Search NASA⌕ Search

SEARCH · Search NASA

Results for “reflection data”

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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Radiometric calibration and monitoring of NOAA AVHRR visible data

Results and corrections to calibration for the NOAA-7, -8, -9, -10, and -11 AVHRR Channel 1 data, covering the period from July 1983 through December 1989, are presented. Results from the NOAA-7 and NOAA-9 analysis are used as examples to illustrate key points and present detailed results. In the AVHRR monitor procedure, the spatial variability index is calculated first to classify the data as CLEAR or CLOUD. This classification is then used to sort the data to produce three 1D radiance histograms for different surface types. The surface reflectances are retrieved from the radiances, and a set of reflectance filters are applied to sort the data into global surface reflectance maps. An examination of the NOAA-7 results shows that the NOAA-7 radiometer sensitivity actually decreased at a rate of about 0.5-1.0 percent per year. Trends inferred from the point measurements representing independent calibrations at different times, using models, known sites, and coincident aircraft measurements, agree well with the satellite methods.

Brest, Christopher L.↗
DOE OSTI2024

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗
NASA NTRS1982

Optical constants in the extreme ultraviolet and soft X-ray region

The nature of optical constants and their measurement by reflection or absorption techniques in the extreme ultraviolet and soft X-ray spectral region from 30 to 3000 eV is discussed with emphasis on mirror design. Sources of optical constant data are mentioned and reflectance measurements for SiC and Kanigen between 40 and 200 eV are reported.

Rife, J. C.↗
DOE OSTI2021

Leaf spectral reflectance and transmittance, San Lorenzo, Panama, 2020

This data package contains full-range (350 – 2500 nm) leaf reflectance and transmittance spectra of leaves collected at the San Lorenzo forest canopy crane site in Panama (PA-SLZ) from January to March 2020. Around 1000 leaves were measured from 50 species and various leaf phenological stages. Leaves were sampled from both the top of the canopy and multiple heights within the canopy from 10 vertical profiles and for six core species, from the top of the canopy. This data package includes processed leaf spectra (*.csv), and raw data from the spectroradiometer (compressed as .zip). Metadata files include data descriptions (_dd.csv) for tabular data and sample information and a description of the field campaign protocol (PA-SLZ_2020_Protocol.pdf). In addition to the leaf spectral measurements included here, these samples were also used for measurement of leaf gas exchange, carbon and nitrogen content and leaf mass per unit leaf area (LMA) contained in related data packages.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Use of In Situ and Airborne Multiangle Data to Assess MODIS and Landsat-Based Estimates of Directional Reflectance and Albedo

The quantification of uncertainty in satellite-derived global surface albedo products is a critical aspect in producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A challenge in validating albedo measurements acquired from space is the ability to overcome the spatial scaling errors that can produce disagreements between satellite and field-measured values. Here, we present the results from an accuracy assessment of MODIS and Landsat-TM albedo retrievals, based on collocated comparisons with tower and airborne Cloud Absorption Radiometer (CAR) measurements collected during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC). The initial focus was on evaluating intersensor consistency through comparisons of intrinsic bidirectional reflectance estimates. Local and regional assessments were then performed to obtain estimates of the resulting scaling uncertainties, and to establish the accuracy of albedo reconstructions during extended periods of precipitation. In general, the satellite derived estimates met the accuracy requirements established for the high-quality MODIS operational albedos at 500 m (the greater of 0.02 units or +/-10% of surface measured values). However, results reveal a high degree of variability in the root-mean-square error (RMSE) and bias of MODIS visible (0.3-0.7 μm) and Landsat-TM shortwave (0.3-5.0 μm) albedos; where, in some cases, retrieval uncertainties were found to be in excess of 15%. Results suggest that an overall improvement in MODIS shortwave albedo retrieval accuracy of 7.8%, based on comparisons between MODIS and CAR albedos, resulted from the removal of sub-grid scale mismatch errors when directly scaling-up the tower measurements to the MODIS satellite footprint.

biosphere↗
DOE OSTI2019

NGEE Arctic Leaf Spectral Reflectance and Transmittance, Barrow, Alaska, 2014-2016

Data were collected to characterize the leaf-level optical properties and albedo of dominant Arctic tundra species in the Barrow, AK area and to enable trait scaling. Measurements of full-spectrum (i.e. 350-2500nm) leaf spectral reflectance of Arctic plant species. Data were collected in Barrow, Alaska during the 2014-2016 period. This dataset contains 5 zipped folders, 4 csv, 4 xlsx, 1 txt, and 1 pdf files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Measuring surface fluxes in CAPE

Two stations (site 1612 and site 2008) were operated by the University of Georgia group from 6 July 1991 to 18 August 1991. The following data were collected continuously: surface energy fluxes (i.e., net radiation, soil heat fluxes, sensible heat flux and latent heat flux), air temperature, vapor pressure, soil temperature (at 1 cm depth), and precipitation. Canopy reflectance and light interception data were taken three times at each site between 6 July and 18 August. Soil moisture content was measured twice at each site.

Kanemasu, E. T.↗
NASA NTRS1989

Infrared spectroscopy (2.3-20 microns) for the geological interpretation of remotely-sensed multispectral thermal infrared data

The spectral radiance and spectral reflectance of natural weathered surfaces of common sedimentary and igneous rocks is determined from in situ and in the laboratory measurements. In situ spectral radiance measurements (5-14 microns) were made with a portable spectral radiometer and were used to derive the spectral emissivity of the rocks. The spectral reflectance measurements (2.3-20 microns) were made in a laboratory with a Fourier transform IR spectrometer with a diffuse reflectance accessory. Good agreement is found between the two techniques. The field portable spectrometer has a larger field of view and the in situ data provide more accurate measurements of the intensity of spectral features related to temperature and atmospheric effects.

Bartholomew, Mary Jane↗
NASA NTRS1984

Mapping and geological analysis of Mercury radar data

Although many radar profiles and images of the area within 20 deg of Mercury's equator had been obtained from 1971 to 1981, at both Goldstone and Arecibo radar facilities, surprisingly little geological analysis had been done with these data until recently. Topographic profiles and radar roughness reflectivity images which can be derived from these data will be crucial in completing the geological mapping of Mercury now underway at the U.S. Geological Survey. Processing of available radar data must be completed to establish any systematic relationship between radar reflectivities and roughness, density, dielectric constant, and other related geological parameters. Specific tasks accomplished for these purposes include the following. Documentation was located and searched to establish the type and quantity of Goldstone 12.5 cm radar observations which were available for Mercury. Data has been collected during approximately 50 observation periods from 1971 to 1981. About half of the data, collected during 1972 and 1973, have been processed, but without adequate documentation. A standardized, well-documented procedure for processing and analysis for all Goldstone Earth-based observations of Mercury was established.

Clark, P. E.↗
NASA NTRS1986

Maximum normalized acceleration as a flying qualities parameter

In 1984, Maximum Normalized Rate (MNR) was presented as a Flying Qualities parameter. Subsequent analysis of data from ground based simulation and flight test revealed the utility of a companion parameter, Maximum Normalized Acceleration (MNA). MNR and MNA profiles reveal the presence of both continuous and pulsed compensation strategies during discrete attitude tracking. In addition, MNR appears to be a suitable metric for pilot opinion in the LATHOS data base, while the MNR/MNA relationship is sensitive to pilot-induced-oscillation (PIO) and roll ratcheting problems. As part of an investigation of this problem, Northrop has developed an analysis technique known as the Step Target Method. The Step Target method is essentially a one degree-of-freedom simulation, where an attitude command in the form of a step function is presented to a closed-loop pilot/aircraft model. The two parameters MNR and MNA were shown to be useful in Flying Qualities analysis. MNR was shown to correlate with Pilot Opinion Rating in the LATHOS data base, while MNA reflects PIO and roll ratcheting. Profiles of MNR versus MNA reveal the presence of pulsed compensation strategies in both ground based and in-flight simulation. Furthermore, comparison of continuous and discrete attitude tracking simulation data reveals that these two tracking tasks exhibit independent sensitivities to aircraft characteristics.

Warner, J. S.↗
NASA NTRSDate not supplied

MODIS Reflective Solar Band Calibration Improvements using Pseudo-Invariant Desert Targets

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a two-sided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudo-invariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

MODIS↗
NASA NTRSDate not supplied

Updates in Developing a Prototype Science Pipeline and Full-Volume, Global Hyperspectral Synthetic Data Sets for NASA’s Earth System Observatory’s Upcoming Surface, Biology and Geology Mission

The Surface Biology and Geology (SBG) mission recently passed mission confirmation review and has entered phase A – design and development. SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~2.5 TB/day and generate products at ~40 TB/day. Given that the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing, disseminating, and exploiting the SBG data present new challenges. To meet these challenges, we have developed a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight (see poster GC42D-0730). Our science pipeline is based on the science processing technology developed for NASA’s Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or a supercomputer. Ziggy is compliant with NASA Procedural Requirement (NPR) 7150.2C, is at a technical readiness level (TRL) of 7 and has been released to github.com/nasa/ziggy. We integrated Ziggy with EO-1/Hyperion workflows to build a prototype pipeline and ingested the 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We fully implemented the first stage and processed the entire 55 TB Hyperion data set from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We are currently evaluating the ISOFIT atmospheric correction module to convert the L1R data to surface reflectance (Level 2) before reprocessing the full data set to L2. Crosschecks are being performed with RadCalNet as well as with coincident observations by AVIRIS. We are also investigating modern methods for georectifying the Hyperion scenes. Finally, we describe an analysis of the cost to conduct forward processing and reprocessing campaigns for SBG on HECC with dedicated compute and storage resources using the resurrected Hyperion pipeline as a proxy for full-volume SBG data. The analysis demonstrates that SBG L0 data can be processed to L2 on HECC with full reprocessing campaigns every two years for ~$2.6M over a 7-year lifespan. Moreover, 69% of the system capacity would be available for other activities, possibly enabling future open-source science activities, including algorithm development, L3+ processing, .etc.

ESD↗
DOE OSTI2024

Hybrid Modeling of Three-Phase Grid-Supporting Inverters for Dynamic Studies

Grid technologies connected by power electronic converter (PEC) interfaces continually implement grid support functions mandated by grid codes and standards. The transition to converter-based generation demands precise PEC models to assess system dynamics, which have been previously overlooked in conventional power systems. This study proposes a hybrid method for analyzing grid-connected three-phase PEC dynamics with the IEEE standard 1547-2018 Volt-VAr mode that combines physics and data-driven techniques. The physics model reflects the PEC’s internal behavior, whereas the data-driven modeling technique evaluates the grid-supporting capabilities of the smart PEC. The system identification approach is used to generate dynamic PEC models based on changing grid voltage and measured current injected into the grid by the PEC. In the Volt-VAr support mode, a detailed topological model including switches is utilized to compare the goodness-of-fit of the extracted hybrid dynamic model. The results demonstrate that the hybrid PEC model in the Volt-VAr mode accurately matches the dynamics with the topological model.

Subedi, Sunil↗
NASA NTRS1993

Results on the evolution of galaxies and their environment from the Ultraviolet Imaging Telescope on Astro-1

The Ultraviolet Imaging Telescope (UIT), part of the Astro-1 Spacelab Mission, was used to obtain high-resolution surface brightness distribution data in six ultraviolet wavelength bands for the bright reflection nebula NGC 7023. The corresponding data from the visible leads us to conclude that the scattering in the near and far ultraviolet in this nebula is more strongly forward directed than it is in the visible. The UIT also obtained near-UV and far-UV images of the giant OB association NGC 206 in M32. Photometry was obtained for thirty massive stars. We analyzed UV imagery of two Sb bulges and two E galaxies obtained with UIT. For NGC 1275, the measured UV colors indicate a mass function which extends to eight solar masses but no higher. Other aspects of this investigation are discussed.

Stecher, Theodore P.↗
DOE OSTI2022

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗