Lin Wang Xinyu Zhang Yanlong Chen Deqi Xiong A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens) Advances in Meteorology |
| title | A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens) |
| title_full | A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens) |
| title_fullStr | A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens) |
| title_full_unstemmed | A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens) |
| title_short | A Semianalytical Model Using MODIS Data to Estimate Cell Density of Red Tide Algae (Aureococcus anophagefferens) |
| title_sort | semianalytical model using modis data to estimate cell density of red tide algae aureococcus anophagefferens |
| url | http://dx.doi.org/10.1155/2016/1780986 |
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