Abstract: With the successful launching of high-resolution satellites of the China High-Resolution Earth Observation System, the remote sensing images obtained will be increasingly applied for information gathering on crop planting. At present, limited studies were conducted on crop classification and yield estimation using the GF-1 satellite images based on the Normalized Difference Vegetation Index(NDVI). The NDVI transmissions tended to be over-crowded and low in resolution for the southern part of China due to the high vegetation growth in the areas.The proposed method utilized the improved Enhanced Vegetation Index(EVI) time series of GF-1 Wide Field View (WFV) images to overcome the deficiency. Lezhi county in Sichuan province was chosen for our testing.The GF-1/WFV images encompassing the entire rice growth period were acquired to construct the EVI time series.The characteristic EVI curves were obtained for the rice crops covering different growth stages. The Harmonic Analysis of Time Series(HANTS) method was adopted to smooth the EVI time series and maximally reduce the noise to enable reliable reflection of the dynamic changing patterns of rice and other crops or non-crop objects. Thereby, with the aid of the decision tree model, the rice planting area and other relevant information could be extracted. Comparing the results with what was obtained by the geographical conditions monitoring during a same time frame, the current method was considered accurate and precise. The GF-1/WFV images were particularly superior to the moderate or low resolution satellite images for gathering information on rice planting area in the regions where rice fields are scattered widely. The GF-1 technology was believed to represent a significant potential for applications in the field of agricultural remote sensing.