This project aims to develop a hyperspectral remote sensing approach to detect potato virus Y (pathogenic virus of the family Potyviridae, PVY), from an Unpiloted Aerial Vehicle (UAV). The hyperspectral camera is mounted on the UAV to capture the reflectance of the pixels of the leaves and identify the subtle changes in the color as an indicator of the PVY. The PVY-infected plants tend to have visible mosaic patterns on the leaves, leading to a potential signal for optical detection. Managing the PVY is one of the priorities for the Montana Seed Potato Growers, necessitating the development of a rapid-detection system for PVY. We aim to evaluate if we can detect PVY from a UAV with a radiometrically calibrated hyperspectral sensor to measure upwelling radiance and a calibrated spectrometer to measure downwelling irradiance. We aimed to start with publicly available data from Wageningen University, Netherlands, to build a baseline for our model under controlled lighting. However, we encountered difficulty working with this data, and hope to revisit this portion of the effort in the future.
There are many interesting ways in which optics and meteorology intersect and provide cross-discipline learning opportunities. One example is the use of thermal imaging to illustrate the principles underlying urban heat islands (UHIs), found on scales from the mesoscale to the microscale, which give rise to increased temperatures in urban settings. The most common way of documenting such phenomena is through traditional meteorological measurements. This presentation describes the use of a thermal infrared imager to document and help explain micro-scale UHIs observed initially as a persistent difference in air temperature measured by two nearly identical weather stations separated by 2.79 km in Bozeman, Montana. Mobile meteorological measurements from a backpack-mounted weather station, carried throughout the surrounding area at different times of year and compared with the stationary campus weather station, verified the presence and scale of a micro-heat island. This also identified one such micro UHI that existed when the immediate surroundings contained man-made materials such as concrete and asphalt adjacent to natural vegetation. Thermal images from the radiometrically calibrated imager recorded the diurnal thermal signature of manmade and natural surfaces. The thermal images help to explain process that are occurring, whereas most traditional meteorological instrumentation may not provide process-based information. Time-series plots of the infrared brightness temperatures show that the man-made materials emit elevated levels of thermal radiation long after the end of direct solar heating, while natural vegetation quickly comes into thermal equilibrium with the ambient air. The combination of traditional and nontraditional instrumentation document and explain processes occurring in micro UHIs that vary rapidly in space with changing ground cover.
A hyperspectral imager was used to differentiate herbicide-resistant versus herbicide-susceptible biotypes of the agronomic weed kochia, in different crops in the field at the Southern Agricultural Research Center in Huntley, Montana. Controlled greenhouse experiments showed that enough information was captured by the imager to classify plants as either a crop, herbicide-susceptible or herbicide-resistant kochia. The current analysis is developing an algorithm that will work in more uncontrolled outdoor situations. In overcast conditions, the algorithm correctly identified dicamba-resistant kochia, glyphosate-resistant kochia, and glyphosate- and dicamba-susceptible kochia with 67%, 76%, and 80% success rates, respectively.
Getting students interested in science, specifically in optics and photonics, is a worthwhile challenge. We developed and implemented an outreach campaign that sought to engage high school students in the science of polarized light. We traveled to Montana high schools and presented on the physics of light, the ways that it becomes polarized, how polarization is useful, and how to take pictures with linear polarizers to see polarization. Students took pictures that showed polarization in either a natural setting or a contrived scene. We visited 13 high schools, and presented live to approximately 450 students.
Infrared thermal imaging is a valuable tool not only in science but also in optics and photonics education and outreach activities. Observing natural optical phenomena in a different spectral region like the thermal infrared often offers new insights. The commonly used false color images not only allow extraction of useful information about thermal properties of objects, but they can also provide aesthetic sights and are thus an excellent tool for public outreach activities. Recently we have pursued this kind of study using IR imaging within Yellowstone National Park, complementing earlier work on thermal pool colors and spectroscopy. We will discuss and compare images of a variety of VIS and IR cameras of hot springs, geysers, mud pools and other natural phenomena recorded in the park during 2012 and 2016.
As microbolometer focal plane array formats are steadily decreasing, new challenges arise in correcting for thermal drift in the calibration coefficients. As the thermal mass of the cameras decrease the focal plane becomes more sensitive to external thermal inputs. This paper shows results from a temperature compensation algorithm for characterizing and radiometrically calibrating a FLIR Lepton camera.
Nature provides many beautiful optical phenomena that can be used to teach optical principles. Here we describe an interdisciplinary education project based on a simple computer model of the colors observed in the famous thermal pools of Yellowstone National Park in the northwestern United States. The primary wavelength-dependent parameters that determine the widely varying pool colors are the reflectance of the rocks or the microbial mats growing on the rocks beneath the water (the microbial mat color depends on water temperature) and optical absorption and scattering in the water. This paper introduces a teaching module based on a one-dimensional computer model that starts with measured reflectance spectra of the microbial mats and modifies the spectra with depth-dependent absorption and scattering in the water. This module is designed to be incorporated into a graduate course on remote sensing systems, in a section covering the propagation of light through air and water, although it could be adapted to a general university optics course. The module presents the basic 1-D radiative transfer equation relevant to this problem, and allows them to build their own simple model. Students can then simulate the colors that would be observed for different variations of the microbial mat reflectance spectrum, skylight spectrum, and water depth.
Advances in microbolometer long-wave infrared (LWIR) detectors have led to the common use of infrared cameras that operate without active temperature stabilization, but the response of these cameras varies with their own temperature. Therefore, obtaining quantitative data requires a calibration that compensates for these errors. This paper describes a method for stabilizing the camera’s response through software processing of consecutive images of the scene and images of the camera’s internal shutter. An image of the shutter is processed so that it appears as if it were viewed through the lens. The differences between the scene and the image of the shutter treated as an external blackbody are then related to the radiance or temperature of the objects in the scene. This method has been applied to two commercial LWIR cameras over a focal plane array temperature range of ±7.2°C, changing at a rate of up to ±0.5°C/min. During these tests, the rms variability of the camera output was reduced from ±4.0°C to ±0.26°C.
Radiometric calibration methods are described that enable long-term deployment of uncooled microbolometer infrared imagers without on-board calibration sources. These methods involve tracking the focal-plane-array and/or camera-body temperatures and compensating for the changing camera response. The compensation is derived from laboratory measurements with the camera viewing a blackbody source while the camera temperature is varied in a thermal chamber. Results are shown that demonstrate absolute temperature uncertainty of 0.35 °C or better over a 24-hour period, with more than half of this uncertainty inherent in the blackbody source to which the measurements are compared. This work was driven by environmental remote sensing applications, but the calibration methods are also relevant to a wide range of infrared imaging applications.
This article [Opt. Eng.. 52, (6 ), 061304 (2013)] was originally published online on 7 January 2013 with an error in the numerator of Eq. (13) that propagated into Eqs. (14), (15), and (17). The corrected Eq. (13) and subsequent equations are given here:
Advances in microbolometer detectors have led to the development of infrared cameras that operate without active temperature stabilization. The response of these cameras varies with the temperature of the camera’s focal plane array (FPA). This paper describes a method for stabilizing the camera’s response through software processing. This stabilization is based on the difference between the camera’s response at a measured temperature and at a reference temperature. This paper presents the mathematical basis for such a correction and demonstrates the resulting accuracy when applied to a commercially available long-wave infrared camera. The stabilized camera was then radiometrically calibrated so that the digital response from the camera could be related to the radiance or temperature of objects in the scene. For FPA temperature deviations within ±7.2°C changing by 0.5°C/min , this method produced a camera calibration with spatial-temporal rms variability of 0.21°C, yielding a total calibration uncertainty of 0.38°C limited primarily by the 0.32°C uncertainty in the blackbody source emissivity and temperature.
A set of low-cost, compact multispectral imaging systems have been developed for deployment on tethered balloons for education and outreach based on basic principles of optical remote sensing. They have proven to be sufficiently capable, and they are now being used in research as well. The imagers use tiny complementary metal-oxide semiconductor cameras with low-cost optical filters to obtain images in red and near-infrared bands, and a more recent version includes a blue band. The red and near-infrared bands are used primarily for identifying and monitoring vegetation through the normalized difference vegetation index (NDVI), while the blue band can be used for studying water turbidity and so forth. The imagers are designed to be carried by tethered balloons to altitudes currently up to approximately 50 m. These undergraduate-student-built imaging systems are being used by university and college students for a broad range of applications in multispectral imaging, remote sensing, and environmental science.
The commercial development of uncooled-microbolometer, long-wave infrared (LWIR) imagers, combined with advanced radiometric calibration methods developed at Montana State University, has led to new uses of thermal imagery in remote sensing applications. One specific novel use of these calibrated imagers is imaging of vegetation for CO 2 gas leak detection. During a four-week period in the summer of 2011, a CO 2 leak was simulated in a test field run by the Zero Emissions Research and Technology Center in Bozeman, Montana. An LWIR imager was deployed on a scaffold before and during the CO 2 release, viewing a vegetation test area that included regions of high and low CO 2 flux. Increased root-level CO 2 concentration caused plant stress that led to reduced thermal regulation of the vegetation, which was consistent with increased diurnal variation of IR emission observed in this study. In a linear regression, the IR data were found to have a strong relationship to the CO 2 emission and to be consistent with the location of leaking CO 2 gas. Reducing the continuous data set to one image per day weakened the regression fit, but maintained sufficient significance to indicate that this method could be implemented with once-daily airborne images.
Ground-based, low-cost, uncooled infrared imagers are specially calibrated and deployed for long-term measurements of spatial and temporal cloud statistics. Measurements of cloud optical depth are shown for thin clouds, and validated with a dual-polarization cloud lidar. Good comparisons are achieved for thin clouds having 550-nm optical depth of 3 or less.
The commercial development of microbolometer uncooled long-wave thermal infrared imagers in conjuncture with
advanced radiometric calibration methods developed at Montana State University has led to new uses of thermal imagery
in remote sensing applications. A novel use of these calibrated imagers is imaging of vegetation for CO2 gas leak
detection. During a four-week period in the summer of 2011, a CO2 leak was simulated in a test field run by the Zero Emissions Research and Technology Center in Bozeman, Montana. Thermal infrared images were acquired, along with
visible and near-infrared reflectance images, of the exposed vegetation and healthy control vegetation. The increased
root-level CO2 concentration causes plant stress that results in reduced thermal regulation of the vegetation, which is detectable as an increased diurnal variation of infrared emission. . In a linear regression, the infrared data were found to have a strong coefficient of determination and clearly show the effect of the CO2 on the vegetation.
A set of low-cost, compact multispectral imaging systems have been developed for deployment on tethered balloons for education and outreach based on basic principles of optical remote sensing. The imagers use tiny CMOS cameras with low-cost optical filters to obtain images in red and near-infrared bands, and a more recent version include a blue band. The red and near-infrared bands are used primarily for identifying and monitoring vegetation through the Normalized Difference Vegetation Index (NDVI), while the blue band is used for studying water turbidity, identifying water and ice, and so forth. The imagers are designed to be carried by tethered balloons at altitudes up to approximately 50 m. Engineering and physics students at Montana State University-Bozeman gained hands-on experience during the early stages of designing and building the imagers, and a wide variety of university and college students are using the imagers for a broad range of applications to learn about multispectral imaging, remote sensing, and applications typically involving some aspect of environmental science.
Measuring the modulation transfer function (MTF) of digital imagers focused at or near infinity in laboratory or field settings presents difficulties because the optical path is longer than a typical laboratory. Also, digital imagers can be hindered by low-resolution detectors, resulting in the resolution of the optics surpassing that of the detector. We measure the MTF for a short-wave infrared hyperspectral imager developed by Resonon, Inc., of Bozeman, Montana, which exhibits both characteristics. These difficulties are overcome with a technique that uses images of building rooflines in an oversampled, tilted knife-edge-based MTF measurement. The dark rooftops backlit by a uniformly cloudy sky provide the high-contrast edges required to perform knife-edge MTF measurements. The MTF response is measured at five wavelengths across the imager's spectral band: 1085, 1178, 1292, 1548, and 1629 nm. The MTF also is observed at various distances from the roof to investigate performance change with distance. Optimum imaging is observed at a distance of 150 m, potentially a result of imperfect infinity focus and atmospheric turbulence. In a laboratory validation of the MTF algorithm using a monochrome visible imager, the roofline MTF results are similar to results from point-source and sine-card MTF measurements.
KEYWORDS: Sensors, Auroras, Calibration, Signal detection, Radio optics, Analog electronics, Electronics, Interference filters, Microcontrollers, Prototyping
Natural optical phenomena enjoy a level of interest sufficiently high among a wide array of people to provide ideal education and outreach opportunities. The aurora promotes particularly high interest, perhaps because of its relative rarity in the areas of the world where most people live. A project is being conducted at Montana State University to use common interest and curiosity about auroras to motivate learning and outreach through the design and deployment of optical sensor systems that detect the presence of an auroral display and send cell phone messages to alert interested people. Project participants learn about the physics and optics of the aurora, basic principles of optical system design, radiometric calculations and calibrations, electro-optical detectors, electronics, embedded computer systems, and computer software. The project is moving into a stage where it will provide greatly expanded outreach and education opportunities as optical aurora detector kits are created and disbursed to colleges around our region.
Calibration of wide-angle (100°+ field of view) long wave infrared cameras with commercially available large-area
blackbody calibration targets poses problems. Typically the emissivity of blackbody sources is specified on axis and up
to angles of approximately 20°. For wide-angle camera calibration the emissivity needs to be known out to 60° or
greater. Presented is a technique that uses the known on-axis emissivity for the blackbody and changes in radiance with
angle to determine the angle-dependent emissivity. Four commercial blackbodies with various surface structures were
measured. The emissivity was found to be significantly angle dependent beyond 30°, dropping to 0.95 or less by 60°.
Measuring the Modulation Transfer Function (MTF) of a hyperspectral imaging spectrometer focused at infinity requires
a longer optical path than is available in a typical laboratory. We describe a technique that uses images of rooflines on
buildings of opportunity in a knife-edge-based MTF measurement. This technique only measures the MTF along one
dimension. However, the hyper-spectral imaging systems characterized in this paper are particularly suited to a knife-edge
technique, as imaging only takes place in one dimension of the array and spectral separation takes place along the
other. The sharp edges needed in these measurements were provided by dark rooftops backlit by a uniformly cloudy sky.
We have applied this technique to hyperspectral imagers that operate in the visible-near infrared (VNIR) and short-wave
infraRed (SWIR) spectral bands. The data presented in this paper focuses on the characterization of the SWIR imaging
spectrometer developed by Resonon Inc.
Previous research at Montana State University led to the development of the Infrared Cloud Imager (ICI) for measuring
downwelling cloud and sky thermal emission for producing cloud coverage statistics using radiometrically calibrated
images of the sky. This technique, that was developed primarily for detection of clouds for studies of arctic climate,
provides benefits over commonly used systems by producing localized high resolution data in comparison to satellites
images, and, in contrast to visible systems, provides continuous day and night operation. As a continuation of the first
effort, in collaboration with the Optical Communications Group at the NASA's Jet Propulsion Laboratory (JPL), here we
present a new generation of the ICI that can be used to monitor the cloud coverage of a site that can house a ground
telescope dedicated to Earth-space optical communication paths. This new instrument, based around the FLIR Photon
camera, expands the field of view (FOV) from 20° to 50° (up to 100° in the latest version), reduces instrument size,
reduces instrument cost, and extends the time between calibrations to hours instead of minutes. This has been
accomplished by characterizing the changes in the output data for changes in the camera's internal temperature while
viewing a constant source. Deployment of this instrument has taken place at JPL's Table Mountain facility, CA, and
Bozeman, MT.
A polarization-sensitive lidar was used to detect honeybees trained to locate buried landmines by smell. Lidar measurements of bee location agree reasonably well with maps of chemical plume strength and bee density determined by visual and video counts, indicating that the bees are preferentially located near the explosives and that the lidar identifies the locations of higher bee concentration. The co-polarized lidar backscatter signal is more effective than the cross-polarized signal for bee detection. Laboratory measurements show that the depolarization ratio of scattered light is near zero for bee wings and up to approximately thirty percent for bee bodies.
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