1887

n South African Computer Journal - Robust fitting of diurnal brightness temperature cycles : pattern recognition special edition

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Abstract

Land surface temperatures (LSTs) can be approximated from brightness temperatures observed from satellites. Estimation errors between observed brightness temperatures and a brightness temperature model of a given pixel would provide information for a pixel concerned. Robust fitting of an observed Diurnal Temperature Cycle (DTC) taken over a day of a given pixel without cloud cover and other abnormal conditions such as fire can be used to derive a data-based brightness temperature model for a given pixel. A novel Singular Value Decomposition (SVD) method and an improved Reproducing Kernel Hilbert Space (RKHS) interpolator method (using a robust estimation method to approximate the coefficients of the RKHS interpolator) are proposed and compared to a pseudo-physical model approach. In this paper, diurnal brightness temperatures from the METEOSAT Second Generation (MSG) satellite were used to obtain a model. The simulation results show that the approach based on SVD outperforms other approaches in the sense that an accurate model which can be successfully used for the interpolation of missing diurnal cycle data, is more often found.

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/content/comp/2008/40/EJC28049
2008-06-01
2016-12-05
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