Abstract: Remote sensing satellite band setting,signal to noise ratio and sensor observation angle will affect the accuracy of crop extraction.In order to fully tap the advantages of Sentinel-2 satellite multispectral instrument and Landsat8 land imager in winter wheat information extraction.this study takes Shanghe County as the research area.Based on the combination data of spectral characteristics,texture characteristics and vegetation index characteristics of the two data sources,random forest classification and support vector machine are used to extract winter wheat.Experiments show that the optimal Kappa coefficient and optimal OA based on a single image are 0.89 and 95.13%,respectively.The optimal Kappa coefficient based on the combined data source is 0.92 and the optimal OA is 95.28%.The accuracy of the combination of two data sources is better than that of the single data source.The data combination effect is related to the performance of the classifier.The kappa coefficient of RFC is increased by 0.04,0.20 and 0.11 compared with SVM,and OA is increased by 2.41%,11.31% and 6%,respectively.The extraction accuracy of RF for winter wheat is better than that of SVM.This study is of great significance for constructing a typical crop classification and extraction system based on medium-high resolution image combination.

Key words: Landsat 8;Sentinel-2;multiple features;wheat extraction;RF;SVM