Application of in-situ sensors (SUNA and thermal logger) in fine tuning the nitrate model of the Bay of Bengal
| Autor: | D. Poornima, R. Shanthi, R. K. Sarangi, Prakash Chauhan, L. Senthilnathan, R. Ranith, Thirunavukarasu Thangaradjou |
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| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
In situ 010504 meteorology & atmospheric sciences Mean squared error 010604 marine biology & hydrobiology Geography Planning and Development Regression analysis Atmospheric sciences 01 natural sciences chemistry.chemical_compound Sea surface temperature Nitrate chemistry Thermal Environmental science Computers in Earth Sciences Bay 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Remote Sensing Applications: Society and Environment. 4:9-17 |
| ISSN: | 2352-9385 |
| DOI: | 10.1016/j.rsase.2016.04.002 |
| Popis: | The in-situ sensor based nitrate algorithm is developed by using SUNA and thermal logger derived nitrate and temperature data along the coastal waters of southwest Bay of Bengal. Comparison was carried out between SUNA and in-situ nitrate depicted 88% overestimation in open ocean waters and the regression analysis provided R 2 =0.568 with SEE=±0.360. The nitrate algorithm is derived from the empirical relationship between SUNA and thermal logger derived nitrate and SST during postmonsoon season. Overall regression analysis, sigmoid function provides the better relationships of R 2 =0.872 and SEE=±0.776. MODIS Aqua derived SST is used to develop the instrument based algorithm to retrieve nitrate image whereas MODIS Aqua derived SST and chlorophyll are applied with conventional algorithm proposed earlier and compared. The two different nitrate algorithms are regressed with in-situ nitrate value for testing the accuracy of the algorithms. The regression between sensor and laboratory analyzed nitrate showed the R 2 =0.619, SEE=±0.501, MNB=1.303 and RMSE=1.727 µM, whereas the conventional model nitrate showed the R 2 =0.695, SEE=±0.175, MNB=0.603 and RMSE=1.054 µM. Thus, the present results confirm that chlorophyll as an important input for developing nitrate algorithms whatever the way the data have been collected. |
| Databáze: | OpenAIRE |
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