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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 325 records · Page 18
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Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗
NASA NTRS1975

Infrared emission spectra of elastohydrodynamic contacts

A small diamond disk mounted as a window in a steel plate was covered with test fluid, and a weighted steel ball was rotated over the window so as to form a sliding elastohydrodynamic (EHD) contact region. Some of the radiant energy generated in this region, both in the fluid and at the boundaries, passed through the window into an infrared interferometer, giving rise to an emission spectrum. This spectrum could be separated into contributions from the fluid and from the ball surface, making it possible, by appropriate calibrations, to estimate their temperatures separately under operating conditions. Moreover, the shape of the discrete spectral bands of the fluid permitted some inferences on its state. Two fluids were studied under identical mechanical conditions, a polyester and a naphthenic oil, each containing an equal amount of polymethylstyrene as a spectral indicator. Differences of band intensity, band width, and frequency could, therefore, be attributed to differences in the behavior of the base fluid.

Lauer, J. L.↗
DOE OSTI2026

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS2009

Improved Determination of Surface and Atmospheric Temperatures Using Only Shortwave AIRS Channels

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. AIRS is a grating spectrometer with a number of linear arrays of detectors with each detector sensitive to outgoing radiation in a characteristic frequency v(sub i) with a spectral band pass delta v(sub i) of roughly v(sub i) /1200. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(exp -1) (15.38 gm) - 2665 cm(exp -1)' (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometer (longwave) CO2 band, and the 4.3 micrometer (shortwave) CO, absorption band. There are also two atmospheric window regions, the 12 micrometerm - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. One reason for this was concerns about the effects, during the day, of reflected sunlight and non-Local Thermodynamic Equilibrium (non-LTE) on the observed radiances in the shortwave portion of the spectrum. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses the longwave channels to determine cloud cleared radiances R(sub i) for all channels, and uses R(sub i) only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used by the AIRS Science Team in preparation for the AIRS Version 6 Retrieval Algorithm. This paper describes how the effects on the radiances of solar radiation reflected by clouds and the Earth's surface, and also of non-LTE, are accounted for in the analysis of the data. Results are presented for both daytime and nighttime conditions showing improved surface and atmospheric soundings under partial cloud cover resulted from not using R(sub i) in the retrieval process for any longwave channels sensitive to cloud effects. This improvement is made possible because AIRS NEDT in the shortwave portion of the spectrum is extremely low.

Susskind,Joel↗
NASA NTRS1972

Survey of the seasonal snow cover of Alaska

The author has identified the following significant results. The delineation of the transient snow cover can generally be made directly from any of the RBV of MSS images. On many glaciers, however, there seems to be a relatively small difference between the reflectivities of snow and ice in the visible portion of the spectrum (corresponding to MSS bands 4 and 5). On the other hand, the reflectivity is distinctly lower for ice than for snow in the near infrared (MSS bands 6 and 7). By applying the sensors of the latter spectral bands the position of the transient snowline, indicative of the mass balance, can in many cases be determined with what appears to be a satisfactory accuracy. This circumstance should prove especially useful in studies of regional variations of glacier mass balances. It had been found that the effect of winds early in the fall seasons can be seen on the arctic slope when a light dusting of snow is present. Winds channeled by topography redistribute the snow and actually remove it from regions. After freeze up has occurred and a continuous snow cover exists it is possible to identify open water reaches on streams flowing through the region. Such cases are identifiable on the ERTS images especially on the MSS 7 images.

Weller, G. E.↗
NASA NTRS1978

Some observations about LANDSAT digital analysis

Several hypotheses concerning LANDSAT data are analyzed. These hypotheses are: (1) LANDSAT does not discriminate vegetation types, but mostly sees chlorophyl and canopy cover. (2) A majority of the features in the ground scene possess linearly proportional amounts of color from each spectral band. (3) The data are continuous and as a result there is no true separability of ground scene features in the data, but some features possess an excess of color in a particular band pair. (4) There are relatively few features present in the spectral data, and these do not correspond to the conventional definitions that are used. (5) Aside from seasonal effects, in a distributional sense all LANDSAT data are essentially the same. The only difference is the way the data are spatially arranged in the image.

Jayroe, R. R., Jr.↗
NASA NTRS1983

Assessment of Thematic Mapper band-to-band registration by the block correlation method

Rectangular blocks of pixels from one band image were statistically correlated against blocks centered on identical pixels from a second band image. The block pairs were shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient to the maximum correlation was taken as the best estimate of registration error for each block pair. For the band combinations of the Arkansas scene studied, the misregistration of TM spectral bands within the noncooled focal plane lie well within the 0.2 pixel target specification. Misregistration between the middle IR bands is well within this specification also. The thermal IR band has an apparent misregistration with TM band 7 of approximately 3 pixels in each direction. The TM band 3 has a misregistration of approximately 0.2 pixel in the across-scan direction and 0.5 pixel in the along-scan direction, with both TM bands 5 and 7.

Card, D. H.↗
NASA NTRS1985

Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

Rectangular blocks of pixels from one band image were statistically correlated against blocks centered on identical pixels from a second band image. The block pairs were shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient to the maximum correlation was taken as the best estimate of registration error for each block pair. For the band combinations of the Arkansas scene studied, the misregistration of TM spectral bands within the noncooled focal plane lie well within the 0.2 pixel target specification. Misregistration between the middle IR bands is well within this specification also. The thermal IR band has an apparent misregistration with TM band 7 of approximately 3 pixels in each direction. The TM band 3 has a misregistration of approximately 0.2 pixel in the across-scan direction and 0.5 pixel in the along-scan direction, with both TM bands 5 and 7.

Card, D. H.↗
NASA NTRS1990

MODIS-N - Moderate Resolution Imaging Spectrometer-Nadir

The Moderate Resolution Imaging Spectrometer-Nadir (MODIS-N) for the Earth Observing System (EOS) is intended to provide daily global surveys for the atmosphere, the oceans, and the land. To achieve this capability, MODIS-N requires an at-least 2300-km swath width, and provides geometric-instantaneous-fields-of-view (GIFOVs) that are either 856 m, 428 m, or 214 m in size with reference to a 705 km satellite altitude. The 214 m GIFOV may or may not be used depending on total data rate impact assessments traded with science needs. To achieve the data for the multiplicity of science investigations MODIS-N provides nominally 36 spectral bands that are selected for specific locations and bandpasses in the spectral range from the visible to the long wave infrared. Another driver of this instrument combination is the need for long term spectral and radiometric calibration stability. Specific calibration capabilities are to be built into MODIS-N to achieve calibration knowledge over a 5 year operational life.

Weber, Richard R.↗
NASA NTRS1993

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a multispectral imaging radiometer scheduled to fly in Earth orbit in 1998 on NASA's Earth Observation System platform. The instrument will have 14 spectral bands from the visible to thermal infrared wavelength regions with high spectral and spatial resolution and with along-track stereoscopic capability. ASTER imagery will be used to study such phenomena as Earth surface properties, elements of the surface heat balance, cloud cover characteristics, glacier and sea ice extent, patterns of vegetation and land use, volcanoes, coral reefs and coastal processes, geology and topography, and hydrology. ASTER will have three separate radiometer subsystems, each with a swath width of 60 km. Any point on the globe will be accessible at least once every 16 days for the short wavelength infrared and thermal infrared subsystems, and once every five days for the visible and near infrared subsystem. Instrument and spacecraft resources are allocated to support an 8 percent average duty cycle, corresponding to over 700 60 by 60-km scenes per day. ASTER data will be acquired and processed according to specific user requirements over its five-year mission.

Kahle, Anne B.↗
NASA NTRS2019

Sensitivity of Inherent Optical Properties from Ocean Reflectance Inversion Models to Satellite Instrument Wavelength Suites

The Earth science community seeks to develop climate data records (CDRs) from satellite measurements of ocean color, a continuous data record that now exceeds 20 years. Space agencies will launch additional instruments in the coming decade that will continue this data record, including the NASA PACE spectrometer. Inherent optical properties (IOPs) quantitatively describe the absorbing and scattering constituents of seawater and can be estimated from satellite-observed spectroradiometric data using semi-analytical algorithms (SAAs). SAAs exploit the contrasting optical signatures of constituent matter at spectral bands observed by satellite sensors. SAA performance, therefore, depends on the spectral resolution of the satellite spectroradiometer. A CDR spanning SeaWiFS, MODIS, OLCI, and PACE, for example, would include IOPs derived using varied wavelength suites if all available wavelengths were considered. Here, we explored differences in derived IOPs that stem simply from the use of (eight) different wavelength suites of input radiometric measurements. Using synthesized data and SeaWiFS Level-3 mission-long composites, we demonstrated equivalent SAA performance for all wavelength suites, but that IOP retrievals vary by several percent across wavelength suites and as a function of water type. The differences equate to roughly ≤ 6, 12, and 7% for a(sub dg)(443), a(sub ph)(443), and b(sub bp)(443), respectively, for waters with C(sub a) ≤ 1 mg -cu m. These values shrink for sensors with similar wavelength suites (e.g., SeaWiFS, MODIS, and MERIS) and rise to substantially larger values for higher C(sub a) waters. Our results also indicate that including 400 nm (in the case of OLCI) influences the derived IOPs, using longer wavelengths (>600 nm) influences the derived IOPs when there is a red signal, and, including additional spectral information shows potential for improved IOP estimation, but not without revisiting SAA parameterizations and execution. While modest in scope, we believe this study contributes to the knowledge base for CDR development. The implication of ignoring such an analysis as CDRs continue to be developed is a prolonged inability to distinguish between algorithmic and environmental contributions to trends and anomalies in the IOP time-series.

ocean color satellites↗
NASA NTRS2021

Spatial Registration Assessments for the SNPP and N20 VIIRS Reflective Solar Bands Using Unscheduled Lunar Observations

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a multi-spectral Earth-observing instrument on board the Suomi-NPP (SNPP) and NOAA-20 (N20) spacecraft, with spectral bands ranging in wavelength from 0.41 to 12.2 μm. For the reflective solar bands (RSB), the bands are calibrated on orbit using both solar diffuser (SD) and lunar observations. The lunar observations use near-monthly scheduled spacecraft maneuvers in order to view the Moon within a desired phase angle range. While the primary purpose of the maneuvers is for radiometric calibration, these observations can also be used to characterize the spatial performance of the instrument, including the band-to-band and detector-to-detector registration (BBR/DDR). The Moon can also be observed without spacecraft maneuvers. However, these observations are over a larger phase angle range. While the geometry of these unscheduled observations is more varied, they can still be used to assess the sensor performance. In this work, we will use unscheduled Moon data to analyze the BBR and DDR of the SNPP and N20 VIIRS RSB. For the BBR, we implemented an image cross-correlation approach, which removes the residual oscillations in the trending data when compared to previous methodologies. For the DDR, we developed an edge fitting approach that accounts for the lunar motion across the VIIRS focal plane array on a scan-by-scan basis using lunar and satellite ephemeris data. In our analysis, we find that the BBR and DDR for both VIIRS RSB are stable on orbit.

Band-to-band registration (BBR)↗
NASA NTRS2018

Hawkeye Radiometric Calibration Methodology

Hawkeye is an ocean color instrument designed, manufactured and characterized at Cloud land Instruments, CA. It is a push broom instrument that has 8spectral bands similar to SeaWiFS and a spatial resolution of 120 m. Each spectral band has 1800 detectors (pixels) and all 14,000 detectors (pixels) need to be calibrated independently. This paper describes the preliminary design of on-orbit calibration method to correct for the instrument response's temperature sensitivity,scan angle dependency in radiometric sensitivity, relative spectral response (RSR),non linearity, and polarization sensitivity. We will provide a brief description on how each of the calibration parameters are used to address the instrument characteristics and how the calibration parameters are derived from instrument test data and use to retrieve ocean color products.

Lee, Shihyan↗
NASA NTRS1974

Mapping of hydrothermal alternation zones and regional rock types using computer enhanced ERTS MSS images

A combination of digital computer processing and color compositing of ERTS MSS images has been used to map hydrothermal alternation zones and regional rock types in south-central Nevada. The technique is based on enhancement of subtle visible and near infrared reflectivity differences between mineralogically dissimilar rocks, especially unaltered and altered rocks. MSS spectral bands are ratioed, pixel by pixel, in the computer and subsequently stretched. These ratio values are used to produce a new black and white image which shows the subtle spectral reflectivity differences. Additional enhancement is achieved by preparing color composites of two or more stretched ratio images. The choice of MSS bands for rationing depends on the spectral reflectance properties of the rocks to be discriminated. Although this technique is in the initial stage of development and is untested in other areas, it already appears to have considerable potential for targeting mineral prospects and for regional geologic mapping.

Rowan, L. C.↗
NASA NTRS2021

Ten Years of SNPP VIIRS Reflective Solar Bands On-Orbit Calibration and Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) has successfully operated on-orbit for nearly ten years since its launch in October 2011, continuously making global observations and improving studies of changes in the Earth’s climate and environment. VIIRS has 22 spectral bands, among which 14 are reflective solar bands (RSBs) covering a spectral range from 0.41 to 2.25 μm. The SNPP VIIRS RSBs are primarily calibrated by the onboard solar diffuser (SD), with its on-orbit degradation tracked by an onboard SD stability monitor (SDSM). The near-monthly scheduled lunar observations, together with the sensor responses over stable ground targets, have contributed to the sensor’s mission-long on-orbit calibration and characterization. Numerous improvements have been made in the RSB calibration methodology since SNPP VIIRS was launched, and the RSB calibration has reached a mature stage after almost ten years of on-orbit operation. SNPP is a joint NASA/NOAA mission and there are two teams, the NASA VIIRS Calibration Support Team (VCST) and the NOAA VIIRS Sensor Data Record Team, which are dedicated to SNPP VIIRS on-orbit calibration. In this paper, we focus on the calibration performed by the NASA VCST. The SNPP VIIRS RSB calibration methodologies used to produce the calibration coefficient look up tables for the latest NASA Level 1B Collection 2 products are reviewed and the calibration improvements incorporated in this collection are described. Recent calibration changes include the removal of image striping caused by non-uniform degradation of the SD, improvements to the method for combining lunar and SD data, mitigation of the effects due a recent anomaly in the SD measurements, estimation of the SD degradation beyond 935 nm, and fitting strategy improvements for look-up table delivery. Overall, the SNPP VIIRS RSBs have performed well since its launch and continue to meet design specifications.

SNPP↗
NASA NTRS1972

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

Source record↗
NASA NTRS1980

Stochastic analysis of multiple-passband spectral classifications systems affected by observation errors

The classification of targets viewed by a pushbroom type multiple band spectral scanner by algorithms suitable for implementation in high speed online digital circuits is considered. A class of algorithms suitable for use with a pipelined classifier is investigated through simulations based on observed data from agricultural targets. It is shown that time distribution of target types is an important determining factor in classification efficiency.

Tsokos, C. P.↗
NASA NTRS1994

On the interaction of jet noise with a nearby flexible structure

The model of the interaction of the noise from a spreading subsonic jet with a panel-stringer assembly is studied numerically in two dimensions. The radiation resulting from this flow/acoustic/structure coupling is computed and analyzed in both the time and frequency domains. The jet is initially excited by a pulse-like source inserted into the flow field. The pulse triggers instabilities associated with the inviscid instability of the jet mean flow shear layer. These instabilities in turn generate sound which provides the primary loading for the panels. The resulting structural vibration and radiation depends strongly on their placement relative to the jet/nozzle configuration. Results are obtained for the panel responses as well as the transmitted and incident pressure. The effect of the panels is to act as a narrow filter, converting the relatively broad band forcing, heavily influenced by jet instabilities, into radiation concentrated in narrow spectral bands.

Mcgreevy, J. L.↗