Comparison of Winter Wheat Classification using Multi-Temporal IRS-P6 Images

The objective of this study is to measure the area of the winter wheat based on the multi-temporal middle resolution remote sensing images and the database of farmland parcel, and then compare the classification accuracy under the different amount of information. The study firstly analyzed the different crop samples in the support of field data, and then classified the images by the three different ways of NDVI threshold segmentation. The classification accuracies were compared in the three conditions of information amount: single-temporal image in November 19 in 2007, three-temporal image and three-temporal image with database of farmland parcel in Beijing in 2006. The results indicate that single-temporal image reveals the low classification accuracy. The multi-temporal images efficiently distinguish wheat from others plants. Moreover, the accuracy could be further improved if the database of farmland parcel was used to rule out the non-cultivated land.