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NASA NTRS2016

MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records

Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.

Fu, Dejian↗

NASA NTRS1975

Remote sensing by ERTS satellite of vegetational resources believed to be under possible threat of environmental stress

The distribution of natural vegetation on North Merritt Island, Florida, was studied by computer analysis of ERTS satellite multispectral-scanner data. The boundaries of six distinct plant associations were located in photos produced on the image analyzer with an insignificant mean error of -24.38 meters. The six plant associations are described as: aquatic estuarine association, mangrove, spartina swamp, wooded swamp, sabal hammock, and oak-palmetto. The difference in average reflectance 'grey level' between the lowest of the four spectral scanning bands and the highest spectral scanning band for each of the six vegetation types is described. The decreasing trend of the differences is strongly negatively correlated with height of land, the coefficient of correlation being -0.9696.

Pooni, P.↗

NASA NTRS1980

Multispectral data acquisition and classification - Computer modeling for smart sensor design

In this paper a model of the processes involved in multispectral remote sensing and data classification is developed as a tool for designing and evaluating smart sensors. The model has both stochastic and deterministic elements and accounts for solar radiation, atmospheric radiative transfer, surface reflectance, sensor spectral reponses, and classification algorithms. Preliminary results are presented which indicate the validity and usefulness of this approach. Future capabilities of smart sensors will ultimately be limited by the accuracy with which multispectral remote sensing processes and their error sources can be computationally modeled.

Park, S. K.↗

NASA NTRS1982

Parallax studies of four selected fields

Astrometric studies have been completed for four central stars Wolf 294, 39 Com, Case 2, and Vega - and selected reference stars in each of those regions. The parallax of Wolf 294 was measured as 0.1806 + or - 0.0033 arcsec. 39 Com is a visual/astrometric binary with an estimated period of 125 yr and a parallax of 0.0297 + or - 0.0044 arcsec. C 2 was measured as a white dwarf from a Warner and Swasey Observatory spectral survey; its white dwarf status is confirmed by its parallax of 0.0186 + or - 0.0109 arcsec. Vega's parallax was measured as 0.1243 + or - 0.0049 arcsec; a small apparent nonrandom distribution in the residuals is most likely an error from the neutral density filter used for magnitude reduction of the central star.

Russell, J. L.↗

NASA NTRS1984

Evoluation of Landsat-4 image quality for the interpretation of forest, agricultural and soil resources

Landsat-4 Multispectral Scanner (MSS) and Thematic Mapper (TM) sensor performance is being evaluated through the analysis of images generated by computer-compatible tape data and commercially available film products. Natural targets are used to evaluate spectral variability, spatial resolution, radiometric sensitivity, and geometric fidelity. Spectral characteristics are being evaluated through the interpretation of the image tone and texture variability of known features, while spatial characteristics are evaluated through lineal and areal estimates of similar features and the plotting and analysis of residual errors derived from regressions between relative image coordinates and map coordinates.

Degloria, S. D.↗

NASA NTRS1991

Classical Cepheid luminosities from binary companions

Luminosities for the classical Cepheids Eta Aql, W Sgr, and SU Cas are determined from IUE spectra of their binary companions. Spectral types of the companions are determined from the spectra by comparison with the spectra of standard stars. The absolute magnitude inferred from these spectral types is used to determine the absolute magnitude of the Cepheid, either directly or from the magnitude difference between the two stars. For the temperature range of the companions (A0 V), distinctions of a quarter of a spectral subclass can be made in the comparison between the companions and standard stars. The absolute magnitudes for Eta Aql and W Sgr agree well with the period-luminosity-color relation of Feast and Walker (1987). Random errors are estimated to be 0.3 mag. SU Cas, however, is overluminous for pulsation in the fundamental mode, implying that it is pulsating in an overtone.

Evans, Nancy Remage↗

NASA NTRS1994

In search of Nemesis

The parallax of all stars of visual magnitude greater than about 6.5 has already been measured. If Nemesis is a main-sequence star 1 parsec away, this requires Nemesis's mass to be less than about 0.4 solar masses. If it were less than about 0.05 solar masses its gravity would be too weak to trigger a comet storm. If Nemesis is on the main sequence, this mass range requires it to be a red dwarf. A red dwarf companion would probably have been missed by standard astronomical surveys. Nearby stars are usually found because they are bright or have high proper motion. However, Nemesis's proper motion would now be 0.01 arcsec/yr, and if it is a red dwarf its magnitude is about 10 - too dim to attract attention. Unfortunately, standard four-color photometry does not distinguish between red dwarfs and giants. So although surveys such as the Dearborn Red Star Catalog list stars by magnitude and spectral type, they do not identify the dwarfs. Every star of the correct spectral type and magnitude must be scrutinized. Our candidate list is a hybrid; candidate red stars are identified in the astrometrically poor Dearborn Red Star Catalog and their positions are corrected using the Hubble Guide Star Catalog. When errors in the Dearborn catalog make it impossible to identify the corresponding Hubble star, the fields are split so that we have one centering on each possible candidate. We are currently scrutinizing 3098 fields, which we believe contain all possible red dwarf candidates in the northern hemisphere. Since our last report the analysis and database software has been completely rebuilt to take advantage of updated hardware, to make the data more accessible, and to implement improved methods of data analysis. The software is now completed and we are eliminating stars every clear night.

Carlson, S.↗

NASA NTRS1998

The X-Ray, Optical and Infrared Counterpart to GRB 980703

We report on our X-ray, optical and infrared follow-up observations of GRB980703. A previously unknown X-ray source in the GRB error box displays a powerlaw decline with index alpha= -1.0,5(exp +0.24 sub -0.29), fairly consistent with the average optical/infrared decay index alpha = -1.61 plus or minus 0.12. We invoke host galaxy extinction to match the observed spectral slope with the slope expected from 'fireball' models. The hypothesis that between 1998 July 4.4 and 8.4 UT no spectral breaks are present in the infrared to X-ray spectral range is in good agreement with the observations. For these two epochs we obtain an extinction of A(sub v) = 1.50 +/- 0.11 (July 4.4) and A(sub v) = 0.85 +/- 0.26 (July 8.4). From the X-ray data we estimate the optical extinction to be A(sub v) = 20.2(+12.3/-7.3), inconsistent with the former value. Optical spectra we took confirm the redshift of z=0.966 found by Djorgovski et al. We compare the afterglow of GRB 980703 with that of GRB 970508 and find that the fraction of the energy in the magnetic field is much lower in the case of GRB 980703.

Vreeswijk, P. M.↗

NASA NTRS2002

Equivalent Linearization Analysis of Geometrically Nonlinear Random Vibrations Using Commercial Finite Element Codes

Two new equivalent linearization implementations for geometrically nonlinear random vibrations are presented. Both implementations are based upon a novel approach for evaluating the nonlinear stiffness within commercial finite element codes and are suitable for use with any finite element code having geometrically nonlinear static analysis capabilities. The formulation includes a traditional force-error minimization approach and a relatively new version of a potential energy-error minimization approach, which has been generalized for multiple degree-of-freedom systems. Results for a simply supported plate under random acoustic excitation are presented and comparisons of the displacement root-mean-square values and power spectral densities are made with results from a nonlinear time domain numerical simulation.

Rizzi, Stephen A.↗

NASA NTRS2004

A New, More Physically Based Algorithm, for Retrieving Aerosol Properties over Land from MODIS

The MOD Imaging Spectrometer (MODIS) has been successfully retrieving aerosol properties, beginning in early 2000 from Terra and from mid 2002 from Aqua. Over land, the retrieval algorithm makes use of three MODIS channels, in the blue, red and infrared wavelengths. As part of the validation exercises, retrieved spectral aerosol optical thickness (AOT) has been compared via scatterplots against spectral AOT measured by the global Aerosol Robotic NETwork (AERONET). On one hand, global and long term validation looks promising, with two-thirds (average plus and minus one standard deviation) of all points falling between published expected error bars. On the other hand, regression of these points shows a positive y-offset and a slope less than 1.0. For individual regions, such as along the U.S. East Coast, the offset and slope are even worse. Here, we introduce an overhaul of the algorithm for retrieving aerosol properties over land. Some well-known weaknesses in the current aerosol retrieval from MODIS include: a) rigid assumptions about the underlying surface reflectance, b) limited aerosol models to choose from, c) simplified (scalar) radiative transfer (RT) calculations used to simulate satellite observations, and d) assumption that aerosol is transparent in the infrared channel. The new algorithm attempts to address all four problems: a) The new algorithm will include surface type information, instead of fixed ratios of the reflectance in the visible channels to the mid-IR reflectance. b) It will include updated aerosol optical properties to reflect the growing aerosol retrieved from eight-plus years of AERONE". operation. c) The effects of polarization will be including using vector RT calculations. d) Most importantly, the new algorithm does not assume that aerosol is transparent in the infrared channel. It will be an inversion of reflectance observed in the three channels (blue, red, and infrared), rather than iterative single channel retrievals. Thus, this new formulation of the MODIS aerosol retrieval over land includes more physically based surface, aerosol and radiative transfer with fewer potentially erroneous assumptions.

Levy, Robert C.↗

NASA NTRS2005

ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Kiely, A.↗

NASA NTRS2016

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Babcock, Chad↗

NASA NTRSDate not supplied

Wavelength Calibration of the Full-sun Ultraviolet Rocket SpecTrograph (FURST)

The Sun has a well-known periodicity in sunspot number and magnetic field variation. The underlying cause of this 11-year cycle is not fully understood and has yet to be connected with those processes in other stellar objects. The Full-sun Ultraviolet Rocket SpecTrograph (FURST) is a sounding rocket payload being developed by Montana State University (MSU) alongside the Marshall Space Flight Center(MSFC) solar physics group. Scheduled to launch from White Sands Missile Range (WSMR) in 2022, this instrument is unique in that it will provide the connection between stellar observatories with measurements of our Sun. It will achieve this through measuring high-resolution full-disk spectral irradiance. We aim to obtain a wavelength resolution R>10,000 in the 120 - 181 nm UltraViolet (UV) range, on par with that of the Hubble (HST) Space Telescope Imaging Spectrograph (STIS). This resolution goal will allow us to study the relatively low-temperature plasma in the chromosphere and lower corona with spectral accuracy down to 0.1 Å (a Doppler-shift of about±30 km/s). In addition, the Lyman Alpha(121 nm) line is known to saturate most CCD electronics. These factors illustrate the particular challenge of precise wavelength calibration for this spectral range. We are building a collimator in order to calibrate the FURST instrument under these strict spectral requirements. This paper will present the results of our simulation of the diagnostic lamp signal to be used for wavelength calibration. The simulation allows us to begin to account for photon noise, electronic readout noise, and statistical error. These in turn lead to the development of our pre- and post-launch calibration plans. Future work includes absolute radiometric and wavelength calibration with this new collimator. In addition, the ability of FURST to measure small Doppler-shifts will provide capabilities for planetary atmospheric scientists. This impact is coupled with the diverse international partnership created by the closely-knit Sounding Rocket teams around the globe. Sounding Rockets like FURST have an even broader impact, as they encourage future satellite missions under the prospect of long-term observations

FURST↗

NASA NTRS2018

Image Guider Subsystem Analysis for the GHAPS Project

The Gondola for High-Altitude Planetary Science (GHAPS) project is a balloon-borne astronomical observatory designed operate in the UV, Visible, and near-mid IR spectral region. The GHAPS Optical Telescope Assembly (OTA) is designed around a one meter aperture narrow field-of-view telescope with near diffraction limited performance. GHAPS will utilize Wallops Arc-Second Pointing System (WASP) for pointing the OTA with an accuracy of 1 arc second or better. WASP relies heavily on a self-contained star tracker assembly to determine the OTA line of sight. Preliminary structural analysis indicated that potential misalignments could be present between the OTA line of sight and the star tracker FOV center during the expected flight conditions that could compromise GHAPS pointing accuracy. An analysis is presented that estimates the worst case long-term (or bias) pointing misalignments for the GHAPS opto-mechanical configuration, examines the need for additional hardware to correct pointing errors, and determines the best hardware and software implementation to do so. The analysis includes the development of a photometric model to predict the limiting magnitude of a GHAPS Facility Guide System (FGS) for a variety of image sensor technologies from visible to mid IR. FGS system performance is estimated using star magnitude and spectral data from actual star catalogs for more realistic predictions. Based on expected performance and other factors, such as size, weight, power, and cost, a final recommendation is made for the GHAPS configuration.

Telescope Guider↗

NASA NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗

NASA NTRS2023

Modeling Global Indices for Estimating Non-Photosynthetic Vegetation Cover

Non-photosynthetic vegetation (NPV) includes plant litter, senesced leaves, and crop residues. NPV plays an essential role in terrestrial ecosystem processes, and is an important indicator of drought severity, ecosystem disturbance, agricultural resilience, and wildfire danger. Current moderate spatial resolution multispectral satellite systems (e.g., Landsat and Sentinel-2) have only a single band in the 2000–2500 nm shortwave infrared “SWIR2” range where non-pigment biochemical constituents of NPV, including cellulose and lignin, have important spectral absorption features. Thus, these current systems have suboptimal capabilities for characterizing NPV cover. This research used simulated spectral mixtures accounting for variability among NPV and soils to evaluate globally-appropriate hyperspectral and multispectral indices for estimation of fractional NPV cover. The Continuum Interpolated NPV Depth Index (CINDI), a weighted ratio index measuring lignocellulose absorption near 2100 nm, was found to produce the lowest error in estimating NPV cover. CINDI was less sensitive to variability in soil spectra and green vegetation cover than competing indices. While CINDI was sensitive to the relative water content of soil and NPV, this sensitivity allowed for correcting error in estimated NPV cover as water content increased. CINDI bands were less capable than Dual Absorption NPV Index (DANI) bands for maintaining continuity with the heritage Landsat SWIR2 band, but combining multiple CINDI bands demonstrated adequate continuity. Three SWIR2 bands with band centers at 2038, 2108, and 2211 nm can provide superior capabilities for future moderate resolution multispectral/superspectral systems targeting NPV monitoring, including the next generation Landsat mission (Landsat Next). These bands and the associated CINDI index provide potential for global NPV monitoring using a constellation of future superspectral sensors and imaging spectrometers, with applications including improving soil management, preventing land degradation, evaluating impacts of drought, mapping ecosystem disturbance, and assessing wildfire danger.

Index optimization↗

NASA NTRS1985

Advanced Moisture and Temperature Sounder (AMTS) study

Retrieval of tropospheric humidity profiles from satellite-based upwelling radiances are shown to be improved by using physical methods for obtaining first-guess profiles as well as for inverting the radiative transfer equation by relaxation. The first guess is based on an empirically verified hypothesis, from theoretical considerations, that the brightness temperature corresponding to the radiance should be approximately equal to the actual temperatue at a channel-invariant optical depth provided that the surface and stratospheric contributions to the radiance are small. Even greater improvement of retrieved humidity profiles can be accomplished by increasing the number of channels used and by selecting their spectral location and bandpass to obtain sharper independent weighting functions. For example, the AMTS system, with high resolution water channels at 1650, 1700, 1839, 1850 and 1930 cm, is shown to be capable of reducing the retrieved water vapor errors in 200 mb thick layers by a factor of two or three relative to the HIRS-2 system errors. Expected AMTS errors in tropical layer water content are particularly low, less than 20% at all levels, and of the order of 10% or less in the middle troposphere.

Kaplan, L. D.↗

NASA NTRS1988

Rocketdyne automated dynamics data analysis and management system

An automated dynamics data analysis and management systems implemented on a DEC VAX minicomputer cluster is described. Multichannel acquisition, Fast Fourier Transformation analysis, and an online database have significantly improved the analysis of wideband transducer responses from Space Shuttle Main Engine testing. Leakage error correction to recover sinusoid amplitudes and correct for frequency slewing is described. The phase errors caused by FM recorder/playback head misalignment are automatically measured and used to correct the data. Data compression methods are described and compared. The system hardware is described. Applications using the data base are introduced, including software for power spectral density, instantaneous time history, amplitude histogram, fatigue analysis, and rotordynamics expert system analysis.

Tarn, Robert B.↗