An evaluation of the effect of the spectral response function of satellite sensors on the precision of the universal pattern decomposition method

In previous studies of the universal pattern decomposition method (UPDM), the band width has been used to calculate standard spectral pattern vectors, without consideration of the effect of spectral response functions (SRFs). This study revised the UPDM to further reduce sensor dependence, by taking into account the effect of SRFs. Both the UPDM and the revised UPDM (RUPDM) were applied to MODIS and ETM+ data acquired over the Three Gorges region of China. The reconstruction accuracy was significantly greater when the RUPDM was used, with a relative decrease in the mean chi(2) of more than 14%. Using the new method, the dependence of the decomposition coefficients and vegetation index (VIUPD) on the sensor also decreased, with their linear regression factors approximately equal to one. These increases in accuracy indicate that the RUPDM further reduces sensor dependence and hence can outperform the UPDM in data retrieval.