Abstract: Winter wheat is one of main food crops in China. Its planting acreage monitoring is basic information for wise management of plant natural resources. The Moderate Resolution Imaging Spectroradiometer(MODIS) is one detector board on Terra's (EOS-AM1), which was lunched on December 18, 1999 by NASA. It offers a unique combination of spectral, temporal, and spatial resolution compared with previous global sensors, making it a good candidate for large-scale winter wheat planting area monitoring. However, because of subpixel heterogeneity, the application of traditional hard classification approaches to MODIS data may result in significant errors in planting area estimation. The authors developed and tested a linear unmixing approach with MODIS data that estimates subpixel fractions of crop area based on the temporal signature of reflectance throughout the growing season. This method is based on multi-source data. First, the authors use IKONOS data classification result to instruct field work. Second, high accuracy classification results can be obtained in research areas from LANDSAT data. Finally, based on time-series data of TERRA /MODIS surface reflectance daily L2G global 250 m sin grid v004, using linear decomposition of mixed pixels for monitoring winter wheat planting area in Henan Province of China. Comparing with national statistic data, the relative error of wheat planting area is 5.25% in Henan Province in 2002. The accuracy of result can meet the requirements of agricultural monitoring. This research provides an operational approach for remote sensing monitoring of winter wheat acreage in China.