Abstract: This study aims to propose an extraction method of sugarcane planting in large area using remote sensing data. Taking Guangxi Zhuang Autonomous Region, Yunnan Province, Hainan Province and Zhanjiang City in Guangdong Province as the study areas, the time-series Chinese HJ- 1 CCD images were obtained covering the sugarcane growing period in the study areas. The decision tree classification method was applied on the base of the time-series NDVI threshold for sugarcane mapping over the large areas during 2014/2015 sugarcane harvest year. The overall accuracy was 87.5% compared with the statistics of local agricultural department. The independent field survey sampling points were used to evaluate the classification accuracy in Zhanjiang City. The confusion matrix analysis showed that the overall classification accuracy was 93.2% and the Kappa coefficient was 0.81. The results showed that this method was feasible, efficient, and applicable in extracting the planting area of sugarcane in southern China.