During the Great Flood of summer 1993 in the Upper Mississippi Valley, the European Remote Sensing Satellite (ERS-1 ) imaged overbank ooding with a ground resolution of ca 25 m. When combined with topographic information, these data permit measurement of instantaneous longitudinal pro® les of individual¯ooded valleys. Along a major tributary to the Mississippi in southwestern Wisconsin, a measured in-transit¯ood wave exhibits an amplitude of 1´5± 2´0 m, and can be di erentiated from a constant discharge, step backwater-modelle d water surface for a distance of 5 km along the valley.

Satellite imagery classification is useful for a variety of commonly used applications, such as land use classification, agriculture, wetland delineation, forestry, geology, and landslide potential. However, image classification for physical properties of surface soils, such as strength or bearing capacity, is often obscured by other surface conditions, such as moisture and vegetation, although these are also indicators of soil strength. This project used remote methods of terrain analysis to search for areas suitable for vehicle or aircraft maneuverability based on slope, roughness, vegetation, soil type, and wetness and also performed direct classification of imagery based on soil strength. Using a maximum likelihood supervised classification approach, trained by a limited amount of ground-truth strength measurements, a soil strength classification was applied to WorldView-2 multispectral satellite imagery. This paper presents the work done on the imagery classification for soil strength, the apparent relationship between the reflectance and soil strength, and the ongoing work to expand the technique to new imagery by using existing training sets.

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A goal of the Air Force Research Laboratory Opportune Landing Site (OLS) program was to locate large, smooth, flat, obstructionfree areas safe for aircraft operations. The ERDC was tasked to evaluate the quality of OLSs as located by OLS Multi-Spectral (OLS-MS) software that was developed by the Boeing Company and uses Landsat multispectral imagery. ERDC conducted extensive field work evaluating OLSs in Indiana, New Mexico, and California. However, while seeking these OLS-MS-selected field sites, many other software-selected potential OLSs were casually observed not to satisfy requirements with regard to obstructions. Our objective was to evaluate a statistically valid sample of OLSs for freedom from obstructions. We utilized OLSs located by the final version of the OLS-MS software, plotted them over orthophotoquads, and assessed their intersections with obstructions within geographic information system (GIS) datasets containing natural and cultural features. A sample of OLSs was also visually evaluated to assess the accuracy of the GIS analysis process. Features in the GIS datasets often did not correspond exactly with features on the ground, a source of analysis error that may be due to digitizing uncertainty and differences in the creation dates of the images and datasets. The success of the OLS software in avoiding obstructions is presented in the results.