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In recent years satellite water quality information have been used for several purposes, such as: 1) regular and specific monitoring, 2) matters that require Near Real Time information (e.g. when cyanobacterial blooms are threatening the swimming water quality) and 3) for the spatial optimisation of monitoring networks. To the aim, image processing chains need to be set up to transform the radiance recorded by satellite sensors into information on water quality, such as the concentrations of water constituents, the physical values on water surface temperature or maps depicting e.g. the spatial extent of aquatic vegetation. Despite these techniques have been developed since about three decades, there are still ongoing developments to produce accurate and consistent products across all water bodies.This is particularly the case for EOMORES, whose target lakes include a wide range of water types. Moreover, as EOMORES makes use of the latest generation of satellite sensors, consolidated image processing techniques need to be adapted according to the resolutions and spectral bands of these newest sensors. This is especially relevant for Sentinel-2 MSI,since for Sentinel-3 OLCI most of the developments are based on its precursor MERIS on Envisat (2002-2012).This document hence illustrates the image processing chain that have been adapted to produce relevant water quality information for the EOMORES study sites. A first section is dedicated to the description of the methods while the last part describe show the processors have been applied to produce maps (both of the past and recent years, including 2018) of water quality. The selected processors are now being used to set up the operational EOMORES service according to WP6.