Synthetic image generation of chemical plumes for hyperspectral applications

Abstract

Remote sensing of factory stack plumes may provide unique information on the constituents of the plume. Potential information on the chemical composition of the factory products may be gathered from thermal emission/absorption in the infrared. We have developed a new model for generating synthetic images of plumes as viewed from a hyperspectral sensor using DIRSIG, a radiometrically based ray-tracing code. Existing plume models that describe the characteristics of the plume (constituents, concentration, and temperature) are used for input into DIRSIG. Ray-tracing is done for the scene that accounts for radiance from the plume, atmosphere and background, as well as any transmissive effects. Observations are made on the interaction between the plume and its background and possible effects for remote sensing. Images of gas plumes using a hyperspectral sensor are illustrated. Several sensitivity studies are done to demonstrate the effects of changes in plume characteristics on the resulting image. Inverse algorithms that determine the plume effluent concentration are tested on the plume images. A validation is done on the gas plume model using experimental data collected on a SF6 plume. Results show the integrated plume model to be in good agreement with the actual data from five to one hundred meters from the stack exit. The validity and limitations of these models are discussed as a result of these tests.