Montana and similar regions contain numerous rivers and lakes that are too small to be spatially resolved by satellites that provide water quality estimates. Unoccupied Aerial Vehicles (UAVs) can be used to obtain such data with much higher spatial and temporal resolution. Water properties are traditionally retrieved from passively measured spectral radiance, but polarization has been shown to improve retrievals of the attenuation-to-absorption ratio to enable calculation of the scattering coefficient for in-water particulate matter. This feeds into improved retrievals of other parameters such as the bulk refractive index and particle size distribution. This presentation will describe experiments conducted to develop a data set for water remote sensing using combined UAV-based hyperspectral and polarization cameras supplemented with in-situ sampling at Flathead Lake in northwestern Montana and the results of preliminary data analysis. A symbolic regression model was used to derive two equations: one relating DoLP, AoP, and the linear Stokes parameters at wavelengths of 440 nm, 550 nm and 660 nm, to chlorophyll-a content, and one relating the same data to the attenuation-to-absorption ratio for 440 nm, 550 nm and 660 nm. Symbolic regression is a machine learning algorithm where the inputs are vectors and the output is an analytic expression, typically chosen by a genetic algorithm. An advantage of this approach is that the explainability of a simple equation can be combined with the accuracy of less explainable models, such as the genetic algorithm.
Cloud thermodynamic phase is an important parameter in climate models and cloud remote sensing because it controls whether a cloud tends to have a net heating or cooling effect and it must be known to retrieve other cloud parameters. Passive remote sensing of cloud thermodynamic phase using shortwave infrared radiance ratios is a well-known technique, and adding polarization sensitivity to the radiance ratio method can increase accuracy. Ground-based passive polarimetric remote sensing of cloud phase has also been performed in visible and near infrared wavelengths. Prior work has relied on highly sensitive, expensive polarimeters to detect the small change in polarization state between ice and liquid clouds. We explored the use of a low-cost, commercial division-of-focal-plane polarization imager for cloud thermodynamic phase retrievals. We calibrated and deployed a monochrome polarization imager, with both a moderate field-of-view lens and a fisheye lens. The imagers were deployed alongside a verified dual-polarization lidar that provided a truth measurement at the zenith. In this paper, we discuss the relationship between the Stokes S1 parameter measured by the low-cost polarization imager with both lenses and the cloud thermodynamic phase retrieved by a dual-polarization lidar.
It is well known that underwater objects become more readily visible when viewed through a vertical polarizer that suppresses horizontally polarized reflections from the air-water interface. However, quantitative measurements of the contrast enhancement achieved with a polarizer do not seem to have been reported in the literature. To measure the polarization-enabled contrast enhancement, we placed white and black tiles next to each other, immersed in water, then measured the optical contrast between them as a function of viewing angle (relative to the surface normal) with a polarization camera that simultaneously recorded images with linear polarization oriented 0°, 90°, and 45°from horizontal. Images were recorded with an RGB polarization camera through approximately 45 cm of water at Bozeman Pond and with a monochrome polarization camera through approximately 5 cm of water at Bozeman Beach. Images also were recorded with the monochrome camera and a filter to isolate the near infrared band of approximately 750 to 1000 nm. Indoor laboratory measurements also were recorded to verify the role of the color of the reflecting background. All experiments used carefully calibrated division-of-focal-plane polarization cameras. The observed contrast decreased with viewing angle, but less so for the vertically polarized images. The contrast enhancement, represented by the ratio of vertically polarized to unpolarized contrast, increased with viewing angle, even past the Brewster angle (approx. 53°). The contrast enhancement only began decreasing for viewing angles larger than 70°. In outdoor experiments with a mostly clear sky, the highest contrast enhancement was in the blue spectral band. The contrast was essentially the same for red, green, and blue bands with a white background. In all measurements, the black tile exhibited much larger degree of linear polarization, which is an example of the Umov effect. In this paper we describe the experiments, show and explain polarization images, and show and explain plots of contrast and contrast enhancement as a function of viewing angle.
To use moonlight as a source for on-orbit calibration of satellite instruments and for nighttime passive remote sensing, considerable effort has been made to develop and improve radiometric models of the Moon. However, to enable calibration of polarization-sensitive instruments and nighttime polarimetric remote sensing, the polarization state of moonlight must be known as well. While several observations of moonlight polarization have been published, there is no known database of disk-integrated polarization measurements or disk-resolved polarization images as a function of phase angle. We used a monochrome division-of-focal-plane polarization imager with a telescope (focal length of 2 m) and a telephoto lens (focal length of 300 mm) to record images of the degree and angle of linear polarization for lunar phases ranging from full Moon to about 15% full. We calculated the disk-integrated polarization state from the images. We present a plot of disk-integrated polarization state as a function of phase angle, which agrees well with similar plots published previously for small regions of the Moon. The disk-integrated degree of linear polarization (DoLP) reaches a maximum of approximately 8% at a phase angle near 100° and a minimum near 0% at a phase angle of 0°. We also present S0, DoLP, and angle of polarization (AoP) images and use them to explain the lunar locations where polarized light primarily originates. To our knowledge, the presented DoLP images are higher resolution than previously published DoLP images, and AoP images presented here have not yet been published.
Optical remote sensing systems are often used to gather imagery of scenes containing partially polarized light. Partially polarized reflection or emission will affect the detected response if the sensor system has intentional or unintentional polarization sensitivity. As the use of optical remote sensing systems becomes more widespread, the factors affecting the response of these systems needs to be better understood. In this paper, we present the results of polarization response measurements of six hyperspectral imaging systems manufactured by Resonon Inc. The imagers included in this study cover wavelengths from approximately 350nm to 1700 nm, with various spectral sampling rates. Efforts are ongoing to model and compensate for the observed response.
Cloud thermodynamic phase, whether a cloud is composed of spherical water droplets or polyhedral ice crystals, is crucial for understanding the role of clouds in climate change, weather, and optical propagation. Clouds, covering approximately 60% of the earth's surface at any given time, still contribute some of the largest uncertainties in climate science. Cloud thermodynamic phase is also required to properly retrieve other cloud properties, including cloud optical depth and particle size distributions. Cloud phase remote sensing is often done with passively measured radiance ratios or lidar cross-polarization measurements, but recent research shows that the sign of the S1 Stokes parameter can be used to detect cloud thermodynamic phase with a ground-based polarimeter. Our group has been developing ground-based polarimetric imagers to determine cloud thermodynamic phase, with lidar cross-polarization detection used as ground truth. However, because the cloud polarization is small, often on the order of a percent, accurate classification requires high polarization sensitivity. This paper reports preliminary measurements indicating feasibility of using a low-cost, commercial division-of-focal-plane polarization imager for cloud thermodynamic phase remote sensing.
Monochromators are frequently used in spectral calibrations of optical systems due to their ability to sweep a narrowband output across a wide range of wavelengths. However, monochromators tend to output light with a degree of linear polarization that can vary significantly as a function of wavelength. To use a monochromator to calibrate a polarization-sensitive imager, the monochromator output is often passed into an integrating sphere to convert the linearly polarized light into randomly polarized light. In this paper, we demonstrate the ability to obtain a spectral calibration of a division-of-focal-plane (DoFP) imager by assuming subpixels of a polarization super pixel have equal spectral responses. We also characterize the polarization of the output of a monochromator as a function of wavelength using both a DoFP imager and a wire-grid polarizer mounted on a precision rotation stage with an optical power meter.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.