The Laboratory for Earth Observation (LEO) is part of the interdisciplinary research unit Image Processing Laboratory (IPL) from the University of Valencia. Led by Prof. J. Moreno, deals with most of the technical and scientific aspects of Earth observation, including design of new instrument missions, processing of new data types, in particular optical multi-angular and hyperspectral data.

• Theoretical modeling of radiative transfer processes of natural surfaces, with emphasis on hyperspectral sampling of the electromagnetic radiation
• Development of algorithms and implementation of physical model inputs in Earth observation products: model inversion and data assimilation
• Development of new instruments and techniques related to detection of fluorescence
• Development of data processing methods (atmospheric correction, geometric corrections related to multi-angular systems, processing chains)
• Monitoring of natural vegetation, hydrological cycles, desertification, CO2 fluxes, and energy balances using Earth observation data.
• Definition of requirements, development of processing algorithms and data simulation for future sensors and missions (FLEX, Sentinel-3, Sentinel-2, SEOSAT/INGENIO, SPECTRA)
• Calibration and validation of optical satellite data (ENVISAT, MSG, PROBA) and airborne data (AHS, CASI, HYPER).

The LEO group started its work in the field of imaging spectroscopy in 1998 with the participation of Prof. José Moreno as coordinator of the field activities for ESA’s DAISEX98 experiment. This experiment was set up to test the new hyperspectral airborne DAIS sensor developed by the German Aerospace Agency (DLR). Since then, LEO has been involved in more than 30 national and international research projects. In those projects, the group has dealt with most of the technical and scientific aspects of Earth observation, including design of new instrument missions, processing of new data types, in particular optical multi-angular and hyperspectral data. The group has developed a processing chain for automatic image preprocessing; starting from raw data, identifying and correcting for all types of noise, until delivery of atmospherically and geometrically corrected reflectance data and derived products (e.g. cloud maps, aerosol optical depth) at the highest possible quality. This processing chain is currently implemented in the ESA Basic ERS & Envisat (A)ATSR and MERIS Toolbox (BEAM) and has recently been applied to new generation optical sensors, such as AHS, CASI-1500, HYPER and CHRIS-PROBA.