R. Doerffer

Papers

Total Citations

201

H-Index

About

R. Doerffer is a leading figure in ocean color remote sensing, specializing in the development of atmospheric correction algorithms for complex coastal and inland waters. His most significant contribution is the design of the operational atmospheric correction algorithm for the Medium Resolution Imaging Spectrometer (MERIS), specifically tailored for optically complex "case-2" waters—a notoriously challenging environment where standard open-ocean methods fail. This landmark work, detailed in his 2007 paper (cited over 200 times), employs an innovative inverse modeling approach using artificial neural networks to simultaneously retrieve aerosol properties and water-leaving radiances from top-of-atmosphere measurements. By enabling accurate remote sensing of turbid, sediment-laden, and phytoplankton-rich waters, Doerffer's algorithm fundamentally expanded the applicability of satellite ocean color data from the clear open ocean to the biologically productive and economically vital coastal zones. His work has become a cornerstone for subsequent missions like Sentinel-3's OLCI, directly influencing how scientists monitor water quality, carbon cycling, and ecosystem health in our most dynamic aquatic environments.