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Large scale management of spatial distribution of oilseed rape is essential for grain yield estimations, ensuring edible oil supply and sustainable agricultural management. Flowering period is the special growth stage of oilseed rape. Spectral feature of oilseed rape in this period changes largely. Furthermore, the sense of sight for oilseed rape also has a big difference against with other vegetation types during flowering period. Thus, spectral feature and color feature in the flowering stage can be set as the unique features for identifying oilseed rape as well as the basis of oilseed rape extraction. NGVI, a flowering-contained detecting indicator, was used to represent spectral feature of oilseed rape in the flowering period. H, S and V components were conducted as color feature of oilseed rape after processing colorimetric transformation from RGB color space to HSV color space. And then, the samples of oilseed rape and non-oilseed rape, which were interpreted on wide field view (WFV) images from Gaofen satellite no.1 (GF-1) combined Google Earth images and field investigation, were analyzed to determine the thresholds of NGVI, H, S, and V successively. Afterwards, oilseed rape in Hubei Province of China in 2016 was extracted based on GF-1 WFV images that obtained in full-flowering stage, which was evaluated by confusion matrix and compared with traditional support vector machine (SVM) method. Meanwhile, the GF-1 WFV-estimated planting acreage of oilseed rape was validated against agricultural census data. As a result, the sample evaluation achieved 94.51% of overall accuracy and 0.89 of Kappa coefficient, which improved four percentage points and 0.1 compared with SVM method, respectively. The result against statistical data had -14.14% of relative error at provincial level as well as 0.837 (n=17) and 0.738 (n=83) of decision coefficients at municipal level and county level. Moreover, the method was applied on panchromatic and multi-spectral (PMS) image from GF-2 and validated by reference oilseed rape map. The relative error of oilseed rape extraction was -8.33% and spatial consistency was 91.67%. Therefore, this study proposed a simple, effective and robust oilseed rape extraction strategy in large-regional scale based on satellite imagery of full-flowering period.