A new method of spatialization of crop area statistical data supported by remote sensing technology

Spatial information of crop area statistics is of great significance for study of global change, population, resources, environment, ecology and food security. In this paper, based on MODIS NDVI time series data and global optimization algorithm SCE-UA (Shuffled Complex Evolution-University of Arizona), the research of spatialization of crop area statistical data was carried out in 13 counties which were located in Shijiazhuang City of Huanghuaihai Plain. The research crop was winter wheat. At last, the accuracy of the result of spatialization of crop area statistical data crop was validated. The final results showed that the regional accuracy of optimal winter wheat distribution map was 99.71% and pixel accuracy kappa coefficient was 0.898. It proved that the method of spatialization of crop area statistical data using the NDVI time-series data and global optimization algorithm SCE-UA was reasonable and feasible. The spatial crop map with higher accuracy could be gotten using this method which was more significant to solve the spatialization of crop area statistical data.