Capsule Summary We briefly review the use of Observing System Simulation Experiments in the U.S. and discuss their values and limitations, leading to an expert consensus on five recommendations for moving forward.

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This paper presents brief profiles of 19 airborne hyperspectral sensor systems currently or nearly available for data acquisition. These systems represent various design concepts and innovations in hyperspectral information collection technology. A number of companies now have the ability to acquire data from these systems. As the scientific and commercial communities become aware of hyperspectral imaging data acquisition opportunities, more applications for this type of data will be investigated and implemented. INTRODUCIIONAn airborne sensor system scans across a line on the ground, generating hundreds of individual pixels in each scan line (the X-axis); the airplane's forward motion generates the Y-axis. The optical system projects data onto several arrays so that all spectral information for a given area is recorded simultaneously (Baker, 199 1). Hyperspectral imagers split the spectrum into many separate, narrow channels on a pixel-by-pixel basis, allowing researchers to discern an area's composition through spectral signature discrimination more effectively than is possible with broad-band multispectral scanners .Airbome hyperspectral imaging represents an additional dimension for remote Earth observations. The technology appears to be advancing faster than applications are being found for the data generated. This paper will help make potential users aware of the available technology by profiling operational Airbome Hyperspectral Sensor Systems (AHSSs) and identifying data acquisition opportunities. TECHNOLOGYAHSSs were developed to achieve fine spectral resolution ( A M -1 -5%), high spatial resolution (1 -20m), image spatial 309 and spectral pattem data base development (30-200 channels), and spacebome imagery data simulation.Several types of scanning mechanisms can acquire both spatial and spectral dimensions for an area of coverage on the Earth. Scanning mechanisms include scanning, staring, scanningktaring, and staring arrays. The performance associated with varying these and other parameters of the hyperspectral system design can be modeled to obtain an indication of system characteristics. Performance modeling of system response characteristics, discrimination potential analysis, atmospheric constraints, and spectral signature normalization may be performed with sensor system design software (Jaggi, 199 1).An important system performance specification for many applications is signal-to-noise ratio (SNR) for optimizing peak-to-peak and peak-to-valley discrimination in signature matching algorithms. Current methods for estimating SNR methods include laboratory, dark current, image, and geostatistical procedures (Curran and Dungan, 1989). SYSTEM PROFILESAAHIS-I -SETS Technolow. Inc. The Advanced Airborne Hyperspectral Imaging System -1 ( M I S -I ) is being developed by SETS Technology, Inc. to demonstrate the value of very high quality hyperspectral imaging data for a variety of land surface and underwater applications. This fully funded system will first fly in May 1994 and should be available as a se...