Abstract: Remote sensing extraction technology for crops is a promising research method for remote sensing applications. However, it is limited by the spatial and temporal resolution of the remote sensing data; it is difficult to identify crops with similar spectral characteristics. In this study, the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) was used to fuse MODIS and Landsat data to obtain normalized difference vegetation index (NDVI) time series data of the Chahannur Basin with a temporal resolution of 8 days and a spatial resolution of 30 m. The correlation coefficient between the ESTARFM NDVI and the Landsat NDVI during the same period was 0.94. Harmonic analysis of the NDVI time series filter was used to smooth the ESTARFM NDVI data. Finally, the irrigated arable land was extracted using a support vector machine (SVM) with irrigated cultivated land samples. The results showed that the total area of irrigated arable land in the watershed is 1958.24 km². The total area of Shangdu, Xinghe, Shangyi, Kangbao, and Huade Counties accounts for 94% of the watershed, and the irrigated arable land is 616.67 km², 337.36 km², 409.85 km², 290.93 km², and 239.38 km², respectively. The region primarily grows sunflowers, beets, potatoes, and other long-growing crops from the beginning of April to the end of September and vegetables (including celery, Chinese cabbage, cabbage) from the beginning of May to the beginning of August. Cultivated land in Zhangbei, Chahar Youyiqianqi, Houqi, and Xianghuangqi Counties accounts for 6% of the total cultivated land in the basin, and the total irrigated land in the four counties is 64.05 km². Real sample verification indicates that the total classification accuracy is 93.18%, and the Kappa coefficient is 0.91. The results show that the NDVI time series obtained from the data fusion model reflects real changes in crops, and the use of SVMs to extract irrigation arable land in the Chahannur Basin is suitable.