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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Virtual Sensors Determined Through Machine Learning

We propose a method that increases the capability of a conventional sensor, transforming it into an enhanced virtual sensor. This paper focuses on a virtual thermal Infrared Radiation (IR) sensor based on a conventional visual (RGB) sensor. The estimation of thermal IR images can enhance the ability of terrain classification, which is crucial for autonomous navigation of rovers. The estimate in IR from visual band has inherent limitations, as these are different bands, yet correlations between visual RGB and thermal IR images exist, as different terrains, which visually may appear different, also have different thermal inertia. This paper describes the developed deep learning-based algorithm that estimates thermal IR images from RGB images of terrains, providing the feasibility of the idea with average 1.21 error [degree Celsius].

Torresen, Jim↗
NASA NTRS2018

Virtual Sensors Determined Through Machine Learning

We propose a method that increases the capability of a conventional sensor/instrument, transforming it into an enhanced virtual sensor/instrument. This paper focuses on a virtual thermal IR sensor based on a conventional visual (RGB) sensor. The estimation of thermal IR images can enhance the ability of terrain classification, which is crucial for autonomous navigation of rovers. The estimate in IR from visual band has inherent limitations, as these are different bands, yet correlations between visual/RGB and thermal IR images exist, as different terrains, which visually may appear different, also have different thermal inertia. We developed a deep learning-based algorithm that estimates thermal IR images from RGB images of terrains, providing the feasibility of the idea with average 1.21 error [degree].

Kurazume, Ryo↗
NASA NTRS2015

Limb Correction of Individual Infrared Channels Used in RGB Composite Products

This study demonstrates that limb-cooling can be removed from infrared imagery using latitudinally and seasonally dependent limb correction coefficients, which account for an increasing optical path length as scan angle increases. Furthermore, limb-corrected RGB composites provide multiple advantages over uncorrected RGB composites, including increased confidence in the interpretation of RGB features, improved situation awareness for operational forecasters, seamless transition between overlaid RGB composites, easy comparison of RGB products from different sensors, and the availability of high quality proxy products for the GOES-R era, as demonstrated by the case examples presented in Section 3. This limb correction methodology can also be applied to additional infrared channels used to create other RGB products, including those created from other satellite sensors, such as Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS).

RGB↗
NASA NTRS2015

Limb Correction of Individual Infrared Channels Used in RGB Composite Products

This study demonstrates that limb-cooling can be removed from infrared imagery using latitudinally and seasonally dependent limb correction coefficients, which account for an increasing optical path length as scan angle increases. Furthermore, limb-corrected RGB composites provide multiple advantages over uncorrected RGB composites, including increased confidence in the interpretation of RGB features, improved situation awareness for operational forecasters, seamless transition between overlaid RGB composites, easy comparison of RGB products from different sensors, and the availability of high quality proxy products for the GOES-R era, as demonstrated by the case examples presented in Section 3. This limb correction methodology can also be applied to additional infrared channels used to create other RGB products, including those created from other satellite sensors, such as Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS).

Elmer, Nicholas J.↗
NASA NTRS2017

Developing a 3-DOF Compliant Perching Arm for a Free-Flying Robot on the International Space Station

This paper presents the design and control of the 3-DOF compliant perching arm for the free-flying Astrobee robots that will operate inside the International Space Station (ISS). The robots are intended to serve as a flexible platform for future guest scientists to use for zero-gravity robotics research - thus, the arm is designed to support manipulation research. It provides a 1-DOF underactuated tendon-driven gripper capable of enveloping a range of objects of different shapes and sizes. Co-located RGB camera and LIDAR sensors provide perception. The Astrobee robots will be capable of grasping each other in flight, to simulate orbital capture scenarios. The arm's end-effector module is swappable on-orbit, allowing guest scientists to add upgraded grippers, or even additional arm degrees of freedom. The design of the arm balances research capabilities with Astrobee's operational need to perch on ISS handrails to reduce power consumption. Basic arm functioning and grip strength were evaluated using an integrated Astrobee prototype riding on a low-friction air bearing.

Park, In-Won↗
NASA NTRSDate not supplied

Standardized RGB Composite Imagery for Global Applications

NASA’s MODIS instruments on the Terra and Aqua satellites have been providing imaging capabilities from polar orbit for the last 20 years allowing for twice daily sampling of mesoscale atmospheric features with multispectral or Red, Green, Blue (RGB) composite imagery. With the launch of the next generation of geostationary sensors the capability exists for expanded coverage of RGB imagery with the ability to track features over long distances and study the processes that contribute to the development of fast evolving features. However, the use of RGB imagery on a global basis is not without limitations due to the impact of limb-effects at high viewing angles and subtle spectral channel differences between satellite sensors.

Emily Berndt↗
NASA NTRS2016

Limb Correction of Polar-Orbiting Imagery for the Improved Interpretation of RGB Composites

Red-Green-Blue (RGB) composite imagery combines information from several spectral channels into one image to aid in the operational analysis of atmospheric processes. However, infrared channels are adversely affected by the limb effect, the result of an increase in optical path length of the absorbing atmosphere between the satellite and the earth as viewing zenith angle increases. This paper reviews a newly developed technique to quickly correct for limb effects in both clear and cloudy regions using latitudinally and seasonally varying limb correction coefficients for real-time applications. These limb correction coefficients account for the increase in optical path length in order to produce limb-corrected RGB composites. The improved utility of a limb-corrected Air Mass RGB composite from the application of this approach is demonstrated using Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, the limb correction can be applied to any polar-orbiting sensor infrared channels, provided the proper limb correction coefficients are calculated. Corrected RGB composites provide multiple advantages over uncorrected RGB composites, including increased confidence in the interpretation of RGB features, improved situational awareness for operational forecasters, and the ability to use RGB composites from multiple sensors jointly to increase the temporal frequency of observations.

satellite imagery↗
NASA NTRS2008

Chromatic Modulator for a High-Resolution CCD or APS

A chromatic modulator has been proposed to enable the separate detection of the red, green, and blue (RGB) color components of the same scene by a single charge-coupled device (CCD), active-pixel sensor (APS), or similar electronic image detector. Traditionally, the RGB color-separation problem in an electronic camera has been solved by use of either (1) fixed color filters over three separate image detectors; (2) a filter wheel that repeatedly imposes a red, then a green, then a blue filter over a single image detector; or (3) different fixed color filters over adjacent pixels. The use of separate image detectors necessitates precise registration of the detectors and the use of complicated optics; filter wheels are expensive and add considerably to the bulk of the camera; and fixed pixelated color filters reduce spatial resolution and introduce color-aliasing effects. The proposed chromatic modulator would not exhibit any of these shortcomings. The proposed chromatic modulator would be an electromechanical device fabricated by micromachining. It would include a filter having a spatially periodic pattern of RGB strips at a pitch equal to that of the pixels of the image detector. The filter would be placed in front of the image detector, supported at its periphery by a spring suspension and electrostatic comb drive. The spring suspension would bias the filter toward a middle position in which each filter strip would be registered with a row of pixels of the image detector. Hard stops would limit the excursion of the spring suspension to precisely one pixel row above and one pixel row below the middle position. In operation, the electrostatic comb drive would be actuated to repeatedly snap the filter to the upper extreme, middle, and lower extreme positions. This action would repeatedly place a succession of the differently colored filter strips in front of each pixel of the image detector. To simplify the processing, it would be desirable to encode information on the color of the filter strip over each row (or at least over some representative rows) of pixels at a given instant of time in synchronism with the pixel output at that instant.

Hartley, Frank↗
NASA NTRS2016

Limb Correction of Infrared Imagery in Cloudy Regions for the Improved Interpretation of RGB Composites

Red-Green-Blue (RGB) composites (EUMETSAT User Services 2009) combine information from several channels into a single composite image. RGB composites contain the same information as the original channels, but presents the information in a more efficient manner. However, RGB composites derived from infrared imagery of both polar-orbiting and geostationary sensors are adversely affected by the limb effect, which interferes with the qualitative interpretation of RGB composites at large viewing zenith angles. The limb effect, or limb-cooling, is a result of an increase in optical path length of the absorbing atmosphere as viewing zenith angle increases (Goldberg et al. 2001; Joyce et al. 2001; Liu and Weng 2007). As a result, greater atmospheric absorption occurs at the limb, causing the sensor to observe anomalously cooler brightness temperatures. Figure 1 illustrates this effect. In general, limb-cooling results in a 4-11 K decrease in measured brightness temperature (Liu and Weng 2007) depending on the infrared band. For example, water vapor and ozone absorption channels display much larger limb-cooling than infrared window channels. Consequently, RGB composites created from infrared imagery not corrected for limb effects can only be reliably interpreted close to nadir, which reduces the spatial coverage of the available imagery. Elmer (2015) developed a reliable, operational limb correction technique for clear regions. However, many RGB composites are intended to be used and interpreted in cloudy regions, so a limb correction methodology valid for both clear and cloudy regions is needed. This paper presents a limb correction technique valid for both clear and cloudy regions, which is described in Section 2. Section 3 presents several RGB case studies demonstrating the improved functionality of limb-corrected RGBs in both clear and cloudy regions, and Section 4 summarizes and presents the key conclusions of this work.

RGB↗
NASA NTRS2022

Reversible Colorimetric Sensing of Volatile Analytes By Wicking in Close Proximity to A Photonic Film

Isolation of volatile analytes from environmental or biological fluids is a rate-determining step that can delay the response time for continuous sensing. In this paper, we demonstrate a colorimetric sensing system that enables the rapid detection of gas-phase analytes released from a flowing micro-volume fluid sample. The sensor platform is an analyte-responsive metal-insulator-metal (MIM) thin-film structure integrated with a large area quartz micropillar array. This allows precise planar alignment and microscale separation (310 μm) of the optical and fluidic structures. This configuration offers rapid and homogeneous color changes over large areas that permits detection by low-resolution optics or eye, which is well-suited to portable/wearable devices. For our proof-of-principle demonstration, we utilized a poly(methyl methacrylate) (PMMA) spacer and evaluated the sensor's response (color change) to ethanol vapor. We show that the RGB color value is quantitatively linked to the spacer swelling, which is reversible and repeatable. The optofluidic platform reduces the sensor response time from minutes to seconds compared with experiments using a conventional chamber. The sensor's concentration-dependent response was examined, confirming the potential of the reported sensing platform for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples, such as biofluids.

Timothy J. Palinski↗
NASA NTRS2013

Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and recent applications within the operational forecasting environment

Molthan, Andrew L.↗
NASA NTRS2014

Limb Correction of RGB Composite Imagery for Improved Interpretation

RGB (Red‐Green‐Blue) imagery, created by integrating several spectral channels into one composite image, is currently used by the operational weather community to aid in quick, real‐time analysis of atmospheric processes. However, the limb effect - a result of an increasing optical path length of the absorbing atmosphere between the satellite and the earth as scan angle increases - interferes with the qualitative interpretation of RGB composites at large scan angles. It also makes the comparison of similar products from multiple satellite sensors difficult. Recent work has indicated that correcting for the limb effect in the basic channel imagery using simple statistical relationships greatly improves the utility of the derived RGB imagery. However, it is hypothesized that the limb correction coefficients vary with respect to latitude, season, cloud cover, and surface albedo. This poster will highlight an improved approach to the limb correction of RGB imagery using varying coefficients. The Joint Center for Satellite and Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) was used to simulate top of atmosphere brightness temperatures at varying scan angles for infrared channels corresponding to the Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS), and Meteosat‐10 Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors. A subset of European Center for Medium‐Range Weather Forecasts (ECMWF) temperature, specific humidity, and ozone mixing ratio profiles from March 2013 through February 2014 were used as input to the CRTM. The simulated brightness temperatures were used to determine the best fit slope of the linear relationship between the natural log of the cosine of the scan angle and the difference of the simulated brightness temperature at nadir and on the limb. The correction coefficients were then analyzed for variability with respect to latitude, season, cloud cover, and surface type and used to produce improved limb corrected imagery. Applications of the results will be presented.

Elmer, Nicholas↗
NASA NTRS2012

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites). At the same time, new image manipulation and display capabilities are available within AWIPS II, the next generation of the NWS forecaster decision support system. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and articulate an integrated and collaborative path forward with Raytheon AWIPS II development staff for integrating current and future capabilities that support new satellite instrumentation and the AWIPS II decision support system.

Molthan, Andrew L.↗
NASA NTRSDate not supplied

Multispectral Imagery Research and Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center developed techniques to improve the quality and interpretation of multispectral imagery derived from NASA/NOAA geostationary satellites using statistical and machine learning approaches. A physically-based machine learning approach, DustTracker-AI, was developed to overcome the problem of night-time dust detection and to augment dust analysis with satellite products such as the Dust RGB. Additionally, an updated limb-correction and intercalibration methodology for short-wave, near-infrared, thermal infrared, and water vapor bands was developed for the purpose of developing a suite of high-quality RGB imagery that can be used at high viewing angles and across the constellation of geostationary sensors. This presentation will briefly highlight the techniques developed to detect dust in difficult night-time scenes and improve the quality and interpretation of multispectral imagery.

Emily Berndt↗
NASA NTRS2021

Online Photometric Calibration of Automatic Gain Thermal Infrared Cameras

Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance of traditional computer vision techniques developed for electro-optical imagery does not directly translate to the thermal domain due to two major reasons: these algorithms require photometric assumptions to hold, and methods for photometric calibration of RGB cameras cannot be applied to thermal-infrared cameras due to difference in data acquisition and sensor phenomenology. In this paper, we take a step in this direction, and introduce a novel algorithm for online photometric calibration of thermalinfrared cameras. Our proposed method does not require any specific driver/hardware support and hence can be applied to any commercial off-the-shelf thermal IR camera. We present this in the context of visual odometry and SLAM algorithms, and demonstrate the efficacy of our proposed system through extensive experiments for both standard benchmark datasets, and real-world field tests with a thermal-infrared camera in natural outdoor environments.

Daftry, Shreyansh↗
NASA NTRS2003

Chromatic Modulator for High Resolution CCD or APS Devices

A system for providing high-resolution color separation in electronic imaging. Comb drives controllably oscillate a red-green-blue (RGB) color strip filter system (or otherwise) over an electronic imaging system such as a charge-coupled device (CCD) or active pixel sensor (APS). The color filter is modulated over the imaging array at a rate three or more times the frame rate of the imaging array. In so doing, the underlying active imaging elements are then able to detect separate color-separated images, which are then combined to provide a color-accurate frame which is then recorded as the representation of the recorded image. High pixel resolution is maintained. Registration is obtained between the color strip filter and the underlying imaging array through the use of electrostatic comb drives in conjunction with a spring suspension system.

Frank T Hartley↗
NASA NTRS2020

Mapping Temperate Forest Phenology Using Tower, UAV, and Ground-Based Sensors

Phenology is a distinct marker of the impacts of climate change on ecosystems. Accordingly, monitoring the spatiotemporal patterns of vegetation phenology is important to understand the changing Earth system. A wide range of sensors have been used to monitor vegetation phenology, including digital cameras with different viewing geometries mounted on various types of platforms. Sensor perspective, view-angle, and resolution can potentially impact estimates of phenology. We compared three different methods of remotely sensing vegetation phenology—an unoccupied aerial vehicle (UAV)-based, downward-facing RGB camera, a below-canopy, upward-facing hemispherical camera with blue (B), green (G), and near-infrared (NIR) bands, and a tower-based RGB PhenoCam, positioned at an oblique angle to the canopy—to estimate spring phenological transition towards canopy closure in a mixed-species temperate forest in central Virginia, USA. Our study had two objectives: (1) to compare the above- and below-canopy inference of canopy greenness (using green chromatic coordinate and normalized difference vegetation index) and canopy structural attributes (leaf area and gap fraction) by matching below-canopy hemispherical photos with high spatial resolution (0.03 m) UAV imagery, to find the appropriate spatial coverage and resolution for comparison; (2) to compare how UAV, ground-based, and tower-based imagery performed in estimating the timing of the spring phenological transition. We found that a spatial buffer of 20 m radius for UAV imagery is most closely comparable to below-canopy imagery in this system. Sensors and platforms agree within +/− 5 days of when canopy greenness stabilizes from the spring phenophase into the growing season. We show that pairing UAV imagery with tower-based observation platforms and plot-based observations for phenological studies (e.g., long-term monitoring, existing research networks, and permanent plots) has the potential to scale plot-based forest structural measures via UAV imagery, constrain uncertainty estimates around phenophases, and more robustly assess site heterogeneity.

Jeff W. Atkins↗