A High-precision Method for Fractional Wheat Area Mapping based on SMA and Optimal Temporal Endmember Selection - A Case Study in Luancheng, North China Plain

A high-precision method for mapping the fraction of wheat Area in Luancheng County, North China Plain is presented and validated. The method is based on a spectral mixture analysis model and a optimal temporal TM image election where six main endmembers (greenhouse , soil, wheat, roof, nursery garden, shadow), constitute the observed pixel reflectance from the satellite. Given the reflectance observation, the fractional wheat area(FWA) is solved from the spectral mixture analysis(SMA) model. The high-precision estimation for six endmember SMA can be expected at an optional temporal range, which is the last ten days of March month every year. The simple landcover in March month specifies the effect of best simulation on the FWA of TM image pixels while no disturbed vegetations have grown green leaves. This approach enables operational wheat planting area mapping for extensive areas with an almost 95% classification precision to sub-pixel level. Our study area covers 346 km2. comprising whole Luancheng County of Hebei Province. Applying SMA to Landsat/TM cloud-free data acquired on March 21th, 2004, we estimated the areal fraction of wheat cover for the whole County field. The validation against statistical data from the Luancheng County Statistic Bureau indicates that with finite SMA, 92.3% accuracy is gained. Better results were also obtained from the validation against statistical information, for example, 95.8% of wheat-covered area were recognized when heavy haze area-free TM image is applied. A general formula for deriving the fractional wheat planting area mapping provided by SMA is presented, too. It can be concluded that wheat planting area to sub-pixel level in NCP can been operatively monitored with limited endmember SMA in a good precision.