Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 11 5 2007 10.5194/hess-11-1609-2007 http://www.hydrol-earth-syst-sci.net/11/1609/2007/ http://www.hydrol-earth-syst-sci.net/11/1609/2007/hess-11-1609-2007.html http://www.hydrol-earth-syst-sci.net/11/1609/2007/hess-11-1609-2007.pdf 1609 1620 2007-09-27 Unsupervised classification of saturated areas using a time series of remotely sensed images D. A. de Alwis Z. M. Easton H. E. Dahlke W. D. Philpot T. S. Steenhuis tss1@cornell.edu Department of Biological and Environmental Engineering, Riley-Robb Hall, Cornell University, Ithaca, NY 14853, USA School of Civil and Environmental Engineering, Hollister Hall, Cornell University, Ithaca, NY 14853, USA The spatial distribution of saturated areas is an important consideration in numerous applications, such as water resource planning or siting of management practices. However, in humid well vegetated climates where runoff is produced by saturation excess processes on hydrologically active areas (HAA) the delineation of these areas can be difficult and time consuming. A technique that can simply and reliably predict these areas would be a powerful tool for scientists and watershed managers tasked with implementing practices to improve water quality. Remotely sensed data is a source of spatial information and could be used to identify HAAs. This study describes a methodology to determine the spatial variability of saturated areas using a temporal sequence of remotely sensed images. The Normalized Difference Water Index (NDWI) was derived from medium resolution Landsat 7 ETM+ imagery collected over seven months in the Town Brook watershed in the Catskill Mountains of New York State and used to characterize the areas susceptible to saturation. 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