Winter wheat identification based on MODIS data and Fuzzy-ARTMAP

Terra/MODIS has spectral and spatial resolution advantage over NOAA/AVHRR. A method of automatical crop identification on large-scale was set up applying spectral analysis, selecting appropriate bands and using time series characteristics with overall remote sensing images. In the paper, winter wheat identification in North China was taken as an example. First, according to winter wheat phonological stage, the best time phase of identification is at the sowing stage and tillering stage. Second, according to the spectral and biological characteristics of the crop, the spectral reflectances of MODIS were analyzed. One of them, red, blue, NIR and ESWIR bands were selected as working bands for winter wheat identification. And land surface water index(LSWI), which is defined by NIR and ESWIR, enhanced vegetation index(EVI),which is defined by Red, NIR and Blue bands, and EVI21, which is defined by the difference EVI of the two time phase images were used as characteristic parameters to improve the precision. Finally, fuzzy-ARTMAP algorithm was used for winter wheat identification. To verify the result, one Landsat TM was used to verify its precision. The result shows that the precision reaches 85.9%. This shows that it can obviously improve accuracy of crop identification with spectral analysis and times series, and especially the identification time can be advanced for more than three months compared with traditional method, which thinks the best identification time of winter wheat is in March. So it can provide a better operating method for agricultural condition monitoring with remote sensing and information service system at national-level.