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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Guatemala and Panama Urban Development: Evaluating the Effects of Urban Expansion on Social and Environmental Vulnerability in Guatemala and Panama

Central America is experiencing rapid and unregulated urban expansion, which is contributing to an increase in socioeconomic and environmental risks including inequities in infrastructure and housing accessibility, biodiversity loss, vulnerability to natural disasters, and negative health outcomes. NASA DEVELOP, in partnership with NASA SERVIR, Sistema de la Integración Centroamericana (SICA), Secretariat of Central American Social Integration (SISCA), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), and Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPRENEDAC), examined changes in urban extent, characterized roofing material type, and analyzed vulnerability within urban areas in two Central American cities, Guatemala City and Panama City. The team used land cover imagery from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 OLI-2 to map urban extent, and surface reflectance data from Maxar Worldview to identify roofing material types. Socioeconomic and environmental data were used to assess vulnerability. Results depict how the two cities have expanded from 2000 to present day and highlight areas of greatest vulnerability within each urban area. The supervised classification of roofing materials performed well but could be improved with a few enhancements. Findings can help partner organizations improve monitoring of urbanization and inform their planning and decision-making while prioritizing disaster prevention, public health, and environmental integrity. Additionally, these case studies can be used to inform future, similar work elsewhere in Central America to aid in understanding urbanization and its associated challenges.

Jennifer Ruiz↗
NASA NTRSDate not supplied

Mineralogical Evidence for Environmental Change in the Clay-Sulfate Transition at Gale Crater, Mars

A primary reason for selecting Gale crater as the Mars Science Laboratory (MSL) Curiosity rover landing site was a clear mineralogical transition from Fe/Mg smectite in older strata to hydrated Mg sulfate salts in younger strata observed in orbital visible/shortwave-infrared reflectance data. This transition has been observed in other early-Hesperian terrains on Mars and has been hypothesized to signal a planet-wide change in climate from relatively warm and wet to cold and dry. Curiosity studied the sedimentology and geochemical and mineralogical composition of rocks in this “clay-sulfate transition” region from sols 3052 to 3572 (i.e., March 2021 to August 2022), with arrival at the sulfate unit on sol 3574. Here, we report on the mineralogical measurements made by the CheMin X-ray diffractometer of the six drill targets in the clay-sulfate transition and the first drill target in the sulfate unit. We use compositional data and sedimentological observations to interpret depositional and diagenetic environments and present hypotheses to explain the transition from clay minerals to hydrated Mg sulfates.

E. B. Rampe↗
DOE OSTI2019

Ultrasound waveform tomography with wave-energy-based preconditioning

Synthetic-aperture ultrasound tomography systems and methods using scanning arrays and algorithms configured to simultaneously acquire ultrasound transmission and reflection data, and process the data using ultrasound waveform tomography with a wave-energy-based preconditioning method for improved ultrasound tomography imaging.

Huang, Lianjie↗
DOE OSTI2019

Vis-NIR equipped soil penetrometer

Soil penetrometers capable of measuring soil reflectance along the direction of insertion of the penetrometer are provided. The penetrometer can house an array of sensors, such as, for example, a Vis-NIR reflectance sensor, a load cell, a displacement sensor, and a moisture sensor. The reflectance data collected using the penetrometer can allow the interpretation and quantification of soil constituents and contaminants at high vertical resolution, such as 3 cm or more.

Morgan, Cristine↗
DOE OSTI2021

Bi-static and mono-static synthetic aperture radar (SAR) imaging using a short-pulse laser

SAR imaging may be performed using a short-pulse laser to generate range-resolved reflection data. A short-pulse laser may be advantageous over other techniques to acquire the range-resolved data, especially in cases with very distant targets or other cases with low signal-to-noise ratio information, because a short-pulse laser can determine the range to individual reflectors with a single photon return and is more adaptable to a photon-starved inversion algorithm. This technique can be used with both mono-static and bi-static SAR configurations.

Carlsten, Bruce E.↗
DOE OSTI2022

Ultrasound waveform tomography with spatial and edge regularization

Synthetic-aperture ultrasound tomography systems and methods using scanning arrays and algorithms configured to simultaneously acquire ultrasound transmission and reflection data, and process the data for improved ultrasound tomography imaging, wherein the tomography imaging comprises total-variation regularization, or a modified total variation regularization, particularly with edge-guided or spatially variant regularization.

Huang, Lianjie↗
DOE OSTI2023

X-Ray Absorption Spectroscopy (XAS): Surface Structural Determination of Alloy Nanoparticles

In catalysis since reactions occur on the surface of nanoparticles (NP), it is essential to determine the composition of this structure, rather than that of the nanoparticles, since the two may be, and often are, different. Conventional techniques including X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD) are powerful techniques, but these data reflect the average composition of the entire particle. In this chapter, we introduce the method of EXAFS analysis, which isolates the surface atoms of nanoparticles based on its sensitivity to chemical reactions, specifically surface oxidation. As shown in our case studies, if the surface of a Pt-based nanoparticle is contacted by air at room temperature, the surface will selectively oxidize, resulting in the loss of Pt-Pt and Pt-M bonds to the formation of Pt-O bonds. The difference between the completely reduced and surface-oxidized nanoparticle allows for the isolation of signal from the catalytic surface. Although these examples highlight Pt alloys, similar analysis is also possible for other group 8 and IB bimetallic catalysts.

Zhang, Guanghui↗
NASA NTRS2018

Intercomparison of Field Methods for Acquiring Ground Reflectance at Railroad Valley Playa for Spectral Calibration of Satellite Data

Ground reflectance was acquired at the Railroad Valley Playa calibration site in Nevada USA using different methods of collection. The data was collected near the time and date of Landsat 8 OLI and Sentinel-2 satellite overpasses so an inter-comparison could be made with the reflectance products to determine which method was more suitable for vicarious calibration. The field spectrometers and reference panels were characterized before the field campaign. A continuous acquisition method was compared to stop and measure collections. Both acquisition methods were collected along an 80 m east-west transect as well as for a series of north-south transects over an 80 x 320 m area, with the stop and measure method being performed at random sampling locations. The measurements were performed using two field spectrometers by three teams of two people to compare the repeatability. The aim of the field campaign was to determine the variability due to the operator and the method of collection.

Lau, Ian C.↗
NASA NTRS2018

Intercomparison of Field Methods for Acquiring Ground Reflectance at Railroad Valley Playa for Spectral Calibration of Satellite Data

Ground reflectance was acquired at the Railroad Valley Playa calibration site in Nevada USA using different methods of collection. The data was collected near the time and date of Landsat 8 OLI and Sentinel-2 satellite overpasses so an inter-comparison could be made with the reflectance products to determine which method was more suitable for vicarious calibration. The field spectrometers and reference panels were characterized before the field campaign. A continuous acquisition method was compared to stop and measure collections. Both acquisition methods were collected along an 80 m east-west transect as well as for a series of north-south transects over an 80 x 320 m area, with the stop and measure method being performed at random sampling locations. The measurements were performed using two field spectrometers by three teams of two people to compare the repeatability. The aim of the field campaign was to determine the variability due to the operator and the method of collection.

Lau, Ian C.↗
NASA NTRS1985

Multispectral, thermal infrared satellite data for geologic applications

The value of multispectral thermal infrared satellite data for geologic mapping was assessed, applying the principal component and canonical analysis techniques to the images of the central part of the Arabian Peninsula (a 200 x 300 km area). Low resolution thermal infrared (TIR) data from the Nimbus 5 Surface Composition Mapping Radiometer (SCMR) and the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) were used. Color images included an 8.8 micrometer (SCMR) and 3.7 and 10.8 micrometer (AVHRR-night) data, ratioed AVHRR day/night TIR data, ratioed AVHRR reflected radiation data, and transformed 8- and 10-band TIR plus reflected radiation data. The results clearly demonstrated the potential geologic value of multispectral TIR data. Igneous and metamorphic units could be separated as a class (although not from each other except for young calc-alkaline granites). Some previously unmapped extensions of mapped faults below thick sedimentary units could be delineated. No single enhancement technique displayed all the potential information, implying that they should be used together.

Blodget, H. W.↗
NASA NTRS2019

Evaluation of the Surface Reflectance Long-Term Data Record from AVHRR over Multiple Land Surface Types

In this work, we evaluate the performance of the AVHRR surface reflectance LTDR V4 using Landsat-5 Thematic Mapper (TM5) Collection-1 surface reflectance data over 440 globally distributed sites, which give a representative set of land surface types and climate conditions. Surface reflectance anisotropy effects were normalized using the VJB method, and spectral response differences were accounted for with spectral band adjustment factors (SBAFs) computed as a function of the Normalized Difference Vegetation Index (NDVI) from a set of over 100,000 hyperspectral spectra from Hyperion. The performance of the AVHRR record is reported in terms of the accuracy, precision, and uncertainty, as compared to the specifications of the reference product. Results show that the AVHRR record performance is close to the 0.071ρ+0.0071 specification defined in the original TM5 product evaluation.

LTDR↗
NASA NTRS1992

Learning class descriptions from a data base of spectral reflectance with multiple view angles

A learning program has been developed which combines 'learning by example' with the generate-and-test paradigm to furnish a robust learning environment capable of handling error-prone data. The problem is shown to be capable of learning class descriptions from positive and negative training examples of spectral and directional reflectance data taken from soil and vegetation. The program, which used AI techniques to automate very tedious processes, found the sequence of relationships that contained the most important information which could distinguish the classes.

Kimes, Daniel S.↗
NASA NTRS1990

Determination of surface reflectance and estimates of atmospheric optical depth and single scattering albedo from Landsat Thematic Mapper data

Groound-reflectance data on selected targets for calbiration of a Landsat TM image of Wind River Basin, Wyoming, acquired November 21, 1982 were examined. Field-derived calibration relationships together with Landsat radiometric calibration data are used to convert scanner DN values to spectral radiance for the TM bands and (together with a simplified homogeneous atmospheric model) to obtain estimates of single-scattering albedo and optical depth consistent with the derived path radiance and transmission properties of the atmosphere. These estimates are used to study the problems of evaluation of the magnitude of adjacency effects for reference targets, the assumption of isotropic properties, and the aggregate magnitude of multiple reflections between sky and ground. The radiance calibration equations are also used together with preflight measured signal/noise properties of the TM-4 system to estimate the noise-equivalent reflectance recoverable in practice from the system.

Conel, James E.↗
NASA NTRS1984

Study of spectral/radiometric characteristics of the thematic mapper for land use applications

The previous characterization of scan-related low-frequency noise was confirmed and extended through analysis of reflective-band data from another nighttime acquisition. Amplitude and phase relationships of the level shifts were determined for each detector in each of free full frames. Analysis of scan-direction-related signal droop effects in nighttime data from the reflective bands was begun with encouraging initial observations. Also, an effort to characterize high-frequency noise in the reflective bands through Fourier analysis of nighttime data was initiated. Recommendations are made relative to the choice of radiometric calibration constants in the thematic mapper image processing system for the routine processing of TM data. Non-linear (piece-wise linear) calibration curves are recommended.

Malila, W. A.↗
DOE OSTI2024

UAS remote sensing (AltaX platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance (Level 0 data), Seward Peninsula, Alaska, 2023

Airborne remote sensing data collected using Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) AltaX platform on the Seward Peninsula, Alaska, USA. This package includes raw (L0) data from 11 flights flown over the NGEE-Arctic Kougarok mile marker 64 (MM64) and Teller MM 27 sites in July, 2023. The AltaX is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350 – 1000 nm. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), binary (*.dat, *.ulg), tabular (*.csv), geospatial (*.kml. *kmz), image (*.jpg, *.png, *.tif) and pdf formats. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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↗
DOE OSTI2024

UAS remote sensing (AltaX platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance (Level 0 data), Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) AltaX platform on the Seward Peninsula, Alaska, USA. This package includes raw (L0) data from 10 flights flown over the NGEE-Arctic Kougarok mile marker 64 (MM64) and Teller MM 27 sites in July, 2022. The AltaX is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350 – 1000 nm. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), binary (*.dat, *.ulg), tabular (*.csv), geospatial (*.kml. *kmz), image (*.jpg, *.png, *.tif) and pdf formats. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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 NTRS2019

Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data: Incorporating Surface Reflectance, Through Phenological Fitting, into Regression Yield Models

A combination of Landsat 8 and Sentinel-2 offers a high frequency of observations (3–5 days) at moderate spatial resolution (10–30 m), which is essential for crop yield studies. Existing methods traditionally apply vegetation indices (VIs) that incorporate surface reflectances (SRs) in two or more spectral bands into a single variable, and rarely address the incorporation of SRs into empirical regression models of crop yield. In this work, we address these issues by normalizing satellite data (both VIs and SRs) derived from NASA’s Harmonized Landsat Sentinel-2 (HLS) product, through a phenological fitting. We apply a quadratic function to fit VIs or SRs against accumulated growing degree days (AGDDs), which affects the rate of crop development. The derived phenological metrics for VIs and SRs, namely peak, area under curve (AUC), and fitting coefficients from a quadratic function, were used to build empirical regression winter wheat models at a regional scale in Ukraine for three years, 2016–2018. The best results were achieved for the model with near infrared (NIR) and red spectral bands and derived AUC, constant, linear, and quadratic coefficients of the quadratic model. The best model yielded a root mean square error (RMSE) of 0.201 t/ha (5.4%) and coefficient of determination R2 = 0.73 on cross-validation.

phenological fitting↗