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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 OSTI2022

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by low-altitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data; while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data (thermal, RGB, and multispectral) derived from an unmanned aerial vehicle (UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination (R 2 ) ranging from 0.40 to 0.53 under water-stressed environment and 0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yield-based drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed data. Collectively, this study demonstrated a promising strategy for the use of different UAV-based imaging sensors to quantify yield-based drought tolerance.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessment of ITER radiation environment during the remote-handling operation of In-Vessel components with D1SUNED

During ITER operational life, a remote-handled cask will be used to transfer In-Vessel components to the Hot Cell for maintenance, storage and decommissioning purposes. Due to the distribution of penetrations for system allocation in the facility, the radiation field of each transfer operation presents a high spatial variability; all operations must be studied independently for workers and electronics protection. In this paper, we present a fully representative approach to describe the radiation environment during the complete remote-handling scenario of In-Vessel components in the ITER facility. The impact of all relevant radiation sources during different stages of the operation is addressed. As-built structures and 2020 baseline designs are considered to produce the most detailed neutronics model of the Tokamak Complex, the 400,000-tonne civil structure hosting the tokamak, up to date. Novel capabilities of the D1SUNED code have allowed to compute the integral dose, the dose rate and the photon-induced neutron flux of both moving and static radiation sources. Time bins are included in the simulations to compute the dose rate caused by In-Vessel components at all positions along the transfer. The time evolution of the dose rate is built in video format with a 1-m resolution, especially valuable for hot-spots identification.

42 ENGINEERING↗
NASA NTRS1983

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗
NASA NTRS1983

Assessment of wetland productive capacity from a remote-sensing-based model - A NASA/NMFS joint research project

NASA and the U.S. National Marine Fisheries Service have undertaken the development of Landsat Thematic Mapper (TM) technology for the evaluation of the usefulness of wetlands to estuarine fish and shellfish production. Toward this end, a remote sensing-based Productive Capacity model has been developed which characterizes the biological and hydrographic features of a Gulf Coast Marsh to predict detrital export. Regression analyses of TM simulator data for wetland plant production estimation are noted to more accurately estimate the percent of total vegetative cover than biomass, indicating that a nonlinear relationship may be involved.

Butera, M. K.↗
NASA NTRS1986

Assessing impacts of off-nadir observation on remote sensing of vegetation - Use of the Suits model

The use of Suits' (1972a, b) digital radiative transfer model to simulate the effect of nonLambertian canopy reflectance on off-nadir observations of vegetation is discussed. Canopy reflectances of cord grass are calculated using the radiative transfer model, field radiometric measurements, and airborne multispectral scanner data. The effects of varying view angles on canopy reflectance are analyzed and compared. The comparison reveals that the model is effective in simulating the sense and magnitude of reflectance change due to variable angles of observations; however, the model does not reproduce the observed dependence of nadir canopy reflectance on solar zenith angle. It is concluded that the radiative transfer model is applicable for predicting the variation in canopy reflectance due to changing view zenith angles.

Bartlett, D. S.↗
DOE OSTI2022

Public – Private Partnership to Promote Efficient Manufacturing and Workforce Development (IAC Final Technical Report)

Through delivering ninety (90) energy assessments to small- and medium-sized manufacturing facilities in and around Tennessee, significant understandings were gained through providing detailed energy assessment reports to manufacturers and training seventy-seven (77) engineering students in which thirty-five (35) certified IAC students were recognized by DOE. The robust involvement of Tennessee Valley Authority (TVA), local utility and Tennessee Tech’s Cybersecurity Education, Research, and Outreach Center (CEROC) in majority of assessments made the technical operation very effective where leaded to 40.5% implementation rate of energy recommendations. Other benefits of the award to the public are a dynamic modeling tool capable of analyzing existing cooling towers for energy use optimization was developed and presented to DOE IAC, providing technical assistance to non-participating manufacturers in the form of workshop and training, publishing fifteen (15) peer-reviewed conference and journal papers as well as a book chapter in the area of industrial energy efficiency field, assisting the TVA Magnolia Combined Cycle Power Plant to become the First 50001 Ready Certified Power Plant in the U.S. through briefing them on ISO 50001 and 50001 Ready as well as providing an energy assessment to the plant, assisted the new IAC center at Clemson University with on-site and remote support, and provided assessment and training in unique areas of water, waste water, cyber security and smart manufacturing to our clients, students and community.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1985

Optical remote sensing of the earth

In the present assessment of the contributions of optical earth resources remote sensing in the 0.4-15.0 micron region, attention is given to underlying principles, applications to scientific disciplines such as geology, hydrology and oceanography, the recent development history of the requisite sensors, and sensor development trends. Development status characterizations are given for thematic mapping, modular optoelectronic multispectral scanning, the telescope/CCD 'SPOT' program of France, the thermal IR multispectral scanner for mineral signature identification, airborne imaging spectrometry, and the Advanced Visible and IR Imaging Spectrometer that is nearing deployment. Technology development trends and the capabilities they portend are projected.

Goetz, A. F. H.↗
NASA NTRS1983

Potential impact of remote sensing data on sea-state analysis and prediction

The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

Cardone, V. J.↗
NASA NTRS2000

Mt. Washington Icing Sensors Project (MWISP) Tests Technologies for Remote Sensing of Icing Conditions

The Mt. Washington Icing Sensors Project (MWISP) was an intensive multiagency field test of remote-sensing technologies and methods for in-flight icing detection. This field test was the first comprehensive examination of multiple remote-sensing technologies, and it included ground and airborne in situ measurements for comparison. The data gathered will allow the assessment of icing remote-sensing technologies leading toward the development of ground-based and airborne systems. These systems will provide flight crews with the information required for avoiding or exiting hazardous icing conditions.

Reehorst, Andrew L.↗
NASA NTRS2003

Flood warnings, flood disaster assessments, and flood hazard reduction: the roles of orbital remote sensing

Orbital remote sensing of the Earth is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction.

floods↗
NASA NTRS2003

Flood warnings, flood disaster assessments, and flood hazard reduction : the roles of orbital remote sensing

Orbital remote sensing is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent (near-daily) radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction. These latter tasks are accomplished, in part, by accurate mapping of flooded lands and commonly over periods of several days or more. We use radar scatterometer data from QuikSCAT to detect changes in surface water area and with a full global coverage every 2.5 days. Also, MODIS, RADARSAT, and other higher spatial resolution data are used for flood mapping and other flood measurements. These records are preserved in a global flood hazard atlas at http://www.dartmouth.edu/-floods/Atlas.html.

Shabaneh, Tamer B.↗
NASA NTRS2021

Mangrove Carbon Stocks in Pongara National Park, Gabon

Mangroves are recognized for their valued ecosystem services to coastal areas, and the functional linkages between those services and ecosystem carbon stocks have been established. However, spatially explicit inventories are necessary to facilitate management and protection of mangroves, as well as providing a foundation for payment for ecosystem service programs such as REDD+. We conducted an inventory of carbon stocks in mangroves within Pongara National Park (PNP), Gabon using a stratified random sampling design based on forest canopy height derived from TanDEM-X remote sensing data. Ecosystem carbon pools, including aboveground and belowground biomass and necromass, and soil carbon to a depth of 2 m were assessed using measurements and samples from plots distributed among three canopy height classes within the park. There were two mangrove species within the inventory area in PNP, Rhizophora racemosa and R. harrisonii. R. harrisonii was predominant in the sparse, low-stature stands that dominated the west side of the park. In the east side of the park, both species occurred in tall-stature stands, with tree height often exceeding 30 m. Canopy height was an effective means to stratify the inventory area, as biomass was significantly different among the height classes. Despite those differences in aboveground biomass, the soil carbon density was not significantly different among height classes. Soils were the main component of the ecosystem carbon stock, accounting for over 84% of the total. The ecosystem carbon density ranged from 644 to 943 Mg C ha−1 among the three height classes. The ecosystem carbon stock within PNP is estimated to be 40,588 Gg C. The combination of pre-inventory information about stand conditions and their spatial distribution within the assessment area obtained from remote sensing data and a spatial decision support system were fundamental to implementing this relatively large-scale field inventory. This work exemplifies how mangrove carbon stocks can be quantified to augment national C reporting statistics, provide a baseline for projects involving monitoring, reporting and verification (i.e., MRV), and provide data on the forest composition and structure for sustainable management and conservation practices.

Carl C Trettin↗
NASA NTRS2006

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS2011

Resolution Assessment in Dynamic Image Formation

Remote sensing and astronomical image formation is often complicated by deficiencies in measurement quality, density, or diversity. Penalized likelihood methods can incorporate additional first-principles physical prior knowledge and improve the image reconstructions, but a systematic bias is unavoidable as a consequence. This work derives theory to understand the bias and develops a computational tool to probe its effect on the reconstructed image and bound resolution limits. Though the focus is on image formation, the contributions of this paper apply to any inference problem that can be expressed under the linear state-space signal model.

multidimensional signal processing↗
NASA NTRS1979

Overview of the NASA tropospheric environmental quality remote sensing program

This paper will summarize the current NASA Tropospheric Environmental Quality Remote Sensing Program for studying the global and regional troposphere from space, airborne and ground-based platforms. As part of the program to develop remote sensors for utilization from space, NASA has developed a series of passive and active remote sensors which have undergone field test measurements from airborne and ground platforms. Recent measurements with active lidar and passive gas filter correlation and infrared heterodyne techniques will be summarized for measurements of atmospheric aerosols, CO, SO2, O3, and NH3. These measurements provide the data base required to assess the sensitivity of remote sensors for applications to urban and regional field measurement programs. Studies of Earth Observation Satellite Systems are currently being performed by the scientific community to assess the capability of satellite imagery to detect regions of elevated pollution in the troposphere. The status of NASA sponsored research efforts in interpreting satellite imagery for determining aerosol loadings over land and inland bodies of water will be presented, and comments on the potential of these measurements to supplement in situ and airborne remote sensors in detecting regional haze will be made.

Allario, F.↗