The National Wetlands Inventory (NWI) produces information on the characteristics, extent, and status of the Nation's wetlands and deepwater habitats. NWI utilizes conventional photo-interpretation techniques and now incorporates on-screen digitizing from 1: 40,000 to 1: 80,000 maps. Although the NWI system of detecting and mapping wetlands is very accurate, it is not free of bias. Delineation is based on a subjective interpretation of the aerial photographs by people trained in recognizing wetlands. An integration of the modern NWI methodology used in recent updating with remote sensing tools can eliminate some of the bias, and increase the speed and consistency of the mapping update. The purpose of this study is to illustrate the potential of two-directional analyses and the complementarities of two data products: NWI wetland maps and Advance Spaceborn Thermal Emission and Reflection Radiometer (ASTER) images. We will test an approach for incorporating information from both the NWI maps and the ASTER satellite images, such that each could contribute to the overall knowledge gain rather than assuming that one data set is more accurate than the other. Images from spring, summer and fall will be classified to one of three levels: upland vs. wetland; wetland-treed vs. wetland-shrub vs. wetland-herb vs. aquatic beds; and species type within wetlands. A Normalized Euclidean distance will be computed for the classified image at each classification level in order to eliminate the noise caused by pixel-mixing. A compound topographic index (CTI) will be calculated from digital elevation models and overlaid with digital soil survey and topographic data and combined with the NWI maps, and a coincidence table produced. We expect the relationships to be specific to the upper and middle Coastal Plain provinces of Virginia but hope to extrapolate the methods for adaptation to other areas where ASTER data and updated NWI maps are available.