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Proceedings Paper

Hyperspectral monitoring of chemically sensitive plant sentinels
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Paper Abstract

Automated detection of chemical threats is essential for an early warning of a potential attack. Harnessing plants as bio-sensors allows for distributed sensing without a power supply. Monitoring the bio-sensors requires a specifically tailored hyperspectral system. Tobacco plants have been genetically engineered to de-green when a material of interest (e.g. zinc, TNT) is introduced to their immediate vicinity. The reflectance spectra of the bio-sensors must be accurately characterized during the de-greening process for them to play a role in an effective warning system. Hyperspectral data have been collected under laboratory conditions to determine the key regions in the reflectance spectra associated with the degreening phenomenon. Bio-sensor plants and control (nongenetically engineered) plants were exposed to TNT over the course of two days and their spectra were measured every six hours. Rochester Institute of Technologys Digital Imaging and Remote Sensing Image Generation Model (DIRSIG) was used to simulate detection of de-greened plants in the field. The simulated scene contains a brick school building, sidewalks, trees and the bio-sensors placed at the entrances to the buildings. Trade studies of the bio-sensor monitoring system were also conducted using DIRSIG simulations. System performance was studied as a function of field of view, pixel size, illumination conditions, radiometric noise, spectral waveband dependence and spectral resolution. Preliminary results show that the most significant change in reflectance during the degreening period occurs in the near infrared region.

Paper Details

Date Published: 18 August 2009
PDF: 8 pages
Proc. SPIE 7457, Imaging Spectrometry XIV, 74570G (18 August 2009); doi: 10.1117/12.828112
Show Author Affiliations
Danielle A. Simmons, Rochester Institute of Technology (United States)
John P. Kerekes, Rochester Institute of Technology (United States)
Nina G. Raqueno, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7457:
Imaging Spectrometry XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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