In order to give consideration to the change information of summer maize planting area and spatial distribution in Huanghuaihai plain, the present paper combined statistical analysis and remotely sensed classification technology to extract summer maize based on MODIS EVI images. The results showed high accuracy (>67.35%) with the TM-derived in spatial distribution and high correlation coefficient with the agriculture statistics in planting areas at city level (R2>0.497 7). On this basis, change imagery was computed using image overlying algorithm based on binaryzated images derived from classification results in Huanghuaihai plain during 2000—2010. The change detection feature was analysed according to the plates in the region. The results show that the summer maize planting area increased significantly in huanghuaihai plain from 2000 to 2010. The planting area increased steadily in southern part during study year. In the northern part, it discreased from 2000 to 2003 and increased from 2003 to 2010. The most huge change occurred in the northern part in the period of 11 years. The planting proportion increased in the north of plain but decreased in the north. The new method can be widely used in regional dynamic detection and has a good applicability and accuracy.