Section outline

  • Image with wind turbines in a rural landscape. 2% of Germany's land area is to be allocated to wind power production by 2032

    How Spatial Information Infrastructures Support the Planning of Wind Farms

    (August 2024)

    In this learning material, we use the real-world use case of planning the extension of a wind farm in the municipality of Lorup in Lower Saxony, Germany, to explore how geoinformation infrastructures support the availability and use of geospatial data needed in the wind farm planning process.

    You will learn,

    • why wind farm planning requires easy access to up-to-date, high-quality geospatial data and what kind of data is needed,
    • how SIIs facilitate the discoverability, accessibility, and usability of geospatial data that is needed for wind farm planning.

    Content Structure
    1. Overview

    2. Background

    3. Planning the extension of a wind farm in Lorup, Germany

    4. Summary and discussion

    5. Check your Knowledge

    Target Group and Prequistes

    This tutorial is designed for students and professionals who want to improve their understanding of Spatial Information Infrastructures. We assume that you have some basic knowledge about geospatial data, QGIS and spatial data analysis. You will need about 90 minutes to use this tutorial.

    License Statement

    You are free to use, alter and share the tutorial under the terms of the CC-BY-SA 4.0 license, unless explicitly stated otherwise for specific parts of the content.

    The tutorial can be referenced as follows: “OER-SDI4WindFarmPlanning”, OER4SDI project /  University Münster, CC BY-SA 4.0.

    All logos used are generally excluded. Any code provided with the tutorial can be used under the terms of the MIT license. Please see the full license terms: https://github.com/oer4sdi/OER-WindFarmExtension/edit/main/LICENSE.md)

    Authors and Funding

    This Tutorial has been developed in the context of the OER4SDi project at the Institute for Geoinformatics, University of MĂĽnster. Authors are Nouran Armanazi and Albert Remke with contributions from Stefan LĂĽtkemeyer (Revento GmbH).

    The OER4SDI project has been recommended by the Digital University NRW and is funded by the Ministry of Culture and Science NRW.