In this study we present methods and automatic technology developed for routine processing of satellite imagery acquired by cameras
MSU-201 and MSU-202 (KMSS-M) onboard Meteor-M No2. The developed methods were aimed at imag ery georeferencing issues fixing,
clouds and shadows detection as well as atmospheric and radiometric correction. Basing on these methods we built an automatic technology and complete KMSS-M data processing ch ain which provided analysis ready dataset for Russian grain belt and ad jacent areas of neighboring countries for the year 2020. Method for imagery georeferencing was based on Pearson’s correlation localized maximization when compared to the georefenced and cloudfree coarse-resolution reference image produced in IKI RAS through MOD09 product time series processing. Method for clouds and shadows detection was base d both on the spatial analysis of outputs from geocorrection step and auxiliary image, characterizing georeferenced KMSS-M image values relative accordance with the IKI reference image. The atmospheric correction was based on localized histogram matching of KMSS-M and IKI reference date-corresponding imagery, and thereby concurrently performed radiometric correction of KMSS-M data, compensating effects of varying viewing and illumination geometry which explicitly manifest across 960-km-wide swath area. The developed methods are noticeably mini malistic, requiring only one target spectral band to perform properly. Due to high flexibility and robustness, they also may be applied to raw satellite imagery acquired from various Earth observation system s, including Russian systems of high and moderate spatial resolution. The techno logy is currently being deployed in an operative mode for several test sites of Russia since the year 2021 onwards