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General satellite data service provision infrastructure for processing Envisat MERIS and other sources of data

Timo Pyhalahti(1), Sami Korhonen(1), Jenni Attila(1), Mikko Kervinen(1), Samuli Neuvonen(1), Saku Anttila(1), Kati Tahvonen(1), Kari Y. Kallio(1), Hanna Alasalmi(1), Sari Metsämäki(1), Miia Salminen(1), Sampsa Koponen(2) and Kaj Andersson(3)

(1) Finnish Environment Institute (SYKE), P.O. Box 140, FI - 00251 HELSINKI, Finland
(2) Helsinki University of Technology (TKK), P.O. Box 3000, 02015 TKK, Finland
(3) VTT, PO Box 13031, 02044 VTT, Finland


Validated and scientifically sound data interpretation algorithms for different phenomena are naturally the basis of any satellite-based observing system. However, significant amount of organisation, arrangements and infrastructure are required on top of the satellite data interpretation software for providing an operational service. The infrastructure required consists of hardware and software arrangements and the associated organisational structures - involving both the operators of the service and the users of the data. Failure to provide for example timely delivery of data for certain applications may cause the service to be useless. For other uses, the near real time delivery is not essential, but the ability to provide metadata (source and quality information of the provided data) for the services is. There are typically many tasks within the data processing chain which do not absolutely require human intervention, some of them are even common to broad range of applications. Certain tasks, for example those in the final quality control of certain products, require significant amount of human decision making ability and judgement in order to deliver services with acceptable quality. Automatisation of tasks is a challenging task, in case one wants to retain ability to use parallel sources of data from different satellite systems. This will be very relevant to all data users who wish for example to generate consistent datasets using both Envisat MERIS and future Sentinel data.

Instead of putting effort on 're-inventing the wheel' for each type of satellite, modelling result or other type of data for automatisation, process control and metadata creation, generic approach for data processing was applied for setting up processing environment in SYKE for NOAA AVHRR, Envisat MERIS, Terra/Aqua MODIS and Radarsat data. The guidelines for implementing different services allow the detailed set-up requirements of each service to be taken into account. The same (semi-)automatic system was applied for generating similar control interfaces for post-processing of HIRLAM atmospheric model data. The approach is compared with the approach adopted in NASA/Goddard for processing the MODIS and SeaWifs data.

Specialised approach was used for enabling the generation of different types of metadata from gathered XML information on processing. Dedicated user interfaces with common practices for the operators for providing the end-user services are reviewed.


Workshop presentation

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry