Current events clearly demonstrate that chemical and biological threats against the public are very real. Automated detection of chemical threats is a necessary component of a system that provides early warning of an attack. Plant biologists are currently developing genetically engineered plants that de-green in the presence of explosives (i.e. TNT) in their environment. The objectives of this thesis are to study the spectral reflectance phenomenology of the plant sensors and to propose requirements for an operational monitoring system using spectral imaging technology. Hyperspectral data were collected under laboratory conditions to determine the key spectral regions in the reflectance spectra associated with the de-greening phenomenon. The collected reflectance spectra were then entered into simulated imagery created using the Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. System performance was studied as a function of pixel size, radiometric noise, spectral waveband dependence and spectral resolution. It was found that a framing array sensor with 40nm wide bands centered at 645 nm, 690 nm, 875 nm, a ground sample distance of 11cm or smaller, and an signal to noise ratio of 250 or better would be sufficient for monitoring bio-sensors deployed under conditions similar to those simulated for this work.
Library of Congress Subject Headings
Chemical detectors--Remote sensing; Multispectral photography
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Simmons, Danielle, "Hyperspectral monitoring of chemically sensitive plant sensors" (2013). Thesis. Rochester Institute of Technology. Accessed from
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