The Remote Sensing and Fluorescence Labs at ERDC-Research Division are engaged in basic and applied research in fluorescence, reflectance, and thermal sensing for terrain and environmental understanding. Examples of research foci are: 1) the development and modeling of fluorophores as target materials for LiDAR 2) the collection and analysis of reflectance to support hyperspectral imaging, 3) thermal short- and longwave emissive spectroscopy and imaging, 4) distributed sensing and 5) understanding of vegetative fluorescence compounds.
The Lab’s capabilities include development and spectral characterization of luminescent materials for LiDAR and hyperspectral targeting. Additionally, the lab has demonstrated novel ways to improve signal to noise levels of fluorophores (improved quantum efficiency) for recovery by synoptic sensors. The Lab has also developed a new fluorescence lifetime imager called SeePhase, which represents a revolutionary way to characterize luminescence in the imaging domain.
The Lab has support technologies to measure both steady-state and lifetime (decay) fluorescence spectra. Using state-of-the art spectrometers and lasers including both a frequency-domain lifetime spectrofluorometer, and a TCSPC system the Lab can measure fluorescence decays in the picosecond to microsecond range. The Lab also has incorporated instruments to characterize reflectance and thermal phenomena including VIS_NIR_SWIR hyperspectral cameras, a broadband TIR camera and a hyperspectral TIR spectrometer.
- Anderson, J. , R. Massaro, L. Lewis, R. Moyers, and J. Wilkins. 2010. Lidar-activated Phosphors and Infrared Retro-Reflectors: Emerging Target Materials for Calibration and Control. Photogrammetric Engineering and Remote Sensing. 2010, vol. 76, n8, pp. 877-881.
- Naumann, J.C., J.E. Anderson and D.R. Young. 2010. Remote detection of plant physiological responses to TNT soil contamination. Plant and Soil 329: 239-248.
- Naumann, J.C., J.E. Anderson and D.R. Young. 2008. Linking physiological responses, chlorophyll fluorescence and hyperspectral imagery to detect salinity stress using the physiological reflectance index in the coastal shrub, Myrica cerifera. Remote Sensing of Environment, 112: 3865-3875.
- Nelson, J., J. Zinnert (Naumann), J. Anderson, E. Mendoza and D. Young. 2010. Remote Lifetime Imaging – Advanced Technology for Vegetation Fluorescence Sensing. Proceedings of the 4th International Workshop on Remote Sensing of Vegetation Fluorescence, November 15-17, 2010, Valencia.
- Smith, C. and Tabb, J. 2011. Encapsulated Fluorescent Bioprobes for theDetection of Explosive Materials in Soil. J. of EWR & Mine Action. Spring Issue (15.1), 73-75.
- Smith, C., Edwards, J., and Fisher, A. 2010. TCSPC Lifetime Characterization of Bacillus endospore Species. IEEE. SPIE DSS. Proc. of SPIE Vol. 7687 76870B-1.
- Smith, C., Anderson, J., Edwards, J. and Kam, K. 2011. In-situ Surface Etched Bacterial Spore Detection using DPA-Eu-Silica Nanoparticle Bioreporters. Applied Spectroscopy. August 65(8).
- Massaro, R.D., Dai, Y, and Blaisten-Barojas, E. 2009. Energetics and Vibrational Analysis of Methyl Salicylate Isomers. Journal of Physical Chemistry A, 113: 10385-10390.
Points of Contact
(703) 428-6698, LiDAR, Hyperspectral
(703) 428-6789, Autonomous Sensors
(703) 428-3636, Luminescence Sensing
(703) 428-3644, LiDAR, Hyperspectral, Modeling
(804) 828-0079, Plant Physiology, Terrain
(703) 428-7428, Thermal Spectroscopy, Imaging
SeePhaseTM, Remote Fluorescence Lifetime Imaging: SeePhaseTM, a first-of-its-kind prototype, is an imaging system which remotely acquires, processes, and displays the unique lifetime fluorescence response of interrogated material, which is dependent upon its chemical composition. This first-generation system is presently undergoing ERDC operational applications testing, including: 1) direct and surrogate detection of CBRN threat agents and volatile contaminants, 2) intrinsic vegetation-related optical signs reflective of stress and disturbance, 3) foliage cover and concealment, and 4) various tagging, tracking and locating (TTL) applications using fluorescence decay.
Innovative studies of Vegetation Stress via Fluorescence and other Optical Measures: Leaf-level biochemical processes are being linked to landscape level remote sensing signals. Chlorophyll fluorescence, hyperspectral reflectance and thermal imagery are used to examine plant physiological responses to the environment. This work varies from natural stress detection (drought and salinity) to plants as indicators of soils contaminated with hazardous materials, such as explosives. Current research is focused on using optical signatures to discriminate natural from anthropogenic stress.
Thermal infrared (TIR): Broadband imaging is currently being used to identify and characterize plant stress. Grass exhibits an increase in temperature during periods of stress when compared to a non-stressed control. A thermally controlled blackbody is used for calibration of the instrument.
LiDAR Materials Research for Calibration, Tagging and Tracking: Phosphors and retro-reflective materials are being developed and used to work with current and future LiDAR (Light /Laser Distance and Ranging) Systems. LiDAR is seen as a fast-moving remote sensing tool that provides topographic range and geometric data, but is also capable of activating optical targets as shown below.
AQUA PATH and WATCHMAN: AQUAPATH (Autonomous Querying Threat Agent Sensor for Potable Water Handling) is a biosensing system comprised of a cluster of water quality buoys that report in a geospatial wireless network. It utilizes fluorescence-based biotechnology and optical reporting as the sensor modality for detection. AQUAPATH is focused on detection of water quality parameters for developing geospatial models of the environment and recovery of potable water supplies via remote sensing that are relevant to military or civil communities. WATCHMAN (Wireless AuTonomous Contaminant Hazard Monitoring Network) broadens the transition of the AQUA PATH system anthology that demonstrates transitional developments and recommendations for the selection of new innovation in multi-sensing technology called HYDRA. The geospatial network backbone is comprised of a mature design and construction that is aimed at expanding a new suite of sensor modalities comprised of additional chem.-bio sensing components including Silver HAWQTM, global positioning, regional weather data input, and wide ranging wireless network capabilities.