Forecasts for Adaptive Sensor Tasking in the Infrared (FASTIR)

Satellite ground imagery from space-based infrared (IR) sensors can be invaluable when monitoring areas of military significance during periods of rapid activity of several hours to days. IR ground imagery is strongly influenced by weather conditions such as cloud cover and water content that can adversely impact surveillance. Predictions of IR image availability and quality during adverse weather conditions can be critical in making decisions for real-time sensor management and adaptive sensor tasking to detect targets of interest. To provide such a predictive capability, we propose to develop the Forecasts for Adaptive Sensor Tasking in the Infrared (FASTIR) modeling system to provide 72-hour forecasts of remotely sensed IR images. The FASTIR approach is to directly propagate the satellite imagery forward in time using weather forecast information. Ground surface properties are derived from the imagery as the initial condition. FASTIR processing will entail using atmospheric correction, temperature-emissivity separation, and constructing the IR image using radiation transport codes. In Phase II, these FASTIR model elements will be fully implemented and integrated to forecast satellite IR imagery for any desired location on the earth surface.