The traditional Fourier Descriptors（FDs） are normalized in this paper to make it independent of translation

rotation and scale changes.Four typical objects i.e.building

paddy

road and river are selected and their boundaries are expressed as sequences of complex numbers.FDs are obtained through one-dimensional Fourier transform.The characteristics of the frequency spectrum

contribution rate and the shape reconstruction are analyzed.The results show that the different frequency ranges have different contribution rates;the Direct Component（DC） reaches a proportion of more than 70%;the Low Frequency（LF） and High Frequency（HF） totally reach 7%-24%while the Medium Frequency（MF） merely 2%-4%.The LF components（descriptors 1—5） make a commendable reconstruction of objects’ shape and these descriptors are applied to the object-oriented classification.The overall classification accuracy is 98.48%with a Kappa coefficient 0.9714.