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.