The SISCAL project (1), funded by the European Community, aims at promoting a user-friendly access to Earth Observation data products for end users concerned by monitoring the water quality of coastal areas and inland waters. This objective will be realized by the SISCAL processor which will offer, through the internet, EO data products, geographical information systems and a tool box for data analysis. We will present here this SISCAL prototype, its functionality and outputs from a validation exercise.
In the frame of the EC-funded project SISCAL (Satellite-based Information System on Coastal Areas and Lakes), in situ campaigns have been executed in three coastal areas in the Baltic Sea, North-Eastern Atlantic and the Eastern Mediterranean as well as in a lake in North-Eastern Germany. The aim of these campaigns was to obtain measurements of the chlorophyll concentration for the validation of MERIS (Medium Resolution Imaging Spectrometer) data products. Between May and September 2002, in situ measurements have been performed concomitantly to thirteen MERIS overpasses. As of December 2002, MERIS Level-2 ocean products could be made available for six of the thirteen overpasses. At the specific in situ sampling sites, ocean products were available in four of the six MERIS data sets. On a pixel-by-pixel basis, three / four match-ups are available for Algal Pigment Index (API) I / II. The following preliminary conclusions can be drawn from the SISCAL validation activities: 1) API I shows a better dynamic resolution than does API II and reveals such more detailed dynamic structure, especially in oligotrophic areas, 2) in open ocean areas, API II values are larger (mostly by a factor of roughly two) than the API I values and appear to be overestimated, 3) in coastal areas influenced by significant CDOM concentrations, API II gives better results than API I.
Frank Fell, Phelim Burgess, Alexander Gruenewald, Mia Meyer, Richard Santer, Dirk Koslowsky, Dov Ganor, Barak Herut, Saleem Nimre, Gideon Tibor, Diego Berastegui, Lotte Nyborg, Michael Schultz-Rasmussen, Torunn Johansen, Geir Johnsen, Morten Brozek, Henrik Joergensen, Jan Habberstad, Frank Hanssen, Ran Amir, Alon Zask, Antje Koehler
SISCAL (Satellite-based Information System on Coastal Areas and Lakes) is a pan-European project dedicated to develop facilities to provide end-users with customized and easy-to-use data for environmental monitoring of coastal areas and lakes. The main task will be to create a software system providing Near-Real-Time information on the aquatic environment (using instruments such as AVHRR, MODIS or MERIS) and ancillary GIS-data. These products will be tailored to individual customers needs, allowing them to exploit Earth Observation (EO) data without extensive in-house knowledge. This way, SISCAL aims at closing the gap between research institutes, satellite data providers and the actual end-users.
Data and information exchange will entirely take place over the internet, from the acquisition of satellite data raw from the providers to the dissemination of finalized data products to the end-users. The focus of SISCAL is set on the optimal integration of existing techniques. The co-operation between the ten SISCAL partners, including four end-users representative of public authorities from local to national scale, aims at strengthening the operational use of EO data in the management of coastal areas and lakes.
The remote determination of the oceanic constituents in the upper ocean layer relies on the spectral information contained in the water leaving radiance. For waters of which the optical properties are mostly determined by phytoplankton and correlated degradation products ("case-I" waters), empirical or semi-empirical algorithms are successfully used to relate the water leaving radiance at two or more wavelengths to the chlorophyll concentration. These algorithms often fail in "case-II" waters where the water color is additionally influenced by sediments and non-autochtonous Colored Dissolved Organic Matter (CDOM). A promising method to derive chlorophyll concentration in case-II waters makes use of the sun-induced chlorophyll fluorescence (SICF) which is a feature specific to phytoplankton. The potential of the SICF for the space-borne retrieval of phytoplankton is reflected by the fact that several new satellite instruments (such as MERIS on ENVISAT) dispose of the required spectral channels to retrieve the SICF signal. In this article, we present an algorithm relating SICF to chlorophyll concentration in the topmost water layer. The algorithm has been derived from measurements gathered at more than 400 stations in different European waters and been applied to airborne imaging spectrometer data of European river plumes. Comparison with concurrent in situ measurements indicates that chlorophyll can be derived with a factor two error margin for the observed case-II waters. Recently, the algorithm was applied to one of the first available MERIS images and the retrieved chlorophyll concentration compared to results obtained from SeaWiFS data using the standard OC4v4 retrieval scheme.
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