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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 109 records · Page 6

Direct Top-down Estimates of Biomass Burning CO Emissions Using TES and MOPITT Versus Bottom-up GFED Inventory

In this study, we utilize near-simultaneous observations from two sets of multiple satellite sensors to segregate Tropospheric Emission Spectrometer (TES) and Measurements of Pollution in the Troposphere (MOPITT) CO observations over active fire sources from those made over clear background. Hence, we obtain direct estimates of biomass burning CO emissions without invoking inverse modeling as in traditional top-down methods. We find considerable differences between Global Fire Emissions Database (GFED) versions 2.1 and 3.1 and satellite-based emission estimates in many regions. Both inventories appear to greatly underestimate South and Southeast Asia emissions, for example. On global scales, however, CO emissions in both inventories and in the MOPITT-based analysis agree reasonably well, with the largest bias (30%) found in the Northern Hemisphere spring. In the Southern Hemisphere, there is a one-month shift between the GFED and MOPITT-based fire emissions peak. Afternoon tropical fire emissions retrieved from TES are about two times higher than the morning MOPITT retrievals. This appears to be both a real difference due to the diurnal fire activity variations, and a bias due to the scarcity of TES data.

bias↗

Research in remote sensing of agriculture, earth resources, and man's environment

Progress is reported for several projects involving the utilization of LANDSAT remote sensing capabilities. Areas under study include crop inventory, crop identification, crop yield prediction, forest resources evaluation, land resources evaluation and soil classification. Numerical methods for image processing are discussed, particularly those for image enhancement and analysis.

Landgrebe, D. A.↗

Landslide Mapping Along the Karnali Highway, Nepal using High-Resolution Imagery

The Karnali highway (Figure 1) is the only major transportation link that connects the remote Karnali region to the provincial capital in Province 6 of Nepal. This area becomes inaccessible by roads during every rainy season due to landslides. Despite the known landslide frequency, there have been no systematic landslide inventories conducted along this highway to date. Recent advancements in remote-sensing technologies have significantly increased our ability to map landslides of various sizes rapidly with less in situ surveys or human interaction. Landslide susceptibility, hazard and risk studies require a complete landslide inventory, which might only be possible from very high-resolution (VHR) and high-resolution (HR) imagery. Recent launch of Sentinel-2 in 2015 has provided free access to HR imagery enabling landslide detection at finer scales then what was possible with previous open source satellite imagery obtained from Landsat and ASTER. Satellites providing VHR imagery are commercially owned, expensive and not freely available expect for when disasters charter is activated. NextView licensing agreement, a partnership between the US government and US commercial vendors provides access to VHR imagery to federal agencies in support of scientific research [1]. This partnership provides access to VHR imagery obtained from the DigitalGlobe (DG) constellation which enables mapping of small landslides (< 100 m2). In this study, VHR imagery from DG and HR imagery from Sentinel-2 will be used to map landslides along the Karnali highway using a semi automatic method based on object-oriented analysis (OOA) to create most recent and up-to-date landslide inventory. The effectiveness of this remote sensing based landslide inventory to produce a susceptibility map and its predictive capacity will be tested.

landslide↗

High-Resolution Mapping of Nitrogen Oxide Emissions in Large US Cities From TROPOMI Retrievals of Tropospheric Nitrogen Dioxide Columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NO x ) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO x emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO 2 ) retrievals. The accuracy of the coupled method is validated through application to synthetic NO 2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88 ± 0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

NOx emissions↗

Coastal wetlands - Prospects for satellite inventory

It is pointed out that coastal wetlands are among the nation's most valuable natural resources. A relatively low cost and moderately accurate method for mapping these areas would, therefore, be very attractive. It appears that such a method could be found by utilizing ERTS-1 data. Two test sites were selected for an intensive study of the feasibility of such an approach. One test area involves a salt marsh complex located at the mouth of the Chincoteague Bay in Virginia. The second area constitutes a near-saline marsh at the mouth of the Nanticoke River, Maryland. The study shows that ERTS-1 digital data provide maximum gray-level resolution for the mapping of wetland species and features.

Anderson, R. R.↗

Study of application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

The author has identified the following significant results. The mine refuse inventory maps were prepared in response to a need by both the State and the coal industry. The lack of information on the scope of the problem handicapped all people concerned in drafting realistic legislation for a severance tax on coal production to raise funds for restoration of refuse sites. The inventory was conducted rapidly and economically, and demonstrated the benefits which can be derived through remote sensing methods.

Wier, C. E.↗

Gaseous fuel reactors for power systems

Gaseous-fuel nuclear reactors have significant advantages as energy sources for closed-cycle power systems. The advantages arise from the removal of temperature limits associated with conventional reactor fuel elements, the wide variety of methods of extracting energy from fissioning gases, and inherent low fissile and fission product in-core inventory due to continuous fuel reprocessing. Example power cycles and their general performance characteristics are discussed. Efficiencies of gaseous fuel reactor systems are shown to be high with resulting minimal environmental effects. A technical overview of the NASA-funded research program in gaseous fuel reactors is described and results of recent tests of uranium hexafluoride (UF6)-fueled critical assemblies are presented.

Kendall, J. S.↗

On the transfer of remote sensing technology to an operational data system

Data processing techniques for the transfer of remote sensing technology to an operational data system are evaluated. The study is aimed at developing a scheme for the improvement of the quantifying cost/performance ratio, noting the timeliness of the results, the ease of system development, system operating costs, and accuracy. The method is applicable to the Production Area and Yield Estimation System (PAYES) and the Large Area Crop Inventory Experiment (LACIE).

Tarbet, J. D.↗

Reporter Concerns in 300 Mode-Related Incident Reports from NASA's Aviation Safety Reporting System

A model has been developed which represents prominent reporter concerns expressed in the narratives of 300 mode-related incident reports from NASA's Aviation Safety Reporting System (ASRS). The model objectively quantifies the structure of concerns which persist across situations and reporters. These concerns are described and illustrated using verbatim sentences from the original narratives. Report accession numbers are included with each sentence so that concerns can be traced back to the original reports. The results also include an inventory of mode names mentioned in the narratives, and a comparison of individual and joint concerns. The method is based on a proximity-weighted co-occurrence metric and object-oriented complexity reduction.

McGreevy, Michael W.↗

Spaceborne Applications of P-Band Imaging Radars for Measuring Forest Biomass

In three test sites of boreal and temperate forests, P-band polarimetric radar data estimate total above-ground dry woody biomass with 10 to 30 of the actual biomass values, depending on the complexity of the forest. A description and examples of the process are provided. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forest inventories.

Oren, Ram↗

Tidal Insights into Rocky and Icy Bodies: An Introduction and Overview

Solid body tides provide key information on the interior structure, evolution, and origin of the planetary bodies. Our Solar system harbours a very diverse population of planetary bodies, including those composed of rock, ice, gas, or a mixture of all. While a rich arsenal of geophysical methods has been developed over several years to infer knowledge about the interior of the Earth, the inventory of tools to investigate the interiors of other Solar-system bodies remains limited. With seismic data only available for the Earth, the Moon, and Mars, geodetic measurements, including the observation of the tidal response, have become especially valuable and therefore, has played an important role in understanding the interior and history of several Solar system bodies. To use tidal response measurements as a means to obtain constraints on the interior structure of planetary bodies, appropriate understanding of the viscoelastic reaction of the materials from which the planets are formed is needed. Here, we review the fundamental aspects of the tidal modeling and the information on the present-day interior properties and evolution of several planets and moons based on studying their tidal response. We begin with an outline of the theory of viscoelasticity and tidal response. Next, we proceed by discussing the information on the tidal response and the inferred structure of Mercury, Venus, Mars and its moons, the Moon, and the largest satellites of giant planets, obtained from the analysis of the data that has been provided by space missions. We also summarise the upcoming possibilities offered by the currently planned missions.

Tides↗

Petrologic Comparison of High- and Low-Titanium Basalt Clasts Derived From ANGSA Core 73001

Volatile elements and compounds significantly influence the properties and behavior of magma, including ascent and eruptive processes. Basalts record a complicated history of the volatile species inherent to their parental magma, and the processes, such as degassing, that change these volatile inventories. On the Moon, outstanding questions remain concerning the behavior of magmatic volatiles and their roles in the evolution of lunar magmas and the formation of mare basalts. As part of the Apollo Next Generation Sample Analysis (ANGSA) program, we are investigating the petrogenesis of two basalt clasts collected from the recently processed Apollo 17 drive tube, 73001. Our team is studying the petrology of the two basalt clasts in 2D and 3D. Recent work has highlighted the utility of coupling traditional 2D methods with 3D measurements to better understand the crystallization and degassing histories of lunar lava flows. We are also investigating the volatile inventory of the samples through in situ studies of volatile-bearing phases, like apatite, to understand the eruptive signatures and degassing histories of low-titanium and high-titanium lunar basalts. At the upcoming conference, we will present the first detailed study of the 2D and 3D mineralogy, textures, 3D vesiculation, and chemistry of these basalt clasts to shed light on their magmatic, volcanic, and post-eruptive histories.

Basalt↗

Analyzing Carbon Dioxide and Methane Emissions in California Using Airborne Measurements and Model Simulations

Greenhouse gas (GHG) concentrations have increased over the past decades and are linked to global temperature increases and climate change. These changes in climate have been suggested to have varying effects, and uncertain consequences, on agriculture, water supply, weather, sea-level rise, the economy, and energy. To counteract the trend of increasing atmospheric concentrations of GHGs, the state of California has passed the California Global Warming Act of 2006 (AB-32). This requires that by the year 2020, GHG (e.g., carbon dioxide (CO2) and methane (CH4)) emissions will be reduced to 1990 levels. To quantify GHG fluxes, emission inventories are routinely compiled for the State of California (e.g., CH4 emissions from the California Greenhouse Gas Emissions Measurement (CALGEM) Project). The major sources of CO2 and CH4 in the state of California are: transportation, electricity production, oil and gas extraction, cement plants, agriculture, landfills/waste, livestock, and wetlands. However, uncertainties remain in these emission inventories because many factors contributing to these processes are poorly quantified. To alleviate these uncertainties, a synergistic approach of applying air-borne measurements and chemical transport modeling (CTM) efforts to provide a method of quantifying local and regional GHG emissions will be performed during this study. Additionally, in order to further understand the temporal and spatial distributions of GHG fluxes in California and the impact these species have on regional climate, CTM simulations of daily variations and seasonality of total column CO2 and CH4 will be analyzed. To assess the magnitude and spatial variation of GHG emissions and to identify local “hot spots”, airborne measurements of CH4 and CO2 were made by the Alpha Jet Atmospheric eXperiment (AJAX) over the San Francisco Bay Area (SFBA) and San Joaquin Valley (SJV) in January and February 2013 during the Discover-AQ-CA study. High mixing ratios of GHGs were observed in-flight with a high degree of spatial variability. To provide an additional method to quantify GHG emissions, and analyze AJAX measurement data, the GEOS-Chem CTM is used to simulate SFBA/SJV GHG measurements. A nested-grid version of GEOS-Chem will be applied and utilizes varying emission inventories and model parameterizations to simulate GHG fluxes/emissions. The model considers CO2 fluxes from fossil fuel use, biomass/biofuel burning, terrestrial and oceanic biosphere exchanges, shipping and aviation, and production from the oxidation of carbon monoxide, CH4, and non-methane volatile organic carbons. The major sources of CH4 simulated in GEOS-Chem are domesticated animals, rice fields, natural gas leakage, natural gas venting/flaring (oil production), coal mining, wetlands, and biomass burning. Preliminary results from the comparison between available observations (e.g., AJAX and CALGEM CH4 emission maps) and GEOS-Chem results will be presented, along with a discussion of CO2 and CH4 source apportionment and the use of the GEOS-Chem-adjoint to perform inverse GHG modeling.

Johnson, Matthew S.↗

Satellite data for surface-mine inventory

To determine the feasibility of satellite data for surface-mine inventory, particularly as it applies to coal, a case study was conducted in Maryland. A band-ratio method was developed to measure disturbed surface areas, and it proved to be extendible both temporally and geographically. This method was used to measure area changes in the region over three time periods from September 1972 through July 1974 and to map the entire two-county area for 1973. For mines ranging between 31 and 244 acres (12 to 98 hectares) the measurement accuracy of total affected acreage was determined to be 92%. Mines of 120 acres (50 hectares) and larger were measured with greater accuracy, some within one percent of the actual area. The ability to identify, classify, and measure strip-mine surfaces in a two-county area (1,541 square kilometers - 595 square miles) of western Maryland was demonstrated through the use of computer processing. On the basis of these results the use of LANDSAT satellite data and multilevel sampling of aircraft and field verification inspections, multispectral analysis of digital data is shown to be an effective, rapid, and accurate means of monitoring the surface mining cycle.

Anderson, A. T.↗

The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary

Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.

Castruccio, P. A.↗

Remote sensing applications for range management

The use of satellite information for range management is discussed. The use of infrared photography and color photography for analysis of vegetation cover is described. The methods of interpreting LANDSAT imagery are highlighted and possible applications of such interpretive methods to range management are considered. The concept of using LANDSAT as a sampling frame for renewable natural resource inventories was examined. It is concluded that a blending of LANDSAT vegetation data with soils and digital terrain data, will define a basic sampling unit that is appropriate for range management utilization.

Haas, R. H.↗

Research in the application of spectral data to crop identification and assessment, volume 2

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

Daughtry, C. S. T.↗

Using Satellite Observations to Evaluate the AeroCOM Volcanic Emissions Inventory and the Dispersal of Volcanic SO2 Clouds in MERRA

Simulation of volcanic emissions in climate models requires information that describes the eruption of the emissions into the atmosphere. While the total amount of gases and aerosols released from a volcanic eruption can be readily estimated from satellite observations, information about the source parameters, like injection altitude, eruption time and duration, is often not directly known. The AeroCOM volcanic emissions inventory provides estimates of eruption source parameters and has been used to initialize volcanic emissions in reanalysis projects, like MERRA. The AeroCOM volcanic emission inventory provides an eruptions daily SO2 flux and plume top altitude, yet an eruption can be very short lived, lasting only a few hours, and emit clouds at multiple altitudes. Case studies comparing the satellite observed dispersal of volcanic SO2 clouds to simulations in MERRA have shown mixed results. Some cases show good agreement with observations Okmok (2008), while for other eruptions the observed initial SO2 mass is half of that in the simulations, Sierra Negra (2005). In other cases, the initial SO2 amount agrees with the observations but shows very different dispersal rates, Soufriere Hills (2006). In the aviation hazards community, deriving accurate source terms is crucial for monitoring and short-term forecasting (24-h) of volcanic clouds. Back trajectory methods have been developed which use satellite observations and transport models to estimate the injection altitude, eruption time, and eruption duration of observed volcanic clouds. These methods can provide eruption timing estimates on a 2-hour temporal resolution and estimate the altitude and depth of a volcanic cloud. To better understand the differences between MERRA simulations and volcanic SO2 observations, back trajectory methods are used to estimate the source term parameters for a few volcanic eruptions and compared to their corresponding entry in the AeroCOM volcanic emission inventory. The nature of these mixed results is discussed with respect to the source term estimates.

OMI SO2↗