Crop discrimination with multitemporal SPOT/HRV data in the Saga Plains, Japan

Nine scenes of SPOT/HRV data obtained in eight different months in 1997 wer e evaluated for crop discrimination in the Saga Plains, Japan. All images w ere atmospherically corrected with the 6S code. Annual Normalized Differenc e Vegetation Index (NDVI) profiles were generated to characterize seasonal trends in six cropping systems (rice, rice-winter cereal, soybean, soybean- winter cereal, lotus, and rush). The dataset of this study showed the uniqu e temporal change patterns of NDVI for each cropping system. Separability a nalyses determined optimal scene combinations for the highest accuracy in c lassifying the cropping systems. The scene combinations for the accurate cl assification of cropping systems were obtained from three separability meas urements (Euclidean spectral distance, divergence, and Jeffries-Matsushita distance). Kappa statistics were applied to evaluate the classification acc uracies. The four-scene combination that was derived from April, June, July and September classified the cropping systems almost as well as those comb inations including more scenes. A colour composition technique applied to t he three-scene combination that showed the highest separability also discri minated each cropping system. Based on these results, we can request observ ations during specific time intervals considering local crop calendars and environmental conditions.