Offshore wind is an attractive energy source due to the potential of very high wind power as a result of relatively low sea surface roughness. Currently wind observations at meteorological masts positioned in the sea or along the coastline are collected for a minimum of one year and then used in atmospheric models at local scales, for example in the Wind Atlas Analysis and Application Program (WASP) and at regional scales, for example in the Karlsruhe Atmospheric Mesoscale Model (KAMM). Satellite synthetic aperture radar (SAR) imagery provides spatial patterns of wind speed, yet only as snapshots of various atmospheric situations. Regardless, SAR wind speed data may offer new possibilities for mapping offshore wind resources. SAR-derived sea wind maps may be estimated from empirical scatterometer algorithms that are valid for open sea conditions. Scatterometer wind retrieval algorithms are based upon statistical analysis of open-sea wind observations; medium-range forecast winds from weather models; and scatterometer data. Conventional scatterometers measure the normalized radar cross-section at several different aspect angles to infer wind speed and direction. Backscatter coefficients are physically related to wind speed through the roughness of the open sea. Sea roughness is generated by wind-wave interactions in the capillary and short gravity wave spectrum and additional parameters in fetch-limited seas may influence sea roughness compared to the open sea. Hence, SAR-derived wind maps may be biased in fetch-limited seas. Because SAR data provides only one backscatter value in each resolution cell, wind direction must be known a priori. A simple comparison of meteorological observations at a Danish offshore site and from an European Remote Sensing (ERS) SAR wind speed map retrieved using the CMOD4 algorithm shows promising results for wind retrieval from SAR images in coastal regions.