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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED-2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2021

Carbon–Nutrient Economy of the Rhizosphere: Improving Biogeochemical Prediction and Scaling Feedbacks from Ecosystem to Regional Scales

Our project has advanced the science of plant-soil-microbial dynamics across these areas: i) nutrient cycling and plant uptake; ii) root exudation and priming; and, iii) mycorrhizal dynamics. Our project has accomplished 5 main developments: 1) Incorporation of phosphorus cycling into the Fixation & Uptake of Nutrients (FUN 3.0) model. 2) Coupling of FUN 3.0 into the E3SM Land Model (ELM). 3) Data collection across a large mycorrhizal gradient in the US, as well data in the tropics, to parameterize, test, and validate the model. 4)Scaling up mycorrhizal association measurements across landscapes using airborne hyperspectral remote sensing data. 5) Evaluation of global carbon and nutrient cycle impacts in the Community Land Model (CLM5.0) from a suite of new global mycorrhizal association maps. Over 25 publications resulted from this project, with more continuing past the project funded lifetime. Paper highlights from most of these publications have already been submitted to the DOE paper submission online system. These publications include journals such as Science and PNAS, as well as top disciplinary journals from the Nature journals, Global Change Biology, New Phytologist, and Ecology Letters, for example. Our project also contributed to improving the process representation, capabilities, and accuracy of the DOE ELM. Overall, this project significantly advanced the science of belowground plant-soil-microbial interactions as well as technical capabilities from remote sensing to modeling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

Electromagnetic reflection and transmission at interfaces involving graded dielectrics with applications to planetary radar astronomy

Reflection and transmission of electromagnetic waves at an interface between two homogeneous materials is modified when a transition zone of linearly increasing permittivity is inserted between the half spaces. Mathematical expressions for reflection and transmission coefficients are derived for waves at arbitrary incidence angles and polarized either in or perpendicular to the plane of incidence. Discontinuities in permittivity at the transition-zone boundaries are allowed. There is efficient transmission between the two half-spaces for transition-zone thicknesses of a wavelength or greater. For sharper changes, the matching layer has diminishing effect and the wave-interface interaction is characterized by the difference in properties between the two half-spaces. Examples applicable to lunar radar astronomy and airborne terrestrial remote sensing are used to illustrate the relationship between wavelength and thickness of the transition layer.

Simpson, R. A.↗
NASA NTRS1985

Convective storm downdraft outflows detected by NASA/MSFC's Airborne 10.6 micron pulsed Doppler Lidar System

The capability of a unique Airborne Doppler Lidar System to measure the horizontal winds in the vicinity of severe storm activity is demonstrated. The Airborne Doppler Lidar System (ADLS), developed at NASA/MSFC, was flown on a CV990 research aircraft during the CCOPE (Cooperative Convective Precipitation Experiments, Montana, Summer 1981). Flown between 400 and 600 m AGL, the lidar probed the subcloud regions of several deep convection storms. ADLS data collected near storms on 21 and 23 July 1981 are presented along with satellite imagery, radar echo maps and surface station measurements. These case studies are evidence of the successful performance of an airborne remote wind sensing system and the advantages of two dimension flow visualization of storm outflow structures and interactions.

Emmitt, G. D.↗
NASA NTRS1985

Spectroscopy of Moses Rock Kimberlite Diatreme

Three types of remote sensing data (Airborne Imaging Spectroscopy (AIS), NS001, Zeiss IR-photographs) were obtained for the Moses Rock kimberlite dike in southern Utah. The goal is to identify and characterize the mantle derived mafic component in such volcanic features. The Zeiss and NS001 images provide information on the regional setting and allow units of the dike to be distinguished from surrounding material. A potential unmapped satellite dike was identified. The AIS data provide characterizing information of the surface composition of the dike. Serpentized olivine-bearing soils are (tentatively) identified from the AIS spectra for a few areas within the dike.

Pieters, C. M.↗
NASA NTRS1989

MARA (Multimode Airborne Radar Altimeter) system documentation. Volume 1: MARA system requirements document

The Multimode Airborne Radar Altimeter (MARA), a flexible airborne radar remote sensing facility developed by NASA's Goddard Space Flight Center, is discussed. This volume describes the scientific justification for the development of the instrument and the translation of these scientific requirements into instrument design goals. Values for key instrument parameters are derived to accommodate these goals, and simulations and analytical models are used to estimate the developed system's performance.

Parsons, C. L.↗
NASA NTRS1992

Far-Infrared Imaging Radiometer

Inexpensive far-infrared imaging radiometer contains 128 X 128-picture-element array of AlxGa1-xAs quantum-well detectors. Potentially useful in remote sensing from airborne platforms. Industrial applications include rapid thermal imaging of heat-sensitive components. Astronomical applications include imaging of planets and Sun.

Forrest, Kathrine↗
NASA NTRS1997

Airborne Infrared Spectroscopy of 1994 Western Wildfires

In the summer of 1994 the 0.07/ cm resolution infrared Airborne Emission Spectrometer (AES) acquired spectral data over two wildfires, one in central Oregon on August 3 and the other near San Luis Obispo, California, on August 15. The spectrometer was on board a NASA DC-8 research aircraft, flying at an altitude of 12 km. The spectra from both fires clearly show features due to water vapor, carbon dioxide, carbon monoxide, ammonia, methanol, formic acid, and ethylene at significantly higher abundance and temperature than observed in downlooking spectra of normal atmospheric and ground conditions. Column densities are derived for several species, and molar ratios are compared with previous biomass fire measurements. We believe that this is the first time such data have been acquired by airborne spectral remote sensing.

Worden, Helen↗
NASA NTRS2003

Analysis of Measurements of Saharan Dust by Airborne and Ground-based Remote Sensing Methods during the Puerto Rico Dust Experiment (PRIDE)

For 26 days in mid-June and July 2000, a research group comprised of U.S. Navy, NASA, and university scientists conducted the Puerto Rico Dust Experiment (PRIDE). In this paper we give a brief overview of mean meteorological conditions during the study. We focus on findings on African dust transported into the Caribbean utilizing Navajo aircraft and AERONET Sun photometer data. During the study midvisible aerosol optical thickness (AOT) in Puerto Rico averaged 0.25, with a maximum less than 0.5 and with clean marine periods of _0.08. Dust AOTs near the coast of Africa (Cape Verde Islands and Dakar) averaged _0.4, 30% less than previous years. By analyzing dust vertical profiles in addition to supplemental meteorology and MPLNET lidar data we found that dust transport cannot be easily categorized into any particular conceptual model. Toward the end of the study period, the vertical distribution of dust was similar to the commonly assumed Saharan Air Layer (SAL) transport. During the early periods of the study, dust had the highest concentrations in the marine and convective boundary layers with only a, weak dust layer in the SAL being present, a state usually associated with wintertime transport patterns. We corroborate the findings of Maring et al. that in most cases, there was an unexpected lack of vertical stratification of dust particle size. We systematically analyze processes which may impact dust vertical distribution and determine and speculate that dust vertical distribution predominately influenced by flow patterns over Africa and differential advection couple with mixing by easterly waves and regional subsidence.

Reid, Jeffrey S.↗
NASA NTRS2002

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.anomaly. Both the visible and infrared subsystems scan in "pushbroom" mode: that is, an aircraft carrying the system moves along a ground track, the system is aimed downward, and image data are acquired in acrosstrack linear arrays of pixels. Both subsystems operate at a frame rate of 30 Hz. The infrared and visible-light optics are adjusted so that both subsystems are aimed at the same moving swath, which has across-track angular width of 15. Data from the infrared and visible imaging subsystems are stored in the same file along with aircraft-position data acquired by a Global Positioning System receiver. The combination of the three sets of data is used to construct infrared and hyperspectral maps of scanned areas shown.

Source record↗
NASA NTRS2002

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.

Lucey, Paul G.↗
NASA NTRS2017

Towards a Preservation Content Standard for Earth Observation Data

Information from Earth observing missions (remote sensing with airborne and spaceborne instruments, and in situ measurements such as those from field campaigns) is proliferating in the world. Many agencies across the globe are generating important datasets by collecting measurements from instruments on board aircraft and spacecraft, globally and constantly. The data resulting from such measurements are a valuable resource that needs to be preserved for the benefit of future generations. These observations are the primary record of the Earths environment and therefore are the key to understanding how conditions in the future will compare to conditions today. Earth science observational data, derived products and models are used to answer key questions of global significance. In the near-term, as long as the missions data are being used actively for scientific research, it continues to be important to provide easy access to the data and services commensurate with current information technology. For the longer term, when the focus of the research community shifts toward new missions and observations, it is essential to preserve the previous mission data and associated information. This will enable a new user in the future to understand how the data were used for deriving information, knowledge and policy recommendations and to repeat the experiment to ascertain the validity and possible limitations of conclusions reached in the past and to provide confidence in long term trends that depended on data from multiple missions. Organizations that collect, process, and utilize Earth observation data today have a responsibility to ensure that the data and associated content continue to be preserved by them or are gathered and handed off to other organizations for preservation for the benefit of future generations. In order to ensure preservation of complete content necessary for understanding and reusing the data and derived digital products from todays missions, it is necessary to develop a specification of such preservation content. While there are existing standards that address archival and preservation in general, there are no existing international standards or specifications today to address what content should be preserved. The purpose of this paper is to outline briefly the existing standards that apply to preservation, describe a recent effort in getting an international standard in place for specifying preservation content for Earth observation data and derived digital data products and the remaining work needed to arrive at a standard.

ISO Standards↗
NASA NTRSDate not supplied

Utilizing Airborne and Space-Based Remote Sensing Imagery to Implement the Unvegetated-Vegetated Ratio to Assess Salt Marsh Vulnerability in South Carolina

Among the most productive ecosystems on earth, salt marshes provide crucial ecosystem services including water filtration, shoreline protection, storm surge buffering, and flood mitigation. Marshes are largely dependent on their sediment budget which can significantly vary across a region and can be used to determine the life span of the marsh. Upstream land use change near Charleston, South Carolina, along with rising sea levels, are expected to alter sediment budgets and threaten marsh stability and long-term health. The unvegetated-vegetated ratio (UVVR), developed by researchers at USGS, is a scalable and efficient method to assess vulnerability. The NASA DEVELOP National Program collaborated with the South Carolina Department of Natural Resources, the South Carolina Department of Health and Environmental Control, and the United States Geological Survey Woods Hole Coastal and Marine Science Center to apply the UVVR method within Google Earth Engine. Marsh vulnerability was analyzed using UVVR derived from clustering and manual interpretation of National Agriculture Imagery Program (NAIP) high-resolution aerial imagery. NAIP derived UVVR was aggregated to Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) resolution and projection. A Random Forest Regression between Landsat derived data and UVVR was modeled to estimate a potential relationship. The estimation of this relationship was used to produce temporal change analysis maps of salt marsh vulnerability back to 1984. The NAIP imagery processed through Google Earth Engine allowed us to make detailed UVVR maps for 2009, 2015, 2017, and 2019 for decision making within South Carolina. Google Earth Engine scripting provided a novel approach to UVVR methodology that will allow decision makers to input new marsh regions and easily calculate marsh vulnerability without external data downloading. These results were used to understand what areas of the marsh need most resource allocation in the future.

NASA DEVELOP↗
NASA NTRSDate not supplied

Causes of Model Biases in Simulating Inorganic Aerosol Composition During KORUS-AQ and Implications for the Estimate of Transboundary Pollution

East Asia is a region of increasing economic growth which has led to severe PM2.5 pollution in urban areas. The joint NASA-NIER Korea-United States Air Quality (KORUS-AQ) field campaign in May-June 2016 provided an extensive dataset of ground, airborne, and remote sensing observations to test model simulations of PM2.5 pollution transport and potential control measures. During KORUS-AQ, a period of haze was observed in which PM2.5 rapidly increased to the highest levels observed during the campaign. This increase is associated with increasing inorganic aerosol. While a portion of this increase is due to long-range transport, there is observational evidence that aerosol formation from local precursors was also enhanced. This suggests that domestic policy measures could have a greater than expected influence on controlling PM2.5. However, models have difficulty reproducing PM2.5 levels, particularly the composition of secondary inorganic aerosol. Models generally underestimate sulfate and overestimate nitrate and fail to represent the peak levels of PM2.5 during haze events. These biases have been chiefly attributed to errors in chemical mechanisms and model meteorology, not issues with underlying emissions inventories. Here, we use observations from KORUS-AQ interpreted by the GEOS-Chem chemical transport model to improve the model’s ability to reproduce secondary inorganic aerosol concentrations during the campaign and explore mechanisms to improve model biases during the haze event. We assess the fraction of inorganic aerosol from the improved model simulation that results from transboundary transport during KORUS-AQ and test the model sensitivity to potential emission reduction measures that could improve air quality in Seoul during different meteorological periods including haze episodes.

Katie Travis↗
NASA NTRS2020

South Carolina Water Resources Project Summary - Implementing the Unvegetated-Vegetated Ratio to Assess Salt Marsh Vulnerability in South Carolina Using Airborne and Space-Based Remote Sensing Imagery

Among the most productive ecosystems on earth, salt marshes provide crucial ecosystem services including water filtration, shoreline protection, storm surge buffering, and flood mitigation. Marshes are largely dependent on their sediment budget which can significantly vary across a region. Upstream land use change near Charleston, South Carolina, along with rising sea levels, are expected to alter sediment budgets and threaten marsh stability and long-term health. The unvegetated-vegetated ratio (UVVR) is a scalable and efficient method to assess vulnerability. This NASA DEVELOP project collaborated with the South Carolina Department of Natural Resources, the South Carolina Department of Health and Environmental Control, and the United States Geological Survey Woods Hole Coastal and Marine Science Center. Marsh vulnerability was analyzed using UVVR derived from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) in conjunction with National Agriculture Imagery Program (NAIP) high-resolution aerial imagery. A Landsat random forest regression showed a low correlation (r2 = 0.247) between Landsat 7 ETM+ bands and NAIP aggregated UVVR suggesting the need for a more complex model and higher resolution sensors. Google Earth Engine scripting provided a novel approach to UVVR methodology that will allow decision makers to input new marsh areas and easily calculate UVVR without external data downloading.

DEVELOP Project Summary↗