Search NASA⌕ Search

SEARCH · Search NASA

Results for “SPECTRAL BANDS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Two-Flux and Green's Function Method for Transient Radiative Transfer in a Semi-Transparent Layer

A method using a Green's function is developed for computing transient temperatures in a semitransparent layer by using the two-flux method coupled with the transient energy equation. Each boundary of the layer is exposed to a hot or cold radiative environment, and is heated or cooled by convection. The layer refractive index is larger than one, and the effect of internal reflections is included with the boundaries assumed diffuse. The analysis accounts for internal emission, absorption, heat conduction, and isotropic scattering. Spectrally dependent radiative properties are included, and transient results are given to illustrate two-band spectral behavior with optically thin and thick bands. Transient results using the present Green's function method are verified for a gray layer by comparison with a finite difference solution of the exact radiative transfer equations; excellent agreement is obtained. The present method requires only moderate computing times and incorporates isotropic scattering without additional complexity. Typical temperature distributions are given to illustrate application of the method by examining the effect of strong radiative heating on one side of a layer with convective cooling on the other side, and the interaction of strong convective heating with radiative cooling from the layer interior.

Siegel, Robert↗
NASA NTRS1973

Broad-band 20-micron photometry of 76 stars

Observations in the 16 to 28 micron spectral band made with an infrared photometer mounted at the Cassegrain f/10 focus of a 2.24-m telescope are discussed. The stars observed belonged to classes B through M and included several carbon and S stars. Most of them are Mira, semiregular, or irregular variables. The remaining 12 stars are nonvariable objects of which the brightest (both in the visible and infrared) are alpha-Boo and alpha-Tau. Since 16 of the Mira stars varied during the period of observation, it is concluded that they are probably intrinsic variables at 20 microns. There is no conclusive evidence for variation of any other star. Because the variation at this wavelength originates largely in circumstellar shells for most of these stars, the nonvariability suggests that these shells are stable phenomena, at least on a time scale of a year.

Morrison, D.↗
NASA NTRS1975

Plan for the uniform mapping of earth resources and environmental complexes from Skylab imagery. Assessment of natural vegetation, environmental, and crop analogs

The author has identified the following significant results. For interpreting a wide range of natural vegetation analogs, S-190A color infrared and the ERTS-1 color composite were consistently more useful than were conventional color or black and white photos. Color infrared was superior for five vegetation analogs while color was superior for only three. The errors in identification appeared to associate more with black and white single band images than with multiband color. For rice crop analogs, spectral and spatial discriminations both contribute to the usefulness of images for data collection. Tests and subjective analyses conducted in this study indicated that the spectral bands exploited in color infrared film were the most useful for agricultural crop analysis. Accuracy of crop identification on any single date of Skylab images was less than that of multidate analysis due to differences in crop calendar, cultural practices used, rice variety, planting date, planting method, water use, fertilization, disease, or mechanical problems.

Poulton, C. E.↗
NASA NTRS2008

MODIS On-board Blackbody Performance

Currently, there are two MODIS instruments operated on-orbit: one on-board the Terra spacecraft launched in December 1999 and the other on-board the Aqua spacecraft launched in May 2002. MODIS is a scanning radiometer that has 16 thermal emissive bands (TEBs) in the MWIR and LWIR regions. The remaining spectral bands are in the VISINIR and SWIR regions. The TEBs have a total of 160 detectors (10 detectors per band), which are calibrated on-orbit using an on-board blackbody (BB). MODIS TEB calibration is performed via a quadratic algorithm with its linear calibration coefficients updated on a scan-by-scan basis using each detector's response to the BB. The offset and nonlinear terms of the quadratic calibration equation are stored in a look-up table (LUT). The LUT parameters are derived from pre-launch calibration and updated on-orbit from BB observations, as needed. Typically, the BB is set at a fixed temperature. Periodically, a warm-up and cool-down activity is performed, which enables the BB temperature to be varied from instrument ambient up to 315K. The temperature of the BB is measured each scan using 12 thermistors, which were fully characterized pre-launch with reference to the NIST temperature scale. This paper describes MODIS on-board BB operational activities and performance. The TEB detector response (short-term stability and long-term changes) and noise characterization results derived from BB observations and their impact on the TEB calibration uncertainty are also presented.

Xiong, Xiaoxiong↗
NASA NTRS2007

Detector Noise Characterization and Performance of MODIS Thermal Emissive Bands

MODIS has 16 thermal emissive bands, a total of 160 individual detectors (10 for each spectral bands), located on the two cold focal plane assemblies (CFPA). MODIS TEB detectors were fully characterized pre-launch in a thermal vacuum (TV) environment using a NIST traceable blackbody calibration source (BCS) with temperatures ranging from 170 to 340K. On-orbit the TEB detectors are calibrated using an on-board blackbody (BB) on a scan-by-scan basis. For nominal on-orbit operation, the on-board BB temperature is typically controlled at 285K for Aqua MODIS and 290K for Terra MODIS. For the MODIS TEB calibration, each detector's noise equivalent temperature difference (NEdT) is often used to assess its performance and this parameter is a major contributor to the calibration uncertainty. Because of its impact on sensor calibration and data product quality, each MODIS TEB detector's NEdT is monitored on a daily basis at a fixed BB temperature and completely characterized on a regular basis at a number of BB temperatures. In this paper, we describe MODIS on-orbit TEB NEdT characterization activities, approaches, and results. We compare both pre-launch and on-orbit performance with sensor design specification and examine detector noise characterization impact on the calibration uncertainty. To date, 135 TEB detectors (out of a total of 160 detectors) in Terra MODIS (launched in December 1999) and 158 in Aqua MODIS (launched in May 2002) continue to perform with their NEdT below (or better than) their design specifications. A complete summary of all TEB noisy detectors, identified both pre-launch and on-orbit, is provided.

Xiong, X.↗
NASA NTRSDate not supplied

Langley Automated Sensor Inter-calibration System (LASICS): Open Access Tools for Satellite Imager Inter-Calibration

Satellite imager calibration teams are tasked with maintaining stable measurement records to facilitate reliable monitoring of geophysical parameters and ensure dependable input for weather forecast models. Satellite imagers are neither uniformly calibrated nor radiometrically scaled to a common reference. Consistent inter-calibration between various earth-orbiting satellite imager pairs is a critical step in the creation of seamless earth-scene reflectance data records over time for input to higher level algorithms that retrieve earth system climate-sensitive properties. Each imager inherently by virtue of its optics (and associated properties like Spectral Response etc.) will have a unique measurement of the same earth-scene reflected signal. A key part of this is the identification and prediction of events where the imager pairs from their respective earth-orbits view the same stable terrestrial targets with nearly identical viewing and solar geometry. Langley Automated Sensor Inter-calibration System (LASICS) will provide the Earth remote sensing community with a foundation for the harmonization of these remote sensing records by the development of an intuitive, user-friendly, interactive web-based open access service that will leverage, an existing extensive and ever-growing database of earth-imager channel spectral response functions, on-demand capabilities for computation and visualization of spectral band adjustment factors using a variety of external hyper-spectral earth observation sources (e.g. SCIAMACHY, GOME-2 for VIS and IASI, AIRS for IR) and a variety of Solar Irradiance Spectra.

Arun Gopalan↗
NASA NTRS2016

JPSS-1 VIIRS Version 2 At-Launch Relative Spectral Response Characterization and Performance

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Chris Moeller↗
NASA NTRS2020

SNPP VIIRS Reflective Solar Bands On-Orbit Calibration Using the Moon

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-Orbiting Partnership (SNPP) satellite has been on orbit for more than eight years since its launch on October 28, 2011. The VIIRS has 22 spectral bands, among which 14 are reflective solar bands(RSBs) covering a spectral range from 0.41 to 2.25 m. The VIIRS RSBs are primarily calibrated on-orbit by an onboard solar diffuser (SD) panel and a solar diffuser stability monitor (SDSM). Besides the SD and SDSM calibration, the RSBs are scheduled to view the Moon approximately monthly through the instrument’s space view (SV). The lunar observations have also been used to calibrate the RSBs on-orbit since early mission. Due to the non uniformity of the SD’s degradation, the calibration coefficients that are derived from the SD/SDSM calibration have long-term biases, especially at short wavelengths. In addition, the SDSM has no capability to monitor the SD degradation beyond 0.935 m, resulting in long-term bias in the shortwave infrared bands, about 0.72% for band M8 (1.238 m). These biases induce significant errors and long-term drifts in the VIIRS sensor data records (SDR) and consequently in the environmental data records (EDR). Unlike the SD, the Moon is a known stable target and any temporal drifts observed while viewing the Moon can be attributed to the sensor’s degradation. Thus, the VIIRS lunar calibration is used to track the RSB on-orbit changes, especially to provide an accurate long-term baseline. Due to the non-uniformity of the lunar surface, the lunar irradiance, instead of the lunar radiance, is used to calibrate the RSBs. The lunar irradiance strongly depends on lunar view geometry and it is still a challenge to accurately characterize the geometric effects associated with the lunar measurements and any residual errors can induce seasonal oscillations in the derived calibration coefficients. The errors of the geometric dependence correction induce seasonal oscillations in the derived RSB lunar calibration coefficients. In this paper, the algorithms for the view geometric effect correction are significantly improved, resulting in a significant reduction in the seasonal oscillations observed in the calibration coefficient time-series. The lunar and SD/SDSM calibration results are properly incorporated to generate a set of hybrid calibration coefficients and implementation of these coefficients is shown to significantly improve the long-term stability of the VIIRS SDR. This is of fundamental importance in making accurate Earth observations from which reliable and high quality science products are generated. The consequent improvements in SNPP VIIRS RSB SDRs and EDRs are shown and discussed. The lunar calibration methodology can be directly applied to follow-on VIIRS instruments.

Junqiang Sun↗
NASA NTRSDate not supplied

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.↗
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.↗