Winter wheat extraction using curvilinear integral of GF-1 NDVI time series

As one of the major crops in China, the winter wheat production is directly related to the national economic development, the social stabilization and the food security. Normalized difference vegetation index (NDVI) time series has been widely used in crop identification, while most of the present researches about NDVI time series focused on moderate or low resolution remote sensing images, which affecting the accuracy of winter wheat extraction. With the successful launch of the first satellite GF-1 of China High-resolution Earth Observation System, more possibilities have been provided for construction of NDVI time series with high time resolution and high spatial resolution. Considering the peculiarity of winter wheat, which curvilinear integral of the NDVI time series different from other crops, this can be used for identification of winter wheat. So the paper present a high precision winter wheat identification method, Curvilinear integral method, which makes full use of phenology characteristics of winter wheat based on curvilinear integral of NDVI time series. This method is technologically easy and apparently effective.