Harmonised global datasets of wind and solar farm locations and power

The methodology to produce these data is described in the accompanying paper:Dunnett, S., Sorichetta, A., Taylor, G. et al. Harmonised global datasets of wind and solar farm locations and power. Sci Data 7, 130 (2020). https://doi.org/10.1038/s41597-020-0469-8AbstractEnergy systems need decarbonisation in order to limit global warming to within safe limits. While global land planners are promising more of the planet’s limited space to wind and solar photovoltaic, there is little information on where current infrastructure is located. The majority of recent studies use land suitability for wind and solar, coupled with technical and socioeconomic constraints, as a proxy for actual location data. Here, we address this shortcoming. Using readily accessible OpenStreetMap data we present, to our knowledge, the first global, open-access, harmonised spatial datasets of wind and solar installations. We also include user friendly code for enabling users to easily create newer versions of the dataset. Finally, we include first order estimates of power capacities of installations. We anticipate this data will be of widespread interest within global studies of the future potential and trade-offs associated with the global decarbonisation of energy systems.Data overviewThe datasets represent three different formats of the following data in WGS 1984 and Eckert IV projections:Global wind turbines in April 2020 clustered using a neighbourhood distance of 800mGlobal solar installations in April 2020 clustered using a neighbourhood distance of 400mThe formats comprise:ESRI geodatabase (*.gdb): proprietary geospatial file format for use with ArcGIS that contains two layers in the same file, one for solar and one for wind;Geopackages (*.gpkg): open source geospatial file format that can work with a variety of software and can store different geometries natively;Comma-delimited files (*.csv): the simplest format, these files represent the centroid of each data record, i.e. point data, as X and Y coordinates in a data table.Also included is an archive folder, analysis, that contains four R scripts and accompanying data used for acquiring and processing the data.Sharing and accessData adapted or built on OpenStreetMap data are required to be distributed under the same licence. These data are therefore made available under the Open Data Commons Open Database License (ODbL). Personal figshare accounts cannot currently present data under this licence so the data are currently (incorrectly) presented under a CC0 licence as a stopgap until this changes. More information on OpenStreetMap data and use of data can be found here.The data should be cited as follows:Dunnett, S. Harmonised global datasets of wind and solar farm locations and power. figshare. Dataset. https://doi.org/10.6084/m9.figshare.11310269 (2020)