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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Mapping Electrical Crosstalk in Pixelated Sensor Arrays

Electronic coupling effects such as Inter-Pixel Capacitance (IPC) affect the quantitative interpretation of image data from CMOS, hybrid visible and infrared imagers alike. Existing methods of characterizing IPC do not provide a map of the spatial variation of IPC over all pixels. We demonstrate a deterministic method that provides a direct quantitative map of the crosstalk across an imager. The approach requires only the ability to reset single pixels to an arbitrary voltage, different from the rest of the imager. No illumination source is required. Mapping IPC independently for each pixel is also made practical by the greater S/N ratio achievable for an electrical stimulus than for an optical stimulus, which is subject to both Poisson statistics and diffusion effects of photo-generated charge. The data we present illustrates a more complex picture of IPC in Teledyne HgCdTe and HyViSi focal plane arrays than is presently understood, including the presence of a newly discovered, long range IPC in the HyViSi FPA that extends tens of pixels in distance, likely stemming from extended field effects in the fully depleted substrate. The sensitivity of the measurement approach has been shown to be good enough to distinguish spatial structure in IPC of the order of 0.1%.

focal plane array↗
NASA NTRS2020

Comparison of the MODIS and VIIRS Thermal Emissive Band Radiometric Calibration

Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) are major instruments for Earth science observations.Nearly 40 MODIS scientific products and a wide range of VIIRS environmental data records are produced using their global observations. The consistency of the MODIS and VIIRS calibrated data is important for the study of Earth science. This article assesses the calibration consistency of the Aqua MODIS and VIIRS thermal emissive band (TEB) data. To remove the impact of the mismatched relative spectral response (RSR) on the comparisons, the simultaneous nadir observation data from the cross-track infrared sounder (CrIS) and the infrared atmospheric sounding interferometer (IASI) are used as references in two different methods to independently verify the consistency. The comparisons of the MODIS and VIIRS TEB calibrated data show that the brightness temperature (BT) differences for comparable bands between MODIS and VIIRS are in general within 0.2 K for BT larger than 230 K. The differences of all comparable MODIS and VIIRS TEBs are consistent over time. MODIS measurements agree better with N20 VIIRS than with Suomi National Polar-orbiting Partnership (S-NPP) VIIRS. The S-NPP VIIRS measurements are higher than N20 VIIRS, within 0.1 Kfor long-wave infrared (LWIR) bands and 0.3 K for band M13.

Calibration↗
NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗
NASA NTRS1984

The rationale and suggested approaches for research geosynchronous satellite measurements for severe storm and mesoscale investigations

The measurements from current and planned geosynchronous satellites provide quantitative estimates of temperature and moisture profiles, surface temperature, wind, cloud properties, and precipitation. A number of significant observation characteristics remain, they include: (1) temperature and moisture profiles in cloudy areas; (2) high vertical profile resolution; (3) definitive precipitation area mapping and precipitation rate estimates on the convective cloud scale; (4) winds from low level cloud motions at night; (5) the determination of convective cloud structure; and (6) high resolution surface temperature determination. Four major new observing capabilities are proposed to overcome these deficiencies: a microwave sounder/imager, a high resolution visible and infrared imager, a high spectral resolution infrared sounder, and a total ozone mapper. It is suggested that the four sensors are flown together and used to support major mesoscale and short range forecasting field experiments.

Shenk, W. E.↗
NASA NTRS1989

Thermal emission from interstellar dust in and near the Pleiades

IRAS survey coadds for a 8.7 deg x 4.3 deg field near the Pleiades provide evidence for dynamical interaction between the cluster and the surrounding interstellar medium. The far-infrared images show large region of faint emission with bright rims east of the cluster, suggestive of a wake. Images of the far-infrared color temperature and 100 micron optical depth reveal temperature maxima and optical depth minima near the bright cluster stars, as well as a strong optical depth peak at the core of the adjacent CO cloud. Models for thermal dust emission near the stars indicate that most of the apparent optical depth minima near stars are illusory, but also provide indirect evidence for small interaction between the stars and the encroaching dust cloud.

White, Richard E.↗
NASA NTRS1991

The Geologic Remote Sensing Field Experiment (GRSFE): The first geology multisensor airborne campaign

The primary objective of the Geologic Remote Sensing Field Experiment (GRSFE) is to acquire relevant data for geological sites that can be used to test models for extraction of surface property information from remote sensing data for earth, Mars and Venus in support of the Earth Observing System (EOS), Mars Observer, and Magellan, respectively. Over forty scientists from eight universities and three NASA centers are participating in GRSFE which is co-sponsored by the NASA Planetary Geology and Geophysics Program and the NASA Geology Program. Highlights of the airborne campaign included the first simultaneous acquisition of Airborne Visible and Infrared Imaging Spectrometer (AVRIS) and Thermal Infrared Multispectral Scanner (TIMS) data on September 29, 1989, and acquisition of Advanced Solid-State Array Spectroradiometer (ASAS), Polarimetric Synthetic Aperture Radar (AIRSAR), and Airborne Terrain Laser Altimeter System (ATLAS) data all within three months of each other. The sites covered were Lunar Crater Volcanic Field and Fish Lake Valley in Nevada; and Cima Volcanic Field, Death Valley, and Ubehebe Crater in California. Coincident field measurements included meteorological and atmospheric measurements, visible/near-infrared and thermal spectra, and characterization of geology and vegetation cover. The GRSFE airborne and field data will be reduced to a suite of standard products and submitted, along with appropriate documentation, to the Planetary Data System (PDS) and the Pilot Land Data System (PLDS). These data will be used for a variety of investigations including paleoclimatic studies in the arid southwestern United States, and analysis of Magellan data. GRSFE data will also be used to support Mars Observer Laser Altimeter (MOLA) and Mars Rover Sample Return (MRSR) simulation studies.

Evans, Diane L.↗
NASA NTRS1992

Water vapor column abundance retrievals during FIFE

A variation of the modified Langley plot algorithm is reported here and applied to the retrieval of atmospheric water column abundance from a filtered sunphotometer. In this new methodology an absorption data base (LOWTRAN 7) is used to compute a water abundance versus transmittance curve of growth, rather than the square-root dependence previously assumed. Validation of the technique is provided from an uncertainty analysis, and plans to further validate using Fourier transform spectrometers are detailed. The new sunphotometer technique is used to report local column water vapor during the First ISLSCP Field Experiment (FIFE), and comparisons are made with abundances retrieved via FIFE radiosonde observations. The sunphotometer data can best be utilized, however, to in turn validate data from airborne or in-orbit measurements of water vapor. With these flight sensors, horizontal and topographic variability within the scene can be viewed. An example of the airborne data set is given using an image from the airborne visible infrared imaging spectrometer, as acquired on August 31, 1990.

Bruegge, Carol J.↗
NASA NTRS1993

Compositional and textural information from the dual inversion of visible, near and thermal infrared remotely sensed data

A technique is presented that allows extraction of compositional and textural information from visible, near and thermal infrared remotely sensed data. Using a library of both emissivity and reflectance spectra, endmember abundances and endmember thermal inertias are extracted from AVIRIS (Airborne Visible and Infrared Imaging Spectrometer) and TIMS (Thermal Infrared Mapping Spectrometer) data over Lunar Crater Volcanic Field, Nevada, using a dual inversion. The inversion technique is motivated by upcoming Mars Observer data and the need for separation of composition and texture parameters from sub pixel mixtures of bedrock and dust. The model employed offers the opportunity to extract compositional and textural information for a variety of endmembers within a given pixel. Geologic inferences concerning grain size, abundance, and source of endmembers can be made directly from the inverted data. These parameters are of direct relevance to Mars exploration, both for Mars Observer and for follow-on missions.

Brackett, Robert A.↗
NASA NTRS1996

Telescope With A Two-Color Camera And Two Imaging Spectrometers

Proposed remote-sensing optical instrument system includes two charge-coupled-device (CCD) video cameras sensitive to different colors of light; line-imaging infrared spectrometer; and line-imaging ultraviolet spectrometer; all sharing common telescope foreoptics. Principal advantages: compactness and light weight.

Chrisp, Michael P.↗
NASA NTRS2012

VIIRS On-Orbit Optical Anomaly - Investigation, Analysis, Root Cause Determination and Lessons Learned

A gradual, but persistent, decrease in the optical throughput was detected during the early commissioning phase for the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imager Radiometer Suite (VIIRS) Near Infrared (NIR) bands. Its initial rate and unknown cause were coincidently coupled with a decrease in sensitivity in the same spectral wavelength of the Solar Diffuser Stability Monitor (SDSM) raising concerns about contamination or the possibility of a system-level satellite problem. An anomaly team was formed to investigate and provide recommendations before commissioning could resume. With few hard facts in hand, there was much speculation about possible causes and consequences of the degradation. Two different causes were determined as will be explained in this paper. This paper will describe the build and test history of VIIRS, why there were no indicators, even with hindsight, of an on-orbit problem, the appearance of the on-orbit anomaly, the initial work attempting to understand and determine the cause, the discovery of the root cause and what Test-As-You-Fly (TAYF) activities, can be done in the future to greatly reduce the likelihood of similar optical anomalies. These TAYF activities are captured in the lessons learned section of this paper.

Iona, Glenn↗
NASA NTRS2017

GEO-LEO Reflective Band Inter-Comparison with BRDF and Atmospheric Scattering Corrections

The inter-comparison of the reflective solar bands (RSB) between the instruments onboard a geostationary orbit satellite and a low Earth orbit satellite is very helpful in assessing their calibration consistency. Himawari-8 was launched 7 October 2014 and GOES-R was launched on 19 November 2016. Unlike previous GOES instruments, the Advanced Himawari Imager (AHI) on Himawari-8 and the Advanced Baseline Imager (ABI) on GOES-R have onboard calibrators for the RSB. Independent assessment of calibration is nonetheless important to enhance their product quality. MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) can provide good references for sensor calibration. In this work, the inter-comparison between AHI and VIIRS is performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with accurate adjustment for band spectral difference, reduction of impact from pixel mismatching, and consistency of BRDF (Bidirectional Reflectance Distribution Function) and atmospheric correction. The site used is the Strzelecki Desert in Australia. Due to the difference in solar and view angles, two corrections must be applied in order to compare the measurements. The first is the atmospheric scattering correction applied to the top of atmosphere reflectance measurements. The second correction is applied to correct the BRDF effect. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) model and the BRDF correction is performed using a semi-empirical model. Our results show that AHI band 1 (0.47 microns) has a good agreement with VIIRS band M3 within 0.15 percent. AHI band 5 (1.61 microns) shows the largest difference (5.09 percent) with VIIRS band M10, while AHI band 5 shows the least difference (1.87 percent) in comparison with VIIRS band I3. The methods developed in this work can also be directly applied to assess GOES-16/ABI (Geostationary Operational Environment Satellite16 / Advanced Baseline Imager) calibration consistency, a topic we will address in the future.

The inter-comparison of the reflective solar bands↗
NASA NTRSDate not supplied

What is LAADS DAAC? How to Download Data from NASA's Source for Cloud and Aerosol Data

The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) primarily archives and distributes data on clouds and aerosols in Earth’s atmosphere in addition to providing Level 0 and 1 Moderate Imaging Radiometer Suite (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and airborne data as well as data from the European Space Agency’s Sea and Land Surface Temperature Radiometer (SLSTR) and the Ocean and Land Colour Instrument (OLCI). Secondarily, LAADS DAAC serves as a backup source for MODIS and VIIRS land products. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS DAAC provides a gateway to data through multiple tools. The newest, View Data, allows users to preview data sets before downloading or applying any post-processing transformations. Learn about how to access LAADS DAAC data, get up-to-date information about LAADS DAAC's migration to hosting data in the cloud, and discover how to use the View Data tool.

Tassia Owen↗
NASA NTRS2022

PACE: How One NASA Mission Aligns With the United Nations Decade of Ocean Science for Sustainable Development (Ocean Shot #1)

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; https://pace.gsfc.nasa.gov) mission, scheduled for launch in January 2024, will extend the continuous high-quality ocean color, atmospheric aerosol, and cloud data records begun by NASA in the late 1990s, building on the heritage of the Coastal Zone Color Scanner (CZCS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) (Figure 1). PACE’s global hyperspectral imaging radiometer design concept will enable new discoveries in Earth’s living ocean (Figure 2), such as the diversity of organisms fueling marine food webs and how aquatic ecosystems respond to environmental change. Its instrument payload (Figure 3) will also observe Earth’s atmosphere to study clouds, airborne aerosol particles, and the interactions between the two. Looking at the ocean, clouds, and aerosols together will improve our knowledge of the roles each plays in our evolving planet. Other applications of PACE science data records—from identifying the frequency, extent, and duration of aquatic harmful algal blooms to improving our understanding of air quality—will result in direct economic, recreational, and societal benefits. Ultimately, by extending and expanding NASA’s long record of global Earth satellite observations, the PACE mission will monitor our home planet in new and advanced ways in the coming decade.

Ocean color↗
NASA NTRSDate not supplied

Creating Near Real-time Hourly VIIRS Radiance Mosaic over Polar Regions from SatCORPS Global Cloud Composite (GCC)

While polar orbiting satellites are essential in providing the needed observations over polar regions for data assimilation, weather diagnoses/forecasting, and flight guidance and situation awareness in airborne field campaigns, there is limited temporal coverage. Often, polar mosaics are created by overlaying multiple satellite imagers on top of each other which can lead to transition lines and discontinuities in the data products. To help ease some of these shortcomings, we utilize the NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) Mosaic algorithm for optimally fusing and merging selected imager radiances from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the Suomi National polar-orbiting Partnership (SNPP), Joint Polar Satellite System (JPSS-1), and JPSS-2 satellites, and the MODerate resolution Imaging Spectroradiometer (MODIS) instruments onboard AQUA and TERRA satellites. Since multiple satellites overpasses and instruments are used in creating hourly 3-km composites over the polar regions, selection of the best satellite data for each 3-km composite pixel is based on aggregated ranking of satellite resolution, time, viewing zenith angle, and distance from terminator. This ranking system provides a smoother transition and improves data discontinuity in the merged output resulting in a more seamless polar region dataset. We will discuss the use of this near real-time dataset to support polar airborne field campaigns and SatCORPS satellite-derived Global Cloud Composite (GCC) generation.

Satellite composites↗
NASA NTRSDate not supplied

LIPA: Lunar Ice Perception Algorithm

The highest concentration of Lunar water-ice stores exists within the Permanently Shadowed Regions (PSRs) of the Lunar South Pole. As such, the ability to locate in situ water-ice stores in an accurate, systematic, and safe manner will prove vital for future Lunar activities which rely on hydrogen-based resources. Here we show how the strong absorptive properties of ice can be exploited (by coupling robotics, infrared imaging techniques, and machine learning) so that surface frost located in PSRs can be easily differentiated from the surrounding frozen regolith. Testbeds which simulate an icy lunar landscape were created and then imaged using a mid-wave infrared (MWIR) camera system mounted to a robotic arm (UR5e). Testbeds were imaged under two filter modes (1) wide band mode: whereby imagery captured filled a spectral range of 3.0 - 5.0 μm and (2) narrow band mode: whereby imagery captured were confined to a single central wavelength (CWL) of 3.15 ± 0.03 μm. A CWL of 3.15 μm was chosen due to the highly absorptive nature of ice at that specific wavelength. Images produced under both camera modes were processed in MATLAB. Narrow band images (NB) were subtracted from their wide band (WB) counterparts to produce differenced images (DI) which clearly demonstrated the spatial extent of ice (e.g., WB – NB = DI). Differenced images were used to train a Microsoft Azure model to discriminate between frozen regolith which did and did not contain ice. These works prove promising for future in situ resource utilization (ISRU) missions which employ robotics in combination with camera systems to advance science objectives (e.g., locate water-ice in frozen regolith) on the lunar surface.

Ane Slabic↗
NASA NTRS2016

Identifying Planetary Biosignature Impostors: Spectral Features of CO and O4 Resulting from Abiotic O2/O3 Production

O2 and O3 have been long considered the most robust individual biosignature gases in a planetary atmosphere, yet multiple mechanisms that may produce them in the absence of life have been described. However, these abiotic planetary mechanisms modify the environment in potentially identifiable ways. Here we briefly discuss two of the most detectable spectral discriminants for abiotic O2/O3: CO and O4. We produce the first explicit self-consistent simulations of these spectral discriminants as they may be seen by James Webb Space Telescope (JWST). If JWST-NIRISS (Near InfraRed Imager and Slitless Spectrograph) and/or NIRSpec (Near InfraRed Spectograph) observe CO (2.35, 4.6 micrometers) in conjunction with CO2 (1.6, 2.0, 4.3 micrometers) in the transmission spectrum of a terrestrial planet it could indicate robust CO2 photolysis and suggest that a future detection of O2 or O3 might not be biogenic. Strong O4 bands seen in transmission at 1.06 and 1.27 micrometers could be diagnostic of a post-runaway O2-dominated atmosphere from massive H-escape. We find that for these false positive scenarios, CO at 2.35 micrometers, CO2 at 2.0 and 4.3 micrometers, and O4 at 1.27 micrometers are all stronger features in transmission than O2/O3 and could be detected with sigal to noise ratios greater than or approximately 3 for an Earth-size planet orbiting a nearby M dwarf star with as few as 10 transits, assuming photon-limited noise. O4 bands could also be sought in UV/VIS/NIR reflected light (at 0.345, 0.36, 0.38, 0.445, 0.475, 0.53, 0.57, 0.63, 1.06, and 1.27 micrometers) by a next generation direct imaging telescope such as LUVOIR (Large Ultraviolet Visible Infrared)/HDST (High-Definition Space Telescope) or HabEx (Habitable-Exoplanet Imaging Mission) and would indicate an oxygen atmosphere too massive to be biologically produced.

planetary atmosphere↗