Renewable potentials for solar photovoltaic (PV), onshore wind, and offshore wind were calculated across 201 model nodes using an area-based approach. For each node, the total available area for installing each technology was estimated, and this area was multiplied by an assumed installable capacity per unit area to determine the technical potential. For solar PV and onshore wind, the area analysis excluded unsuitable land types such as protected areas defined by the World Database on Protected Areas (WDPA). Usable land was then estimated based on assumed percentages of each land type within the node. For example, 3% of cropland was assumed usable for onshore wind, based on a European area analysis by Scholz (2012). These assumptions may not be universally applicable due to differing socio-political contexts across regions. Protected area data was sourced from the WDPA, and land cover data was drawn from the Copernicus Global Land Service (CGLS), which provides a global 100 m resolution land cover map with 23 discrete classes. The table below maps CGLS land class codes to specific land types used in the analysis.
Land TypeSolar Usable Fraction (%)Onshore Wind Usable Fraction (%)CGLS Land Classes
Protected Areas00N/A
Urban2.4050
Cropland0.03340
Forest03111, 112, 113, 114, 115, 116, 121, 122, 124, 125, 126
Shrubs and vegetation0.03320, 30
Bare333360
Water, wetland, moss and ice.0070, 80, 90, 100, 200
For offshore wind, assumptions were applied to restrict turbine siting within each node’s exclusive economic zone (EEZ). Turbines were only considered feasible if located at least 5 km offshore and in waters shallower than 300 m. EEZ boundaries were obtained from the Marine Regions World EEZ v12 dataset, and bathymetry data from  GEBCO. Installable capacity assumptions were based on Scholz et al. (2012): onshore wind – 10.42 MW/km², offshore wind – 10.42 MW/km², and solar PV – 141.9 MW/km². Hydropower potentials were sourced from Hoes et al. (2017), an online database of potential hydropower locations. These were aggregated at the node level, excluding any sites located within protected areas. Data sourcing standards for RE potentials are detailed below.

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Data sourcing standards – RE potentials

Input VariableModel TypeGold Standard (‘Best in Class’)Silver Standard (‘Good’)Bronze Standard (‘Publishable’)
Renewable energy potentialsCE & UDLand and policy constraints (e.g. local, state and national land use regulations). Based on a peer reviewed methodology.Land and policy constraints (e.g. local, state and national land use regulations) bands broken up by RE quality. Based on a peer reviewed methodology.Uniform global methodology which is not customised for every country.