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    Support of wind resource modeling using Earth observation – a European perspective on the status and future options

    Esch, T. and Bay-Hasager, C. and Elsner, Paul and Deutscher, J. and Hirschmugl, M. and Metz, A. and Roth, A. (2016) Support of wind resource modeling using Earth observation – a European perspective on the status and future options. In: Weng, Q. (ed.) Remote Sensing for Sustainability. CRC Press/Taylor & Francis. ISBN 9781498700719.

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    Abstract

    This contribution outlines the potential of remote sensing data to support wind resource modelling especially through improved input parameterization regarding the state and characterization of the land surface. Wind speed and wind flow is strongly influenced by land surface properties. Three different remote sensing based parameters can help to characterize wind resources: a) land cover and land use; b) digital elevation models (DEM); c) phenological information. Earth observation data are used already in wind resource models to some extent. However, the new advances and especially the possibilities which open up through the Copernicus Sentinel satellites are not considered yet. Opportunities include seasonal mapping of land cover which will allow a precise quantification of vegetation cover which has a direct influence on heat fluxes. The use of newest DEMs like Tandem-X with a 12 m resolution allows detecting also small landscape feature like rows of hedges and trees. Further, elevation models derived by either photogrammetric approaches or airborne laser scanning can further refine the information. By using EO-based information on the surface, e.g. roughness, and in-situ wind measurements, realistic wind fields for sufficiently large areas can be derived by considering also shadowing effects and wind shear.

    Metadata

    Item Type: Book Section
    School: Birkbeck Schools and Departments > School of Social Sciences, History and Philosophy > Department of Geography
    Depositing User: Paul Elsner
    Date Deposited: 18 Jul 2016 12:41
    Last Modified: 28 Jul 2019 17:10
    URI: http://eprints.bbk.ac.uk/id/eprint/15738

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