The objective of the study was to examine suitable remote sensing methods and data for mapping and measuring the acreages of active crop lands in order to improve irrigation management. We compared classification results from a supervised classification method and a method using normalized difference vegetation index (NDVI) with additional pre-classification processing. IKONOS and Landsat Enhanced Thematic Mapper Plus (ETM+) images were tested to see if high spatial resolution remote sensing data would have significant advantages in distinguishing between active and fallow lands. The classification achieved an overall accuracy of 93.63%. The results showed that the supervised classification did not have a clear advantage over the simple method using NDVI at the level of distinguishing between active crops and fallow lands. The result suggests that using ETM+ instead of IKONOS high spatial resolution imageries is appropriate because of the high cost of IKONOS imageries and image heterogeneity of agricultural fields. It was shown that pre-processing with a mask to exclude the non-agricultural objects blended with agricultural fields is critical.