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DOE OSTI2024

Multiwavelength Investigation of γ-Ray Source MGRO J1908+06 Emission Using Fermi-LAT, VERITAS and HAWC

This paper investigates the origin of the γ-ray emission from MGRO J1908+06 in the GeV–TeV energy band. By analyzing the data collected by the Fermi Large Area Telescope, the Very Energetic Radiation Imaging Telescope Array System, and High Altitude Water Cherenkov, with the addition of spectral data previously reported by LHAASO, a multiwavelength study of the morphological and spectral features of MGRO J1908+06 provides insight into the origin of the γ-ray emission. The mechanism behind the bright TeV emission is studied by constraining the magnetic field strength, the source age, and the distance through detailed broadband modeling. Both spectral shape and energy-dependent morphology support the scenario that inverse Compton emission of an evolved pulsar wind nebula associated with PSR J1907+0602 is responsible for the MGRO J1908+06 γ-ray emission with a best-fit true age of T = 22 ± 9 kyr and a magnetic field of B = 5.4 ± 0.8 μG, assuming the distance to the pulsar d PSR = 3.2 kpc.

Gamma-ray astronomy↗

NASA NTRS1993

Signal processing of aircraft flyover noise

A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a level uniform flyover is considered in the study, but the code can accept more general flight profiles. The effects of spectral smearing and its removal are discussed. Using test data acquired from an XV-15 tilt-rotor flyover, comparisons are made between the measured and corrected spectra. Frequency shifts are accurately accounted for by the de-Dopplerization procedure. It is shown that by correcting for spherical spreading and Doppler amplitude, along with frequency, can give some idea about noise source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

Kelly, J. J.↗

NASA NTRS2000

Hyperspectral Imaging Sensors and the Marine Coastal Zone

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Richardson, Laurie L.↗

DOE OSTI2016

Towards an improved understanding of the influence of subpixel vegetation structure on pixel-level spectra: a simulation approach

The planned NASA Hyperspectral Infrared Imager (HyspIRI) mission, equipped with an imaging spectrometer that has the capability of monitoring ecosystems globally, will provide an unprecedented opportunity to address scientific challenges related to ecosystem function and change. However, uncertainty remains around the impact of subpixel vegetation structure, in combination with the point spread function, on pixel-level imaging spectroscopy data. We estimated structural parameters, e.g., leaf area index (LAI), canopy cover, and tree location, from HyspIRI spectral data, with the goal of assessing how subpixel variation in these parameters impact pixel-level imaging spectroscopy data. The fine-scale variability of real vegetation structure makes this a challenging endeavor. Therefore, we utilized a simulation-based approach to counter the time-consuming and often destructive sampling needs of vegetation structural analysis and to simultaneously generate synthetic HyspIRI data pre-launch. Three virtual scenes were constructed, corresponding to the actual vegetation structure in the National Ecological Observatory Network’s (NEON) Pacific Southwest Domain (Fresno, CA). These included an oak savanna, a dense coniferous forest, and a conifer-manzanita-mixed forest. Simulated spectroscopy data for these scenes were then generated using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Simulations first were used to verify the physical model, virtual scene geometrical information, and simulation parameters. This was followed by simulations of HyspIRI data, where within-pixel structural variability was introduced, e.g., by iteratively changing per-pixel canopy cover and tree placement, tree clustering, leaf area index (LAI), etc., between simulation runs for the virtual scenes. Finally, narrow-band vegetation indices (VIs) were extracted from the data in an attempt to describe the variability of the subpixel structural parameters; this was done in order to assess VI robustness to changes in structural “levels”, as well as placement of trees/canopies within the instrument’s instantaneous field-of-view (IFOV). Our ultimate goal is not only to better understand how such subpixel variability influence imaging spectroscopy outputs, but also to better estimate vegetation structural parameters using spectra. We constructed regression models for LAI (R2 = 0.92) and canopy cover (R2 = 0.97) with narrow-band VIs via this simulation approach. Our models ultimately are intended to improve the HyspIRI mission’s ability to monitor global vegetation structure.

Van Aardt, Jan↗

NASA NTRS1974

New theoretical models and ratio imaging techniques associated with the NASA earth resources spectral information system

Four independent investigations are reported; in general these are concerned with improving and utilizing the correlation between the physical properties of natural materials as evidenced in laboratory spectra and spectral data collected by multispectral scanners. In one investigation, two theoretical models were devised that permit the calculation of spectral emittance spectra for rock and mineral surfaces of various particle sizes. The simpler of the two models can be used to qualitatively predict the effect of texture on the spectral emittance of rocks and minerals; it is also potentially useful as an aid in predicting the identification of natural atmospheric aerosol constituents. The second investigation determined, via an infrared ratio imaging technique, the best pair of infrared filters for silicate rock-type discrimination. In a third investigation, laboratory spectra of natural materials were compressed into 11-digit ratio codes for use in feature selection, in searches for false alarm candidates, and eventually for use as training sets in completely automatic data processors. In the fourth investigation, general outlines of a ratio preprocessor and an automatic recognition map processor are developed for on-board data processing in the space shuttle era.

Vincent, R. K.↗

DOE OSTI2014

Low-Cost Spectral Sensor Development Description

Solar spectral data for all parts of the US is limited due in part to the high cost of commercial spectrometers. Solar spectral information is necessary for accurate photovoltaic (PV) performance forecasting, especially for large utility-scale PV installations. A low-cost solar spectral sensor would address the obstacles and needs. In this report, a novel low-cost, discrete-band sensor device, comprised of five narrow-band sensors, is described. The hardware is comprised of commercial-off-the-shelf components to keep the cost low. Data processing algorithms were developed and are being refined for robustness. PV module short-circuit current ($I_{sc}$) prediction methods were developed based on interaction-terms regression methodology and spectrum reconstruction methodology for computing $I_{sc}$. The results suggest the computed spectrum using the reconstruction method agreed well with the measured spectrum from the wide-band spectrometer (RMS error of 38.2 W/m 2 -nm). Further analysis of computed $I_{sc}$ found a close correspondence of 0.05 A RMS error. The goal is for ubiquitous adoption of the low-cost spectral sensor in solar PV and other applications such as weather forecasting.

Armijo, Kenneth Miguel↗

NASA NTRS1976

Evaluation of surface water resources from machine-processing of ERTS multispectral data

The surface water resources of a large metropolitan area, Marion County (Indianapolis), Indiana, are studied in order to assess the potential value of ERTS spectral analysis to water resources problems. The results of the research indicate that all surface water bodies over 0.5 ha were identified accurately from ERTS multispectral analysis. Five distinct classes of water were identified and correlated with parameters which included: degree of water siltiness; depth of water; presence of macro and micro biotic forms in the water; and presence of various chemical concentrations in the water. The machine processing of ERTS spectral data used alone or in conjunction with conventional sources of hydrological information can lead to the monitoring of area of surface water bodies; estimated volume of selected surface water bodies; differences in degree of silt and clay suspended in water and degree of water eutrophication related to chemical concentrations.

Mausel, P. W.↗

NASA NTRS1976

Uhuru observations of 4U 1608-52 - The 'steady' X-ray source associated with the X-ray burst source in Norma

Data are presented for the X-ray source 4U 1608-52, summarizing its light curve, location, and spectral parameters. Evidence is presented showing that this source is the 'steady' X-ray counterpart of the X-ray burst source in Norma. The spectrum of the 'steady' source is compared with the spectrum observed during two bursts, and it is noted that there is substantially more low-energy absorption during the bursts. The 'steady' source spectral data are used to examine the optical data, and it is concluded that if the X-ray spectrum is thermal, then a globular-cluster counterpart probably would have been detected (whereas none has been). Further X-ray and optical observations are suggested for this source, since an optical identification may be central in determining whether all X-ray bursts have a common origin and if this origin requires a globular-cluster environment.

Tananbaum, H.↗

NASA NTRS1982

Extension of laboratory-measured soil spectra to field conditions

Spectral responses of two glaciated soils, Chalmers silty clay loam and Fincastle silt loam, formed under prairie grass and forest vegetation, respectively, were measured in the laboratory under controlled moisture equilibria using an Exotech Model 20C spectroradiometer to obtain spectral data in the laboratory under artificial illumination. The same spectroradiometer was used outdoors under solar illumination to obtain spectral response from dry and moistened field plots with and without corn residue cover, representing the two different soils. Results indicate that laboratory-measured spectra of moist soil are directly proportional to the spectral response of that same field-measured moist bare soil over the 0.52 micrometer to 1.75 micrometer wavelength range. The magnitudes of difference in spectral response between identically treated Chalmers and Fincastle soils are greatest in the 0.6 micrometers to 0.8 micrometer transition region between the visible and near infrared, regardless of field condition or laboratory preparation studied.

Stoner, E. R.↗

NASA NTRS1988

A high speed data acquisition and analysis system for transonic velocity, density, and total temperature fluctuations

The high speed Dynamic Data Acquisition System (DDAS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAS replaces both a recording mechanism and a separate data processing system. The data acquisition and data reduction process has been combined within DDAS. DDAS receives input from hot wires and anemometers, amplifies and filters the signals with computer controlled modules, and converts the analog signals to digital with real-time simultaneous digitization followed by digital recording on disk or tape. Automatic acquisition (either from a computer link to an existing wind tunnel acquisition system, or from data acquisition facilities within DDAS) collects necessary calibration and environment data. The generation of hot wire sensitivities is done in DDAS, as is the application of sensitivities to the hot wire data to generate turbulence quantities. The presentation of the raw and processed data, in terms of root mean square values of velocity, density and temperature, and the processing of the spectral data is accomplished on demand in near-real-time- with DDAS. A comprehensive description of the interface to the DDAS and of the internal mechanisms will be prosented. A summary of operations relevant to the use of the DDAS will be provided.

Clukey, Steven J.↗

NASA NTRS1991

Spatial transportability of geobotanical spectral signatures associated with soil geochemical anomalies

Consideration is given to a specific problem of spectral signature extension through examination and comparison of multitemporal spectral data signatures developed over a generalized, along-strike geochemical trend located within eastern deciduous hardwood forest. The spectral geobotanical signatures associated with soil Pb, Cu, and Zn anomalies were examined in south-central Virginia. Spectral discrimination between a training pair of anomalous and control sites within the Mineral district was 100 percent successful. It is concluded that spectral geobotanical signatures serve to identify regions of lowered biomass, lowered vigor, and/or differing species composition.

Bell, R.↗

NASA NTRS1993

Infrared spectroscopic measurements relevant to atmospheric remote sensing

SF6 is a synthetic chemical which is used in many industrial applications and as a meteorological tracer. This paper describes determinations of spectral absorption coefficients k-nu of SF6 measured in the central Q-branches of the nu(3)-fundamental at 947/cm at various temperature-pressure combinations representing tangent heights in solar-occultation experiments or layers in the atmosphere. Spectral data were also obtained for C2H4 and NH3 fundamental bands. Measurements were made with the Doppler-limited spectral resolution of a tunable diode laser spectrometer with a cryogenically cooled absorption cell, described by Varanasi and Chudamani (1992).

Varanasi, Prasad↗

NASA NTRS2003

NASA's Earth Observatory and Visible Earth: Imagery and Science on the Internet

The purpose of NASA s Earth Observatory and Visible Earth Web sites is to provide freely-accessible locations on the Internet where the public can obtain new satellite imagery (at resolutions up to a given sensor's maximum) and scientific information about our home planet. Climatic and environmental change are the sites main foci. As such, they both contain ample data visualizations and time-series animations that demonstrate geophysical parameters of particular scientific interest, with emphasis on how and why they vary over time. An Image Composite Editor (ICE) tool will be added to the Earth Observatory in October 2002 that will allow visitors to conduct basic analyses of available image data. For example, users may produce scatter plots to correlate images; or they may probe images to find the precise unit values per pixel of a given data product; or they may build their own true-color and false-color images using multi- spectral data. In particular, the sites are designed to be useful to the science community, public media, educators, and students.

King, Michael D.↗

DOE OSTI2023

Design and Operation of a Multi-Bed Catalytic Micro-Reactor for the Study of Co-Processing of Bio-Oils with VGO

An industry wide shift from fossil-based fuel to renewable fuel sources including biomass, municipal waste, and plastics will require new process monitoring methods to minimize transitional risks including off specification product formation and catalyst deactivation. This project aims to provide a machine learning based process monitoring tool composed of online, slipstream mass spectra for use in biomass refineries and co-processing in existing refineries allowing operators to monitor product qualities and adjust process conditions accordingly. In order to maximize the robustness of the tool, large volumes of data must be collected to fine tune model parameters which consists of both micro and pilot scale mass spectral data. Micro-scale data is collected with a multi-tube micro-reactor housing up to six catalysts in horizontal beds, coupled with a molecular beam mass spectrometer. A pyrolizer equipped with an auto-sampler streamlines the micro-scale data collection process. This type of pyrolizer/micro-reactor configuration does not exist on the market, and therefore had to be created for the purposes of this project. The design and commissioning of this reactor will be presented in detail. This reactor set-up is highly flexible and increases throughput of analysis. For catalyst testing, each bed can be individually selected simply by turning valves. For catalyst reduction and regeneration, simultaneous flow through all six beds is used. The reproducibility of the system was first assessed with whole biomass pyrolysis along with pyrolysis of calibration standards. Initial work on this system evaluated two FCC catalysts, equilibrium catalyst (E-cat), and a proprietary catalyst from Johnson Matthey specifically design for co-processing of bio-oil with vacuum gas oil (VGO). This work used model compounds and VGO which illuminated differences in products produced by the catalysts.

biomass↗

DOE OSTI2023

SIF and Vegetation Indices in the US Midwestern Agroecosystems, 2016-2021, Carbon Monitoring System (CMS)

This dataset contains half-hourly ground solar-induced chlorophyll fluorescence (SIF) and vegetation indices including NDVI, EVI, Red edge chlorophyll index, green chlorophyll index, and photochemical reflectance index at seven crop sites in Nebraska and Illinois for the period 2016-2021. Four sites were located at Eddy Covariance (EC) tower sites (sites US-Ne2, US-Ne3, US-UiB, and US-UiC), and three sites were located on private farms (sites Reifsteck, Rund, and Reinhart). The sites were either miscanthus, corn-soybean rotation or corn-corn-soybean rotation. The spectral data for SIF retrieval and hyperspectral reflectance for vegetation index calculation were collected by the FluoSpec2 system, installed near planting, and uninstalled after harvest to collect whole growing-season data. Raw nadir SIF at 760 nm from different algorithms (sFLD, 3FLD, iFLD, SFM) are included. SFM_nonlinear and SFM_linear represent the Spectral fitting method (SFM) with the assumption that fluorescence and reflectance change with wavelength non-linearly and linearly, respectively. Additional data include two SIF correction factors including calibration coefficient adjustment factor (f_cal_corr_QEPRO) and upscaling nadir SIF to eddy covariance footprint factor (ratio_EC footprint, SIF pixel), and measured FPAR from quantum sensors and Rededge NDVI calculated FPAR. The data are provided in comma-separated values (CSV) format.

Ameriflux↗

NASA NTRS2003

Spectroscopic Determination of the Physical Conditions in Hot Optically Thin Sources

The Astrophysics Plasma Emission Code and Database (APEC/APED), developed in part under this grant, have been upgraded to Version 1.3.0 and are now beginning to find widespread applications to X-ray spectral data from Chandra and XMM-Newton. These models represent the best theoretical data currently available and are reasonably complete below about 30 A. We are making significant progress in improving the spectral models between 30 and 90 A, by the addition of HULLAC calculations and NIST wavelengths for L-shell ions of Ne, Mg, Si, S, Ar, and Ca. While the output models are now public, the code itself is not ready for public release. We have made significant progress toward this goal through programming improvements, including optimized error codes, a major (elusive) bug fix, and additions to our testing protocols. Secondarily, we are beginning to investigate limited uses of APEC for X-ray photoionized plasma, as for opacity modeling. Stellar coronae are being used to benchmark the atomic data in APED as part of the Emission Line Project. The models appear to be in good agreement with the observations for most of the strong lines; however, we have identified significant discrepancies in the 3s/3d line ratios not only for Fe XVII, but also for Fe XVIII and XIX. The careful analysis of these high quality X-ray spectra has also shown that there are serious problems with some of the analysis techniques in widespread use. There are several manifestations of the problem, but the main problem is that line-to-continuum ratios may be seriously mismeasured. We continue to collaborate widely with atomic physicists in order to find the best atomic data, and to solicit calculations and measurements that are needed.

Brickhouse, Nancy↗

NASA NTRS1998

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Kimes, Daniel S.↗

NASA NTRS1986

AIS spectra of desert shrub canopies

Airborne Imaging Spectrometer (AIS) data were collected 30 August 1985 from a desert shrub community in central Oregon. Spectra from artificial targets placed on the test site and from bare soil, big sagebrush (Artemesia tridentata wyomingensis), silver sagebrush (Artemesia cana bolander), and exposed volcanic rocks were studied. Spectral data from grating position 3 (tree mode) were selected from 25 ground positions for analysis by Principal Factor Analysis (PFA). In this grating position, as many as six factors were identified as significant in contributing to spectral structure. Channels 74 through 84 (tree mode) best characterized between-class differences. Other channels were identified as nondiscriminating and as associated with such errors as excessive atmospheric absorption and grating positin changes. The test site was relatively simple with the two species (A. tridentata and A. cana) representing nearly 95% of biomass and with only two mineral backgrounds, a montmorillonitic soil and volcanic rocks. If, as in this study, six factors of spectral structure can be extracted from a single grating position from data acquired over a simple vegetation community, then AIS data must be considered rich in information-gathering potential.

Murray, R.↗