The policy of ecological return of cultivated land has been carried out for several years in China and the cultivated land is decreasing. The objective of this study is to explore the potential and the methodology for the cropland change detection with Discrete Fourier Transform (DFT) approach using high temporal resolution imagery and some ancillary data. The data used in this study are 10-day composite SPOT-4 VEGETATION (VGT) Normalized Difference Vegetation Index (NDVI) over the period from April to November in 1998 and 2002 respectively, and the ancillary data include the existing land cover dataset derived from TM images and agricultural phonological calendar. The DFT
method was applied to the NDVI data set on a per pixel basis. The magnitude of the difference of amplitudes in the first three harmonics was used to identify the areas where changes might occur, and then the unsupervised classification was used to determine the types of change. The methodology used in this study can minimize the influence of noise and phenology variance to the change detection. The result showed that the significant change of cropland and other land cover can be detected with this method.