Fourier analysis has a great amount of applications. For example, it appears to be a very suited tool for vineyard detection in aerial images, due to the periodic patterns induced by this culture. Vine-plot mapping and monitoring are crucial issues in land management, particularly for areas where vineyards are dominant, like in some French regions. In this context, the availability of an automatic tool for vineyard detection and characterization would be very useful. A method based on a local Fourier Transform has been developed to meet this need. Fast Fourier Transform is computed on a sliding window, providing information concerning vineyard presence in the window as well as an estimation of interrow width and row orientation. These characteristics are used to compute a homogeneous `Vine index', which allows a good discrimination of both class `vine' and `non-vine'. To foster large-scale applications, tests and validation were carried out on standard very high spatial resolution remote-sensing data. Using a plot based validation, 88% of the 114 vine plots of the study area were correctly classified and interrow width and row orientation were determinated with an average absolute difference with on screen measurements of respectively 2° and 6cm.