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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A comparison between active and passive sensing of soil moisture from vegetated terrains

A comparison between active and passive sensing of soil moisture over vegetated areas is studied via scattering models. In active sensing three contributing terms to radar backscattering can be identified: (1) the ground surface scatter term; (2) the volume scatter term representing scattering from the vegetation layer; and (3) the surface volume scatter term accounting for scattering from both surface and volume. In emission three sources of contribution can also be identified: (1) surface emission; (2) upward volume emission from the vegetation layer; and (3) downward volume emission scattered upward by the ground surface. As ground moisture increases, terms (1) and (3) increase due to increase in permittivity in the active case. However, in passive sensing, term (1) decreases but term (3) increases for the same reason. This self conpensating effect produces a loss in sensitivity to change in ground moisture. Furthermore, emission from vegetation may be larger than that from the ground. Hence, the presence of vegetation layer causes a much greater loss of sensitivity to passive than active sensing of soil moisture.

Fung, A. K.↗
NASA NTRS1985

A comparison between active and passive sensing of soil moisture from vegetated terrains

A comparison between active and passive sensing of soil moisture over vegetated areas is studied via scattering models. In active sensing three contributing terms to radar backscattering can be identified: (1) the ground surface scatter term; (2) the volume scatter term representing scattering from the vegetation layer; and (3) the surface volume scatter term accounting for scattering from both surface and volume. In emission three sources of contribution can also be identified: (1) surface emission; (2) upward volume emission from the vegetation layer; and (3) downward volume emission scattered upward by the ground surface. As ground moisture increases, terms (1) and (3) increase due to increase in permittivity in the active case. However, in passive sensing, term (1) decreases but term (3) increases for the same reason. This self compensating effect produces a loss in sensitivity to change in ground moisture. Furthermore, emission from vegetation may be larger than that from the ground. Hence, the presence of vegetation layer causes a much greater loss of sensitivity to passive than active sensing of soil moisture.

Fung, A. K.↗
NASA NTRS1998

Cloud and Radiation Mission with Active and Passive Sensing from the Space Station

A cloud and aerosol radiative forcing and physical process study involving active laser and radar profiling with a combination of passive radiometric sounders and imagers would use the space station as an observation platform. The objectives are to observe the full three dimensional cloud and aerosol structure and the associated physical parameters leading to a complete measurement of radiation forcing processes. The instruments would include specialized radar and lidar for cloud and aerosol profiling, visible, infrared and microwave imaging radiometers with comprehensive channels for cloud and aerosol observation and specialized sounders. The low altitude,. available power and servicing capability of the space station are significant advantages for the active sensors and multiple passive instruments.

Spinhirne, James D.↗
NASA NTRS2003

Active and Passive Sensing from Geosynchronous and Libration Orbits

The development of the LEO (EOS) missions has led the way to new technologies and new science discoveries. However, LEO measurements alone cannot cost effectively produce high time resolution measurements needed to move the science to the next level. Both GEO and the Lagrange points, L1 and L2, provide vantage points that will allow higher time resolution measurements. GEO is currently being exploited by weather satellites, but the sensors currently operating at GEO do not provide the spatial or spectral resolution needed for atmospheric trace gas, ocean or land surface measurements. It is also may be possible to place active sensors in geostationary orbit. It seems clear, that the next era in earth observation and discovery will be opened by sensor systems operating beyond near earth orbit.

Schoeberl, Mark↗
NASA NTRS1979

Geologic interpretation from composited radar and Landsat imagery

Dual polarization L-band (lambda = 25 cm) radar imagery and Landsat multispectral scanner (MSS) data from central Death Valley have been computer processed and combined digitally in order to utilize the complementary information contained in multisensor data sets. Physically, like-polarized radar data gives roughness information on a scale proportional to radar wavelength. Cross-polarized data adds information on the overall roughness, particle shape, and packing density. Visible and near IR reflectivities pertain to surface chemistry. Surficial geologic units in Death Valley are defined on the basis of compositional and textural differences: optical and microwave scattering properties encoded in the multisensor image are sufficient to discriminate most of the units. This synergistic effect is most pronounced for the alluvial fans. Using radar scattering data and measured sun angle, passively-sensed (passive microwave, visible, near IR) images can be corrected for shadowing effects.

Daily, M. I.↗
NASA NTRS1991

Polarimetric passive remote sensing of periodic surfaces

The concept of polarimetry in active remote sensing is extended to passive remote sensing. The potential use of the third and fourth Stokes parameters U and V, which play an important role in polarimetric active remote sensing, is demonstrated for passive remote sensing. It is shown that, by the use of the reciprocity principle, the polarimetric parameters of passive remote sensing can be obtained through the solution of the associated direct scattering problem. These ideas are applied to study polarimetric passive remote sensing of periodic surfaces. The solution of the direct scattering problem is obtained by an integral equation formulation which involves evaluation of periodic Green's functions and normal derivative of those on the surface. Rapid evaluation of the slowly convergent series associated with these functions is observed to be critical for the feasibility of the method. New formulas, which are rapidly convergent, are derived for the calculation of these series. The study has shown that the brightness temperature of the Stokes parameter U can be significant in passive remote sensing. Values as high as 50 K are observed for certain configurations.

Veysoglu, Murat E.↗
NASA NTRS1999

New Generation Lidar Technology and Applications

Lidar has been a tool for atmospheric research for several decades. Until recently routine operational use of lidar was not known. Problems have involved a lack of appropriate technology rather than a lack of applications. Within the last few years, lidar based on a new generation of solid state lasers and detectors have changed the situation. Operational applications for cloud and aerosol research applications are now well established. In these research applications, the direct height profiling capability of lidar is typically an adjunct to other types of sensing, both passive and active. Compact eye safe lidar with the sensitivity for ground based monitoring of all significant cloud and aerosol structure and the reliability to operate full time for several years is now in routine use. The approach is known as micro pulse lidar (MPL). For MPL the laser pulse repetition rate is in the kilohertz range and the pulse energies are in the micro-Joule range. The low pulse energy permits the systems to be eye safe and reliable with solid state lasers. A number of MPL systems have been deployed since 1992 at atmospheric research sites at a variety of global locations. Accurate monitoring of cloud and aerosol vertical distribution is a critical measurement for atmospheric radiation. An airborne application of lidar cloud and aerosol profiling is retrievals of parameters from combined lidar and passive sensing involving visible, infrared and microwave frequencies. A lidar based on a large pulse, solid state diode pumped ND:YAG laser has been deployed on the NASA ER-2 high altitude research aircraft along with multi-spectral visible/IR and microwave imaging radiometers since 1993. The system has shown high reliability in an extensive series of experimental projects for cloud remote sensing. The retrieval of cirrus radiation parameters is an effective application for combined lidar and passive sensing. An approved NASA mission will soon begin long term lidar observation of atmospheric structure from space. The Geoscience Laser Altimeter System (GLAS) of the Earth Observing System is scheduled for deployment in the 2001 time frame. GLAS is both a cloud and aerosol lidar and a surface altimeter, principally for monitoring of polar ice sheets. The GLAS instrument is based on all solid state lasers operating at 40 Hz and high efficiency, solid state detectors. The design lifetime is three to five years. Data from the GLAS mission is expected to revolutionize some aspects of our understanding of the global distribution of cloud and aerosols for global climate prediction.

Spinhirne, James D.↗
NASA NTRS1993

Discrete range clustering using Monte Carlo methods

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

Chatterji, G. B.↗
NASA NTRS1982

Tropospheric Passive Remote Sensing

The long term role of airborne/spaceborne passive remote sensing systems for tropospheric air quality research and the identification of technology advances required to improve the performance of passive remote sensing systems were discussed.

Keafer, L. S., Jr.↗
NASA NTRS1986

Microwave remote sensing: Active and passive. Volume 3 - From theory to applications

Aspects of volume scattering and emission theory are discussed, taking into account a weakly scattering medium, the Born approximation, first-order renormalization, the radiative transfer method, and the matrix-doubling method. Other topics explored are related to scatterometers and probing systems, the passive microwave sensing of the atmosphere, the passive microwave sensing of the ocean, the passive microwave sensing of land, the active microwave sensing of land, and radar remote sensing applications. Attention is given to inversion techniques, atmospheric attenuation and emission, a temperature profile retrieval from ground-based observations, mapping rainfall rates, the apparent temperature of the sea, the emission behavior of bare soil surfaces, the emission behavior of vegetation canopies, the emission behavior of snow, wind-vector radar scatterometry, radar measurements of sea ice, and the back-scattering behavior of cultural vegetation canopies.

Ulaby, F. T.↗
NASA NTRS1982

Results from the July 1981 Workshop on Passive Remote Sensing of the Troposphere

Potential roles of passive remote sensors in the study of the chemistry and related dynamics of the lower atmosphere were defined by a Tropospheric Passive Remote Sensing Workshop, and technology advances required to implement these roles were identified. A promising role is in making global-scale, multilayer measurements of the more abundant trace tropospheric gaseous species (e.g., O3, CO, CH4, HNO3) and of aerosol thickness and size distribution. It includes both nadirand limb-viewing measurements. Technology advances focus on both scanning- and fixed-spectra, nadir-viewing techniques with resolutions of 0.1 kaysers or better. Balloon- and Shuttle-borne experiments should be performed to study the effects of instrument noise and background fluctuations on data inversion and to determine the utility of simultaneously obtained nadir- and limb-viewing data.

Keafer, L. S., Jr.↗
NASA NTRS2017

Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interferece-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

Passive remote sensing↗
NASA NTRS2017

Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interference-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

kurtosis↗
NASA NTRS1993

Polarimetric Passive Remote Sensing of Wind-generated Sea Surfaces and Ocean Wind Vectors

This paper investigates the theory of polarimetric passive remote sensing of wind-generated sea surfaces. A two-scale polarimetric scattering and emission model of sea surfaces is developed to interpret existing active and passive remote sensing microwave signatures of sea surfaces, and to investigate the potential application of polarimetic radiometry to ocean surface winds.

Polarimetric Remote Sensing↗
NASA NTRS2021

Evaluation of Global Surface Water Temperature Data Sets for use in Passive Remote Sensing of Soil Moisture

Inland open water bodies often pose a systematic error source in the passive remote sensing retrievals of soil moisture. Water temperature is a necessary variable used to compute water emissions that is required to be subtracted from satellite observation to yield actual emissions from the land portion, which in turn generates accurate soil moisture retrievals. Therefore, overestimation of soil moisture can often be corrected using concurrent water temperature data in the overall mitigation procedure. In recent years, several data sets of lake water temperature have become available, but their specifications and accuracy have rarely been investigated in the context of passive soil moisture remote sensing on a global scale. For this reason, three lake temperature products were evaluated against in-situ measurements from 2007 to 2011. The data sets include the lake surface water temperature (LSWT) from Global Observatory of Lake Responses to Environmental Change (GloboLakes), the Copernicus Global Land Operations Cryosphere and Water (C-GLOPS), as well as the lake mix-layer temperature (LMLT) from the European Centers for Medium-Range Weather Forecast (ECMWF) ERA5 Land Reanalysis. GloboLakes, C-GLOPS, and ERA5 Land have overall comparable performance with Pearson correlations (R) of 0.87, 0.92 and 0.88 in comparison with in-situ measurements. LSWT products exhibit negative median biases of −0.27 K (GloboLakes) and −0.31 K (C-GLOPS), whereas the median bias of LMLT is 1.56 K. When mapped from their respective native resolutions to a common 9 km Equal-Area Scalable Earth (EASE) Grid 2.0 projection, similar relative performance was observed. LMLT and LSWT data are closer in performance over the 9 km grid cells that exhibit a small range of lake cover fractions (0.05–0.5). Despite comparable relative performance, ERA5 Land shows great advantages in spatial coverage and temporal resolution. In summary, an integrated evaluation on data accuracy, long-term availability, global coverage, temporal resolution, and regular forward processing with modest data latency led us to conclude that LMLT from the ERA5 Land Reanalysis product represents the most optimal path for use in the development of a long-term soil moisture product.

Runze Zhang↗