Marine aquaculture is an important part of the marine economy in China. Synthetic aperture radar (SAR) images can work at all times, which makes them suitable for large-scale monitoring of aquaculture areas. However, SAR images from different regions often have obvious differences in background scattering, aquaculture structures, and imaging conditions. These differences cause serious domain shift problems and reduce the segmentation performance of existing methods in cross-region tasks. To solve this problem, this paper proposes a structure- and frequency-aware domain adaptation method (SFDA) for raft aquaculture extraction from SAR images. The method includes a directional structure alignment (DSA) module and a frequency domain alignment (FDA) module. The DSA module aligns the directional structure features between the source and target domains, while the FDA module aligns texture and scattering features in the frequency domain. Experiments on the Gaofen-3 SAR dataset from Jiangsu province show that the proposed method is effective for cross-region raft aquaculture extraction.