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The project ENDORSE: exploiting EO data to develop pre-market services in renewable energy

Abstract : The ENDORSE project is co-funded by the FP7 programme of the European Commission, from 2011 to 2013. It exploits the atmosphere service MACC of the European GMES programme (Global Monitoring for Environment and Security) together with other Earth Observation (EO) data and modelling. It aims at providing public authorities and private investors with accurate evaluation and forecasts of renewable resources. The focus is on the devel-opment of downstream services that create added-value information. We present here the achievements of the first period. A very accurate though fast algorithm describing the position of the sun in the sky has been developed. A series of recommendations for quality control of meteorological data have been issued. All algorithms are available as code sources and are being implemented as Web processing services (WPS). Support vector machine techniques prove successful to map the air temperature at 2-m height from satellite images and a few measurements at ground level. The next development of ENDORSE is a portfolio of pre-market downstream services, serving as precursors and examples of best practices for similar services. The resulting services will be described using the INSPIRE metadata and declared in an existing Catalog Service for the Web (CSW) dedicated to energy. Finally, we discuss the mutual benefits between GEOSS (Global Earth Observation System of Systems) and ENDORSE.
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Contributor : Lucien Wald <>
Submitted on : Monday, October 10, 2011 - 2:56:45 PM
Last modification on : Friday, October 23, 2020 - 4:59:05 PM
Long-term archiving on: : Wednesday, January 11, 2012 - 2:25:16 AM

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  • HAL Id : hal-00630619, version 1

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Lucien Wald, Claire Thomas, Sophie Cousin, Philippe Blanc, Lionel Ménard, et al.. The project ENDORSE: exploiting EO data to develop pre-market services in renewable energy. 25th EnviroInfo Conference 'Environmental Informatics', Oct 2011, Ispra (VA), Italy. pp.549-556. ⟨hal-00630619⟩

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