Abstract
To meet the demand of large-scale agricultural monitoring system with remote sensing, extracting crop area planted must
be rapid, precise and reliable. In this paper, winter wheat identification with MODIS data in 2004 is taken as example in
North China. Applying spectral analysis and integrating genetic algorithm with neural network (GA-BP) is proposed,
which gives attention to two optimization algorithm, genetic algorithm and back propagation algorithm. According to the
spectral and biological characteristics of winter wheat, Red, Blue, NIR, ESWIR, LSWI, EVI are selected as characteristic
parameters. Then GA-BP algorithm is used for winter wheat identification. Results show that compared with maximum
likelihood and back propagation neural network classification algorithm, the GA-BP algorithm can not only run with
better efficiency, but also achieve best accuracy of identification. Therefore, it is the operational method for agricultural
condition monitoring with remote sensing and information service system at national level.
