Identification of hydrologically active areas in the landscape using satellite imagery

The reduction of non-point source (NPS) pollution is a focus of many watershed management programs. In temperate humid climates most NPS pollution originates from Hydrologically Active Areas (HAAS) which are wetter areas in the landscape that saturate during rainstorms and generate most surface runoff. Successful implementation of best management practices for reducing NPS pollution requires knowledge of the locations of the HAAs. Remotely sensed data is a source of spatial information and could be used to identify HAAs, but there is not a satisfactory procedure for doing so. The objective of this dissertation is to develop such a procedure by first determining landcovers types and then using the temporal variability within a landcover type to identify HAAs.; In the first two chapters a landcover map was developed for three small watersheds under 50 km2 and one larger (approximately 15,170 km2) area using greenness variation expressed as NDVI values in seven remotely-sensed Landsat 7 ETM+ images. Each image represented a distinct plant growth stage. The NDVI data were clustered into homogeneous regions having similar NDVI patterns over time and assigned to a landcover type. The derived landcover map for the three small watersheds compared well with existing landcover maps and low-altitude air-borne imagery. The same method was then applied to the larger area. After clouds and lakes were taken out, a landcover map was produced with an accuracy of 69% when compared to field data.; In the last chapter the temporal variability within a landcover type of a remotely sensed wetness index was employed to determine the HAAS by grouping areas that behaved alike. The resulting HAA map agreed well with both observed and spatially distributed computer simulated moisture contents. In summary, the procedure for finding HAAS is a promising tool for delineating runoff producing areas in the landscape.