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The first "ocean colour" sensor, Coastal Zone Color Scanner (CZCS), was launched in 1978. Oceanographers learnt a lot from CZCS but it remained a purely scientific sensor. In recent years, a new generation of satellite-borne earth observation (EO) instruments has been brought into space. These instruments combine high spectral and spatial resolution with revisiting rates of the order of one per day. More instruments with further increased spatial, spectral and temporal resolution will be available within the next years. In the meantime, evaluation procedures taking advantage of the capabilities of the new instruments were derived, allowing the retrieval of ecologically important parameters with higher accuracy than before. Space agencies are now able to collect and to process satellite data in real time and to disseminate them via the Internet. It is therefore meanwhile possible to envisage using EO operationally. In principle, a significant demand for EO data products on terrestrial or marine ecosystems exists both with public authorities (environmental protection, emergency management, natural resources management, national parks, regional planning, etc) and private companies (tourist industry, insurance companies, water suppliers, etc). However, for a number of reasons, many data products that can be derived from the new instruments and methods have not yet left the scientific community towards public or private end users.
It is the intention of the proposed SISCAL (Satellite-based Information System on Coastal Areas and Lakes) project to contribute to the closure of the existing gap between space agencies and research institutions on one side and end users on the other side. To do so, we intend to create a data processor that automatically derives and subsequently delivers over the Internet, in Near-Real-Time (NRT), a number of data products tailored to individual end user needs. The data products will be generated using a Geographical Information System (GIS), combining satellite data, evaluation algorithms and value-adding ancillary digital information. This prevents the end user from investing funds into expensive equipment or to hire specialized personnel. The data processor shall be a generic tool, which may be applied to a large variety of operationally gathered satellite data. In the frame of SISCAL, the processor shall be applied to remotely sensed data of selected coastal areas and lakes in Central Europe and the Eastern Mediterranean, according to the needs of the end users within the SISCAL consortium. A number of measures are required to achieve the objective of the proposed project:
(1) Identification and specification of the SISCAL end user needs for NRT water related data products accessible to EO techniques.
(2) Selection of the most appropriate instruments, evaluation algorithms and ancillary data bases required to provide the identified data products.
(3) Development of the actual Near-Real-Time data processor for the specified EO data products.
(4) Development of the GIS processor adding ancillary digital information to the satellite images and providing the required geographical projections.
(5) Development of a product retrieval and management system to handle ordering and distribution of data products between the SISCAL server and the end users, including payment and invoicing.
(6) Evaluation of the derived data products in terms of accuracy and usefulness by comparison with available in-situ measurements and by making use of the local expertise of the end users.
(7) Establishing an Internet server dedicated to internal communication between the consortium members as well as presenting the SISCAL project to a larger public.
(8) Marketing activities, presentation of data processor to potential external customers, identification of their exact needs.
The innovative aspect of the SISCAL project consists in the generation of NRT data products on water quality parameters from EO data. This article mainly deals with the identification of the end user requirements within the SISCAL consortium and the methods employed to realize them. Details on the technical implementation of the SISCAL processor are provided by Fell et al. (this issue).
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