Improvement of the drought monitoring model based on the cloud parameters method and remote sensing data

Based on the original model, this paper mainly introduces modification to the cloud index in both temporal and spatial dimension, and leads to a new drought monitoring model with a stable performance to the temporal and spatial variation of remote sensing data. In this study, taking into consideration of the temporal and spatial variation, a comprehensive analysis is performed about functions which describe the how the cloud indexes affect the ravage of drought. Afterwards, based on this analysis, a modification function is restricted to a certain format, which is finally settled with the parameters retrieved by the remote sensing data accompanied with the measured date about the humidity of the soil deep to 20cm. This modification function is applied to regulate the 3 cloud impaction functions. Finally, the new drought monitoring model is modified by evaluating different weights to three cloud impaction functions. Meanwhile, this new model is applied to the FY-2C data covering the whole land surface of China. Compared with the traditional monitoring algorithms, the new model is proved to be able to offer a more accurate and reliable result in large scale of time and space.