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Research Article | Open Access |

Comparative Study on Sea Surface Temperature Estimation with Thermal Infrared Radiometer Data among Conventional MCSST, Split Window and Conjugate Gradient Based Methods

Author 1: Kohei Arai
International Journal of Advanced Research in Artificial Intelligence (IJARAI) · Vol. 2, No. 8 · Published 2013

DOI: 10.14569/IJARAI.2013.020802

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Abstract

Comparative study on Sea Surface Temperature: SST estimations among the conventional Multi-Channel Seat Surface Temperature: MCSST, split window method and the proposed Conjugate Gradient based method: CGM with Thermal Infrared Radiometer: TIR data through simulations is conducted. Utilizing the proposed linearized inversion of radiative transfer equation, SST can be estimated. SST estimation accuracy of the proposed method is compared to the conventional regression based method (Split Window and MCSST method). Through the simulation study, it is found that the proposed CGM based method is superior to the conventional regression based method.

Keywords

Sea Surface Temperature radiative transfer equation regression conjugate gradient MCSST split window

How to Cite this Article

Arai, K. (2013). Comparative Study on Sea Surface Temperature Estimation with Thermal Infrared Radiometer Data among Conventional MCSST, Split Window and Conjugate Gradient Based Methods. International Journal of Advanced Research in Artificial Intelligence, 2(8). https://doi.org/10.14569/IJARAI.2013.020802

Arai, Kohei. "Comparative Study on Sea Surface Temperature Estimation with Thermal Infrared Radiometer Data among Conventional MCSST, Split Window and Conjugate Gradient Based Methods." International Journal of Advanced Research in Artificial Intelligence, vol. 2, no. 8, 2013, https://doi.org/10.14569/IJARAI.2013.020802.

@article{Arai2013,
  title     = {Comparative Study on Sea Surface Temperature Estimation with Thermal Infrared Radiometer Data among Conventional MCSST, Split Window and Conjugate Gradient Based Methods},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {2},
  number    = {8},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai},
  doi       = {10.14569/IJARAI.2013.020802},
  url       = {https://doi.org/10.14569/IJARAI.2013.020802}
}

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