PLANtoACT タスク2.2：再生可能エネルギー賦存量分析データ

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a replicable methodology for estimating renewable energy potentials using open data, useful for comparative studies on energy planning.

🏢実務担当者:Offers a ready-to-use spatial dataset for identifying high-potential areas for PV and wind, aiding site selection and project feasibility assessments.

🏛政策担当者:Demonstrates a data-driven approach for regional energy planning that can inform policy design and funding allocation for clean energy transition.

Description This repository presents the results of the renewable energy potentials estimation carried out within Work Package 2 (WP2, Task 2.2) of the PLANtoACT project. PLANtoACT is a LIFE Programme–funded project (October 2025–September 2028) that develops, tests, and promotes a stakeholder-driven, spatially detailed integrated energy planning approach to help European Local and Regional Authorities move from clean energy transition targets to coordinated, financed, and implementable action. Scope of the data assembly The dataset provides spatial data for the estimation of renewable energy potentials for the five pilot regions of the project: Oberland (Germany), Auvergne-Rhône-Alpes (France), Lombardia (Italy), the Porto Metropolitan Area (Portugal), and Alba County (Romania).   Data collection methodology and validation The data was obtained by combining globally available data sources (e.g., CORINE Land Cover dataset) with local, region-specific sources where available (such as 3D building models). The renewable energy potential estimation considered two main technologies: photovoltaic (PV) and wind. For PV, four deployment configurations were analysed: agri-PV, ground-mounted PV, and rooftop PV on both residential and non-residential buildings. For wind, onshore turbines were assessed across all pilot regions. Repository contents The repository is organized by pilot region. For each region, the repository provides the following specific files: pv_potentials.txt: Region-specific documentation detailing the pv energy potentials per deployment configurations. wind_potentials.txt: Region-specific documentation detailing the wind energy potentials per deployment configurations. ren_ene_potentials.gpkg: Complete dataset containing pv and wind energy potentials at municipal level.   References List of all data used.   Globally available data: Copernicus CORINE Land Cover (CLC 2018): European Environment Agency (2019). CORINE Land Cover 2018 (vector/raster 100 m), Europe, 6-yearly, version 2020_20u1. Copernicus Land Monitoring Service. [Dataset] https://doi.org/10.2909/71c95a07-e296-44fc-b22b-415f42acfdf0 Copernicus DSM (100 m): European Space Agency / Copernicus Programme. Copernicus DEM — Global and European Digital Elevation Model, GLO-30 instance (30 m native resolution, data acquired by the TanDEM-X mission 2011–2015), resampled to 100 m (EU-LAEA projection). [Dataset] https://dataspace.copernicus.eu/explore-data/data-collections/copernicus-contributing-missions/collections-description/COP-DEM Copernicus Data Space Ecosystem EEA Nationally Designated Areas (NatDA): European Environment Agency. Nationally designated areas — the official source of protected area information from the 38 European member countries to the World Database of Protected Areas (WDPA), maintained by the EEA with support from the European Topic Centre on Data Integration and Digitalisation (formerly the Common Database on Designated Areas, CDDA). [Dataset] https://www.eea.europa.eu/data-and-maps/data/nationally-designated-areas-national-cdda-17 EMODnet EEA Natura 2000: European Environment Agency. Natura 2000 — spatial data (end-2021 release, revision 1). Ecological network of protected sites under the Birds Directive (1979) and Habitats Directive (1992). [Dataset] https://www.eea.europa.eu/data-and-maps/data/natura-14 Global Wind Atlas (wind power density): Floors, R. et al. (2025). Global Wind Atlas v4, https://doi.org/10.11583/DTU.28955267 . Produced and maintained by the Global Wind Atlas, Department of Wind Energy at the Technical University of Denmark (DTU Wind Energy) and the World Bank Group. [Dataset] https://globalwindatlas.info figshare GEE Community Catalog JRC DBSM: Martínez, A. M., Kakoulaki, G., Florio, P., Politis, P., Gounari, O. (2026). DBSM R2025: EU Digital Building Stock Model update including satellite-based attributes and rooftop photovoltaics potential. European Commission, Joint Research Centre. [Dataset] https://data.jrc.ec.europa.eu/dataset/a601a4a8-9289-4fc4-983a-25d54f957f3a JRC European Flood Hazard Maps (100-year return period): Dottori, F., Alfieri, L., Bianchi, A., Skoien, J., Salamon, P. (2021). River flood hazard maps for Europe and the Mediterranean Basin region — 100-year return period. European Commission, Joint Research Centre (JRC). [Dataset] doi: 10.2905/1D128B6C-A4EE-4858-9E34-6210707F3C81, PID: http://data.europa.eu/89h/1d128b6c-a4ee-4858-9e34-6210707f3c81 (methodology described in Dottori et al., "A new dataset of river flood hazard maps for Europe and the Mediterranean Basin," which presents high-resolution (100 m) hazard maps for river flooding covering most European countries plus river basins draining into the Mediterranean and Black Sea, https://doi.org/10.5194/essd-14-1549-2022 ) European Commission OpenStreetMap (parking areas): OpenStreetMap contributors. Planet dump. OpenStreetMap Foundation. [Dataset] https://www.openstreetmap.org (© OpenStreetMap contributors, available under the Open Database License) Locally available data: Germany (Oberland): 3D Building Models (LoD2) : Bayerische Vermessungsverwaltung. (2024). 3D-Gebäudemodelle (LoD2). https://geodaten.bayern.de/opengeodata/OpenDataDetail.html?pn=lod2 France (Auvergne-Rhône-Alpes): BD-TOPO: IGN. (2024). BD TOPO. https://geoservices.ign.fr/bdtopo Italy (Lombardia): DBGT: Regione Lombardia. (2024). Database Geo-Topografico (DBGT). https://www.geoportale.regione.lombardia.it/specifiche-tecniche

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