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EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites), an intergovernmental organisation founded in 1986, supplies weather and climate-related satellite data, images and products throughout the year for EU Member States and other users worldwide. The optical Earth Observation satellites launched and operated by EUMETSAT, both current and planned ones, have different spatial, spectral and temporal resolutions; sensor models and acquisition geometries. While the number and the diversity of the satellite missions increase, the requirement of novel methods and up-to-date reference data for geometric accuracy assessment of the imagery also grows. This paper aims at reporting the results of a study investigating the availability for suitable satellite imagery to be employed as reference data for the geometric quality assessment (GQA) of MSG SEVIRI Level 1.5 image products. The reference datasets need to have superior spatial resolution, wide global coverage, and spectral compatibility with respect to the SEVIRI sensor, which has 12 spectral bands with 1 km and 3 km spatial resolutions. The SEVIRI sensor works with whiskbroom principle at a geostationary orbit and collects data at 5 minutes (rapid scan) and 15-minutes (full scan) intervals. Although preliminary investigations on reference data were performed by using images of different satellite sensors during the study, in-depth investigations were performed with MERIS global image mosaic and Landsat imagery. The progress and different problems observed in the images are reported here. [ABSTRACT FROM AUTHOR]

The Copernicus programme, is a European initiative for the implementation of information services based on observation data received from Earth Observation (EO) satellites and ground based information. In the frame of this programme, ESA is developing the Sentinel-2 optical imaging mission that will deliver optical data products designed to feed downstream services mainly related to land monitoring, emergency management and security. To ensure the highest quality of service, ESA sets up the Sentinel-2 Mission Performance Centre (MPC) in charge of the overall performance monitoring of the Sentinel-2 mission. TPZ F and DLR have teamed up in order to provide the best added-value support to the MPC for calibration and validation of the Level-2A processor (Sen2Cor) and products. This paper gives an overview over the planned L2A calibration and validation activities. Level-2A processing is applied to Top-Of-Atmosphere (TOA) Level-1C ortho-image reflectance products. Level-2A main output is the Bottom-Of-Atmosphere (BOA) corrected reflectance product. Additional outputs are an Aerosol Optical Thickness (AOT) map, a Water Vapour (WV) map and a Scene Classification (SC) map with Quality Indicators for cloud and snow probabilities. Level-2A BOA, AOT and WV outputs are calibrated and validated using ground-based data of automatic operating stations and data of in-situ campaigns. Scene classification is validated by the visual inspection of test datasets and cross-sensor comparison, supplemented by meteorological data, if available. Contributions of external in-situ campaigns would enlarge the reference dataset and enable extended validation exercise. Therefore, we are highly interested in and welcome external contributors. [ABSTRACT FROM AUTHOR]

This paper presents a new method developed for the atmospheric correction of the images that will be acquired by the Venμs satellite after its launch expected in early 2010. Every two days, the Venμs mission will provide 10 m resolution images of 50 sites, in 12 narrow spectral bands ranging from 415 nm to 910 nm. The sun-synchronous Venμs orbit will have a 2-day repeat cycle, and the images of a given site will always be acquired from the same place, at the same local hour, with constant observation angles. Thanks to these characteristics, the directional effects will be considerably reduced since only the solar angles will slowly vary with time. The algorithm that will be implemented for the atmospheric correction of Venμs data is being developed using both radiative transfer simulations and the actual data acquired by the Formosat-2 satellite. Because of its one-day sun-synchronous repeat cycle, Formosat-2 acquires images with a sun-viewing geometry close to the one Venμs will offer. With this geometry, reflectance time series are free from directional effects on the short term, a feature which reduces the number of unknowns to retrieve. The atmospheric corrections algorithm exploits this feature and the two following assumptions: [–] Aerosol optical properties vary quickly with time but slowly with location. [–] Surface reflectances vary quickly with location but slowly with time. Consequently, the top of atmosphere reflectance short term variations (10 to 15 days) are mainly due to the variations of aerosol optical properties, and it is thus possible to use these variations to characterise the atmospheric aerosols and to retrieve surface reflectances. This paper first describes the aerosol inversion method we developed and its results when applied to simulations. In the second part, we show the first tests of the method against three data sets acquired by Formosat-2 images with constant observation angles. Aeronet sun photometers measurements were available on all sites. Formosat-2 estimates of optical thickness compare favourably with Aeronet in situ measurements, leading to a noticeable improvement of the smoothness of time series of surface reflectances after atmospheric correction. [Copyright &y& Elsevier]