Locating new wind farms is of crucial importance for energy policies
of the next decade. To select the new location, an accurate picture
of the wind fields is necessary. However, characterizing wind fields
is a difficult task, since the phenomenon is highly nonlinear and
related to complex topographical features. In this paper, we propose
both a nonparametric model to estimate wind speed at different time
instants and a procedure to discover underrepresented topographic
conditions, where new measuring stations could be added. Compared
to space filling techniques, this last approach privileges optimization
of the output space, thus locating new potential measuring sites
through the uncertainty of the model itself.