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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

X-ray remote sensing and in-situ spectroscopy for planetary exploration missions and gamma-ray remote sensing and in-situ spectroscopy for planetary exploration missions

Detectors that will be used for planetary missions must have their responses calibrated in a reproducible manner. A calibration facility is being constructed at Schlumberger-Doll Research for gamma and x ray detectors. With this facility the detector response can be determined in an invariant and reproducible fashion. Initial use of the facility is expected for the MARS94 detectors. Work is continuing to better understand the rare earth oxyorthosilicates and to define their characteristics. This will allow a better use of these scintillators for planetary missions. In a survey of scintillating materials two scintillators were identified as promising candidates besides GSO, LSO, and YSO. These are CdWO4 and CsI(Tl). It will be investigated if a detector with a better overall performance can be assembled with various photon converters. Considerable progress was achieved in photomultiplier design. The length of an 1 inch diameter PMT could be reduced from 4.2 to 2.5 inches without performance degradation. This technology is being employed in the gamma ray detector for the NEAR project. A further weight and size reduction of the detector package can be achieved with miniaturized integrated power supplies.

Mahdavi, M.↗
NASA NTRS2004

Remote Sensing of the Haughton Impact Structure (HIS): A Terrestrial Proof of Concept for Using the Remote Sensing of Martian Craters as a Probe of Subsurface Composition

Impact cratering is the most widespread geological process in the Solar System. Impact craters can provide 'windows' into the subsurfaces of planetary bodies through excavation and uplift. By utilizing remote methods in the visible and near infrared (VNIR; 0.4-1.4 micron), short-wavelength infrared (SWIR; 1.4-2.5 micron) and thermal infrared (TIR 7-14 micron), subsurface mineral compositions may be identified and mapped via impact craters. Complex craters in particular, expose minerals from both the shallow and deep-seated subsurface, which may be identified spectroscopically. Complex craters have morphological features such as central peaks or peak rings, which are composed of relatively coherent lithologies tapped from deep-seated crustal components. While near-surface crustal components can be observed as coherent rocks uplifted and exposed in the rim and the crater walls, and from the ejecta deposits. Only two previously published studies using this approach have been successful on large planetary bodies. Tompkins and Pieters utilized ultraviolet and VNIR from Clementine to characterize near- and deep-subsurface materials in and around lunar craters. The work of Ramsey and Wright was the first remote spectroscopic study to successfully identify near-subsurface materials in the ejecta and crater wall of a terrestrial impact structure, namely Meteor Crater. Here we present early results of a third such study, a remote spectroscopy evaluation of the Haughton impact structure (HIS). The purpose of this study is to serve as terrestrial proof of concept that remote visible/infrared spectroscopic methods in this case, analysis of LANDSAT 7 ETM+ and ASTER data of the well-preserved HIS can be utilized in deciphering the subsurface composition of planetary crusts. This technique is particularly promising for Mars were limited tectonic uplift and ubiquitous dust-mantling offer few opportunities to access subsurface information.

Tornabene, L. L.↗
NASA NTRS1978

Remote sensing of water quality

Remote sensing from aircraft has been used to determine water content in areas such as the New York Bight. Extension of the techniques developed to satellite sensing of the Chesapeake Bay will begin in 1978 with the launch of Nimbus-G. Remote sensing offers a number of interesting possibilities for investigating a reasonably large body of water, such as the Chesapeake Bay, coupled with some disadvantages. The chief advantage of remote sensing is that it offers the opportunity to cover large areas in relatively short periods of time. Low altitude satellites traveling at about 7 km/s can cover the Chesapeake Bay in about 1 minute so that the entire Bay can be studied under almost identical conditions of solar illumination.

Hovis, W. A.↗
NASA NTRS2017

Creating Aerosol Types Form CHemistry (CATCH): a New Algorithm to Extend the Link Between Remote Sensing and Models

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

K W Dawson↗
NASA NTRS1991

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.

Yueh, Herng-Aung↗
NASA NTRS1983

Determination of the utility of remote sensing data for land use/cover analysis in the lower Appalachia region: Assessing the utility of remote sensing data for archeological site recognition

Thematic Mapper Simulator (TMS) data were gathered by NASA/ERL over a portion of the lower Ohio River and the middle Mississippi River valleys on April 11, 1982. CIR imagery accompanied the 10 and 30 meter resolution TMS data sets. This area is somewhat unique archeologically as there exists a concentration of sites with major features such as mounds, earthworks, and villages. It was the primary purpose of this study to determine the utility of TMS data in identifying signatures which are distinctly archeological. TMS data were processed using the NASA/ERL software package ELAS. No signatures that were distinctly archeological were detected, due in large part to the complexity of the land cover and land use practices. However, as more sophisticated classification techniques were employed, the classes which were related to archeological features were narrowed. TMS data could certainly be of assistance to a trained archeologist/interpreter in narrowing an area which has to be field-surveyed as anomalous features can be recognized within a particular environmental context.

Weber, N. V.↗
NASA NTRS1973

Remote sensing aids geologic mapping.

Remote sensing techniques have been applied to general geologic mapping along the Rio Grande rift zone in central Colorado. A geologic map of about 1,100 square miles was prepared utilizing (1) prior published and unpublished maps, (2) detailed and reconnaissance field maps made for this study, and (3) remote sensor data interpretations. The map is to be used for interpretation of the complex Cenozoic tectonic and geomorphic histories of the area. Regional and local geologic mapping can be aided by the proper application of remote sensing techniques. Conventional color and color infrared photos contain a large amount of easily-extractable general geologic information and are easily used by geologists untrained in the field of remote sensing. Other kinds of sensor data used in this study, with the exception of SLAR imagery, were generally found to be impractical or unappropriate for broad-scale general geologic mapping.

Knepper, D. H., Jr.↗
NASA NTRS1990

Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Kong, Jin AU↗
DOE OSTI2024

Probing the atmospheric boundary layer with integrated remote-sensing platforms during the American WAKE ExperimeNt (AWAKEN) campaign

The American WAKE ExperimeNt (AWAKEN) collaboration is an observational-based field campaign in northern Oklahoma intended to analyze the potential influence of onshore wind farms and their collective wakes on wind power production, turbine structural loads, and on the atmospheric boundary layer (ABL). Focusing on the ABL effects, the University of Oklahoma and the Lawrence Livermore National Laboratory collected continuous high-resolution kinematic and thermodynamic profile measurements during 2022 and Summer 2023. The deployment strategy for these campaigns is detailed first, followed by an initial comparison of data from two sites in the AWAKEN domain: a near-farm site to examine collective wake impacts on the ABL, and a far-field site remaining outside the wind farm-waked region. Here, we summarize the datasets available and demonstrate the benefits of these observations and multiple value-added products (VAPs) for investigation of ABL features observed during AWAKEN. We also highlight examples of preliminary analyses, including ABL height detection and nocturnal low-level jet examination, which are produced using novel VAPs based on optimal estimation to retrieve deeper Doppler lidar wind profiles than previously resolved, along with their uncertainty. By including the near-farm and far-field site in these analyses, we identified a pattern of stronger lower-atmospheric mixing at the near-farm site than the far-field site, motivating deeper investigation into the relationship between wind farms and general ABL characteristics. Future analysis will delve deeper into this relationship by examining other ABL characteristics, such as atmospheric stability and convection.

17 WIND ENERGY↗
NASA NTRS1985

Theory of microwave remote sensing

Active and passive microwave remote sensing of earth terrains is studied. Electromagnetic wave scattering and emission from stratified media and rough surfaces are considered with particular application to the remote sensing of soil moisture. Radiative transfer theory for both the random and discrete scatterer models is examined. Vector radiative transfer equations for nonspherical particles are developed for both active and passive remote sensing. Single and multiple scattering solutions are illustrated with applications to remote sensing problems. Analytical wave theory using the Dyson and Bethe-Salpeter equations is employed to treat scattering by random media. The backscattering enhancement effects, strong permittivity fluctuation theory, and modified radiative transfer equations are addressed. The electromagnetic wave scattering from a dense distribution of discrete scatterers is studied. The effective propagation constants and backscattering coefficients are calculated and illustrated for dense media.

Tsang, L.↗
DOE OSTI2022

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis . Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Experimental philosophy leading to a small scale digital data base of the conterminous United States for designing experiments with remotely sensed data

Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.

Labovitz, M. L.↗
NASA NTRS2007

Online Remote Sensing Interface

BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.

Lawhead, Joel↗
NASA NTRS1993

Remote sensing of Earth terrain

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Kong, J. A.↗