HISCALENGACALTP

The proposed experiment will test the feasibility of incorporating atmospheric models (expected to be run during HI-SCALE) to improve simulation algorithms of image collection. The simulation algorithms are being developed at the National Geospatial-Intelligence Agency (NGA). NGA's simulations, based on the DIRSIG and MODTRAN programs used by the image science community, do not currently model changing atmospheric parameters at high spatial resolution. This experiment will apply new models of atmospheric dynamics, clouds, and precipitation or other features that impair image interpretation. The new models may be able to help predict image quality for future collections, assist in correcting image product artifacts, and aid in understanding scene content and artifacts of historical imagery, by accounting for fine-scale atmospheric conditions occurring at the time of collection. The new atmospheric models have been applied to data collected at ARM during RACORO in 2009, and this will be a similar experiment that will include measurements of calibration objects placed on the ground during HI-SCALE.

The calibration objects may include spectral panels, tarps with various color patterns, metallic objects of known material composition, heated surfaces (such as hot plates or camp stoves), and space blankets. The objects will make it possible to compare simulated image products with real image products, to see if the high-resolution atmospheric models improve the thermal and spectral accuracy of the simulations. Spectral and thermal properties of the calibration objects will be recorded ahead of time in a laboratory, and on the ground with handheld instruments.

This proposal represents a practical application of ARM's mission of improving representation and understanding of clouds and aerosols, as well as other atmospheric parameters. The intention is to characterize with greater accuracy the contribution of atmospheric effects, such as clouds, aerosols, moisture, and temperature, to artifacts that appear in imagery. If the experiment succeeds, it may lead to simulations of image collection that will be higher in spatial resolution, and more accurate in representing dynamical effects, than current models. Various agencies in the intelligence community and Department of Defense would be able to apply the results to mission tasking and product interpretation.

Timeline

Campaign Data Sets