Abstract: It is more important for spatial imformation discription of highresolution remote sensing image to improve the precision of textural features choosing. In this study, the factors to influence the textural features choosing were analyzed and the results showed that the moving window size was the main factor to affect the obtaining processes of textural features based on the Gray Level Cooccurrance Matrix method. For the highresolution remote sensing image, the most proper moving window size was determined from 9×9 to 15×15. By the calculation of OIF values, the textural features of ME，HO and CR were chosen to be best combination for the size of 3×3 and 5×5, and the combination of VA，HO and CR was considered the most properly for the moving window size from 7×7 to 17×17. Finally, if the moving window size was chosen larger than 17×17, the best combination of VA，CO and SM can be chosen. Precision assessment of different textural combinations showed that VA,HO,CR combination with optimal moving window size(from 9×9 to 17×17) could evidently improve the classification precision for highresolution remote sensing image.