Novel WkNN-based technique to improve instantaneous rainfall estimation over the north of Algeria using the multispectral MSG SEVIRI imagery

摘要

For the estimation of rainfall in northern Algeria, a new method is proposed in this study. It based on the k nearest weighted neighbours (WkNN) classification algorithm using the dataset from the radiometer-imager SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) boarded on the satellite MSG (Meteosat Second Generation) to determine the pixel rainfall rate among the 16 predefined intensity levels observed in the Setif meteorological radar.