After testing different spatial interpolation techniques, ordinary linear Kriging resulted in the most accurate wind speed interpolation technique for our data. Wind speed across the Spanish part of the Iberian Peninsula and the Balearic Islands was modeled using the four nearest wind speed points for a default cell size of 4.2 km. Lack of wind speed data for the Canary Islands impeded us to incorporate them to the optimal windfarm area analysis. The GEBCO, 400 m-resolution 2014 global 30 arc-second interval grid was used to obtain bathymetry data of the Spanish seas [21]. From it, areas of 50 m of depth or less were selected, as 50 m is the maximal depth at which actual commercial windfarm technology (fixed turbines) can operate [23]. The following 1 km2 -resolution layers of broad types of ecosystems were used as surrogates for soft substrate and later merged in a ‘soft substrate layer’: subtidal soft bottom (0–60 m), soft shelf (60–200 m), soft slope (200–2000 m) and deep soft benthic (42000 m) [30]. Both, the resulting wind speed raster layer and resolution bathymetry layer were transformed to vector layers and intersected with the soft substrate layer within the 24 nm SEA area to produce the ‘OWA layer’. The ‘OWA layer’ was then intersected with the ‘new SEA zoning layer’ and possible optimal offshore windfarm development areas were identified.