Eleven Radarsat scenes imaged between 22 September 1996 and 28 February 1998 were analyzed to delineate flood inundation in the forests of the Roanoke River floodplain, North Carolina. Threshold a" values distinguishing flooded from nonflooded forests were identified using classification trees. Data from 13 US Geological Survey IUSGS) wells located throughout the floodplain were used to validate the flood mapping with an overall accuracy of 93.5 percent. Images from both leaf-on and leaf-off periods were acceptable for detectingflooding, although the leaf-off scenes were classifed with higher accuracy than were the leaf-on scenes (98.1 percent versus 89.1 percent). In addition, threshold u0 values were lower for leaf-on scenes. The results also indicate that Radarsat data can be used to detect minimal flood levels-sites with water stages between 10 cm below and 10 cm above the forest floor were classified with 90.6 percent accuracy, Radarsat data are effective and appropriate for flood inundation mapping in forests, regardless of season or water level.