Remote sensing of factory stack and cooling tower plumes has the potential to reveal information about the constituents of the plumes. In the case of factory stacks, the determination of the chemical makeup and concentration of the plume may help determine the products produced by the factory. In the case of cooling towers, the temperature and water droplet characteristics may reveal information about the power output of the station. Synthetically generated images will help in the investigation of plume phenomenology and further help in the understanding of remote sensing of plumes. Using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) ray tracing code, these synthetic images can be used to predict sensor performance under various conditions and provide a way to test remote sensing algorithms. DIRSIG is a radiometrically correct ray-tracer which was developed at Rochester Institute of Technology by Digital Imaging and Remote Sensing (DIRS) laboratory. With this tool synthetic scenes can be rendered to test sensor performance under various conditions. Algorithms designed to determine effluent concentrations can be tested on these images to determine their accuracy and robustness. Synthetic plume imagery also reveals how plumes interact with the background and surrounding atmosphere. Sensitivity studies using passive remote sensing can provide information on plumes over a wide spectral band and with the use of multispectral image fusion additional information may be gathered. These studies are done on the plume-background contrast based on changes in the plume characteristic. Using inverse algorithms with DIRSIG, plume characteristics, such as species and concentrations, can be determined.
Chang, Chia, "Evaluation of inversion algorithms on DIRSIG generated plume model simulations" (1998). Thesis. Rochester Institute of Technology. Accessed from
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