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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Remote Sensing of Earth Terrain

Theoretical models that are useful and practical in relating remote sensing data to the important physical parameters characterizing Earth terrain are developed. The development of models that are useful in data analysis and interpretation, scene simulation, and developing new remote sensing approaches and techniques is discussed. Numerous theoretical models that are applicable to the active and passive remote sensing of plowed fields, atmospheric precipitation, vegetation, and snow fields were developed. The radiative transfer theory is used to interpret the active and passive data as a function of rain rate. Both the random medium model and the discrete scatterer model is used to study the remote sensing of vegetation fields. Due to the non-spherical geometry of the scatterers there is strong azimuthal dependence in the observed data. Thus, the anisotropic random medium model and the discrete scatterer model with nonspherical particles was developed. In order to relate the remote sensing data to the actual physical parameters, the scattering of electromagnetic waves from randomly distributed dielectric scatterers was studied. Both the rigorous random discrete scatterer theory and the strong fluctuation theory are used to derive the backscattering cross section in terms of the actual physical parameters and the results agree well with the data obtained from the snow fields.

Kong, J. A.↗
NASA NTRS2006

GPM Constellation Reconfiguration and Mission Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission that uses combined active and passive remote sensing techniques to improve global precipitation measurements derived from dedicated and operational passive microwave sensors. GPM is a science mission with integrated applications goals to (1) advance the knowledge of precipitation physics and the global water cycle variability, and (2) improve weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation and innovative application methods. The GPM Mission is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA), with opportunities for additional domestic and international partners in satellite constellation buildup and ground validation activities. The GPM concept is centered on employing a dualfrequency precipitation radar and a microwave radiometer with high-frequency capabilities on a core satellite to serve as a physics observatory and calibration standard to provide a consistent framework for unifying precipitation measurements from a heterogeneous constellation of passive microwave sensors. Building on the siccess of TRMM, GPM extends combined radadradiometer precipitation measurements into the mid and high latitudes, with new science foci on improved capabilities for light-rain and snowfall measurements, as well as more accurate precipitation retrievals over land. With recent studies indicating that AMSU-B rainfall estimates are comparable in quality to those derived from conically-scanning radiometers over land, it is envisioned that cross-track microwave sounders with high-frequency channels on operational satellites such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS), NPOESS Preparatory Project (NPP), NOAA-N', and MetOp satellites can play a significant role in augmenting conically-scanning microwave radiometers to achieve better sampling and coverage over land. Plans to reconfigure the baseline GPM constellation to include cross-track microwave sounders over land and the status of other GPM mission elements such as snowfall algorithm development and ground validation plans will be presented

Hou, Arthur Y.↗
NASA NTRS1981

Remote sensing of high-latitude ionization profiles by ground-based and spaceborne instrumentation

Ionospheric specification and modeling are now largely based on data provided by active remote sensing with radiowave techniques (ionosondes, incoherent-scatter radars, and satellite beacons). More recently, passive remote sensing techniques have been developed that can be used to monitor quantitatively the spatial distribution of high-latitude E-region ionization. These passive methods depend on the measurement, or inference, of the energy distribution of precipitating kilovolt electrons, the principal source of the nighttime E-region at high latitudes. To validate these techniques, coordinated measurements of the auroral ionosphere have been made with the Chatanika incoherent-scatter radar and a variety of ground-based and spaceborne sensors

Vondrak, R. R.↗
NASA NTRS1985

Lasers in space

Hinkley and Herring (1984) have considered the differences between active (laser) and passive remote sensing from space. The conclusion was reached that spaceborne lasers will eventually complement passive sensors in providing information on the distributions of key atmospheric species and meteorological parameters. Precise information can also be obtained of ice sheet and crustal dynamics for geological and mapping applications. NASA initiated recently an airborne measurement program directed toward some of these objectives. The program employs optical radar (laser radar) systems onboard the NASA advanced ER-2 high-flying aircraft. The results of the experiments are to provide important information with respect to the potential utility of spaceborne laser remote sensing. A study indicated that a spaceborne pulsed carbon dioxide laser could measure tropospheric winds. Attention is also given to measurements of atmospheric gases by spaceborne lasers, solid-state lasers for spaceborne remote sensing, and laser communication in space.

Hinkley, E. D.↗
NASA NTRS2004

Use of IRI to Model the Effect of Ionosphere Emission on Earth Remote Sensing at L-Band

Microwave remote sensing in the window at 1.413 GHz (L-band) set aside for passive use only is important for monitoring sea surface salinity and soil moisture. These parameters are important for understanding ocean dynamics and energy exchange between the surface and atmosphere, and both NASA and ESA plan to launch satellite sensors to monitor these parameters at L-band (Aquarius, Hydros and SMOS). The ionosphere is an important source of error for passive remote sensing at this frequency. In addition to Faraday rotation, emission from the ionosphere is also a potential source of error at L-band. As an aid for correcting for emission, a regression model is presented that relates ionosphere emission to the integrated electron density (TEC). The goal is to use TEC from sources such as TOPEX, JASON or GPS to obtain estimates of emission over the oceans where the electron density profiles needed to compute emission are not available. In addition, data will also be presented to evaluate the use of the IRI for computing emission over the ocean.

Abraham, Saji↗
NASA NTRS1995

Remote sensing measurements of atmospheric methane at 2.3 microns with a nonmechanical GFCR

Gas filter correlation radiometer (GFCR) is a passive remote sensing technique used in a variety of atmospheric measurements. In recent years, a nonmechanical optical switching GFCR has been invented and developed at NASA Langley Research Center. The use of a polarization modulator, in conjunction with a polarization beamsplitter, enables rapid optical switching without mechanically moving parts. In comparison with the conventional GFCR, which involves mechanical chopping or switching between two optical paths, the nonmechanical GFCR possesses some very attractive advantages such as fast sampling rate, high reliability, low weight, and long operational life time. In a recent study, we have developed a new GFCR configuration and have fabricated a compact, nonmechanical breadboard instrument. Using this instrument, we have carried out atmospheric methane measurements in the 2.3 micron region. Measurement results are compared with theoretical predictions using the HITRAN database.

Wang, Liang-guo↗
NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗
NASA NTRS2007

Emphasizing Spectrum Management for Sustainable Development Research and Applications in Disaster Management

NASA's spaceborne Earth and Heliospheric Observatories and airborne sensors provide a plethora of measurements. These measurements are used in science research to understand the climatology of our home planet and the solar fluxes and cycle of the only star in our solar system 'Sun' which is critical driver for the retention of life on Earth. Specifically, these measurements help us to understand the water and energy cycle, the carbon cycle, weather and climate, atmospheric chemistry, solar variability, and solid Earth and interior to feed into sophisticated mathematical models to analyze and predict the Earth's behavior as an integrated system. The main thrust of this research is on improving the prediction capability in the areas of weather, long term climate and solid Earth processes, and further help the humanity and future generations in terms of societal benefits in managing natural disasters, sustainability issues and many more. This work is further linked with our contributions in the Global Earth Observing System of Systems (GEOSS) Specifically, the data and knowledge resulting from the Earth observing systems and analytical models of the Earth can be made available for assimilation into decision support systems to serve society for disaster management. Through partnerships with national and international agencies and organizations, NASA's Science Mission Directorate's, Applied Sciences Program contributes to benchmarking practical uses of observations and predictions from Earth science remote sensing systems research. The objective is to establish innovative solutions using Earth observations and science information to provide decision support that can be adapted in applications of national and international priority. We along with the international community will continue this critical field of investigation by using our existing and future sensors from space, airborne and insitue environment. In our quest to expanding our knowledge, there will be a need for deploying additional sensors to obtain high spatial, temporal and spectral resolution measurements. These sensors operate in multiple spectral band ranging from UV, visible, infrared, microwave and radio frequency ranges. Of a particular concern is the microwave frequency bands which play a key role in land, ocean, moisture sensing. This is because of a growing commercial demand in the area of high speed broadband communication all over the world, the electronic manufacturers are looking into high frequency microwave spectral bands. This may present a risk to the remote sensing sensors because of additional sources of noise that can impair the highly sensitive passive remote sensing instruments.

Ambrose, Stephen↗
NASA NTRSDate not supplied

Single-Scattering Properties of Melting Precipitation for GPM Passive Microwave and Radar Remote Sensing Applications

Over the past two decades, detailed computational simulations of the intricate three dimensional structures of ice-phase crystals and aggregates of those crystals have been developed. The microwave single-scattering properties of these simulated ice particles have been computed and used to improve quantitative estimates of snow rates and to better deRne the vertical structure of snow water contents in deep convective systems, as derived from satellite-borne passive microwave and/or radar remote sensing measurements. The same icephase particles have more recently been used as the starting point for simulations of melting precipitation using computational melting methods. In the current study, a heuristic melting method, as well as a physically-based melting procedure based on smoothed-particle hydrodynamics, are applied to ice particle models to describe the full evolution of the particles from dry snow to liquid drops. The discrete dipole approximation is utilized to calculate the single-scattering properties of the mixed-phase particles throughout the melting process. Then, the properties of the particles are “mapped” into simpliRed microphysical simulations of particle size spectra in the melting layers of stratiform, precipitating clouds. The bulk single-scattering properties of the melting layers and the sensitivity of their properties to modeling assumptions are explored, and the implications for combined radar-radiometer precipitation remote sensing from GPM are discussed.

William S Olson↗
NASA NTRS2012

Cloud Screening and Quality Control Algorithm for Star Photometer Data: Assessment with Lidar Measurements and with All-sky Images

This paper presents the development and set up of a cloud screening and data quality control algorithm for a star photometer based on CCD camera as detector. These algorithms are necessary for passive remote sensing techniques to retrieve the columnar aerosol optical depth, delta Ae(lambda), and precipitable water vapor content, W, at nighttime. This cloud screening procedure consists of calculating moving averages of delta Ae() and W under different time-windows combined with a procedure for detecting outliers. Additionally, to avoid undesirable Ae(lambda) and W fluctuations caused by the atmospheric turbulence, the data are averaged on 30 min. The algorithm is applied to the star photometer deployed in the city of Granada (37.16 N, 3.60 W, 680 ma.s.l.; South-East of Spain) for the measurements acquired between March 2007 and September 2009. The algorithm is evaluated with correlative measurements registered by a lidar system and also with all-sky images obtained at the sunset and sunrise of the previous and following days. Promising results are obtained detecting cloud-affected data. Additionally, the cloud screening algorithm has been evaluated under different aerosol conditions including Saharan dust intrusion, biomass burning and pollution events.

data quality control algorithm↗
NASA NTRS1980

Enhancement of remote sensing through microwave technology

This overview begins with a brief look at remote sensing to date, focusing on the state of the art and the benefits that have been derived from it. Current and future microwave sensing developments are discussed pointing out special advantages and capabilities and noting the anticipated benefits. The frequency requirements of microwave sensing are outlined and the particular need to both allocate, and when necessary, protect active and passive operational sensing frequencies is emphasized.

Cehelsky, M.↗
NASA NTRS2015

Earth Observations from the International Space Station: Benefits for Humanity

The International Space Station (ISS) is a unique terrestrial remote sensing platform for observation of the Earth's land surface, oceans, and atmosphere. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted active and passive remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous, sun-synchronous sensor systems in higher altitude polar orbits. Beginning in May 2012, NASA ISS sensor systems have been available to respond to requests for data through the International Charter, Space and Major Disasters, also known as the "International Disaster Charter" or IDC. Data from digital handheld cameras, multispectral, and hyperspectral imaging systems has been acquired in response to IDC activations and delivered to requesting agencies through the United States Geological Survey. The characteristics of the ISS for Earth observation will be presented, including past, current, and planned NASA, International Partner, and commercial remote sensing systems. The role and capabilities of the ISS for humanitarian benefit, specifically collection of remotely sensed disaster response data, will be discussed.

Stefanov, William L.↗
NASA NTRS1973

Air pollution measurements from satellites

A study is presented on the remote sensing of gaseous and particulate air pollutants which is an extension of a previous report. Pollutants can be observed by either active or passive remote sensing systems. Calculations discussed herein indicate that tropospheric CO, CO2, SO2, NO2, NH3, HCHO, and CH4 can be measured by means of nadir looking passive systems. Additional species such as NO, HNO3, O3, and H2O may be measured in the stratosphere through a horizon experiment. A brief theoretical overview of resonance Raman scattering and resonance fluorescence is given. It is found that radiance measurements are most promising for general global applications, and that stratospheric aerosols may be measured using a sun occultation technique. The instrumentation requirements for both active and passive systems are examined and various instruments now under development are described.

Ludwig, C. B.↗
NASA NTRS2004

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Sea surface spectrum↗
NASA NTRS1977

Microwave remote sensing from space for earth resource surveys

The concepts of radar remote sensing and microwave radiometry are discussed and their utility in earth resource sensing is examined. The direct relationship between the character of the remotely sensed data and the level of decision making for which the data are appropriate is considered. Applications of active and a passive microwave sensing covered include hydrology, land use, mapping, vegetation classification, environmental monitoring, coastal features and processes, geology, and ice and snow. Approved and proposed microwave sensors are described and the use of space shuttle as a development platform is evaluated.

Source record↗
NASA NTRS1991

The science benefits of and the antenna requirements for microwave remote sensing from geostationary orbit

The primary objective of the Large Space Antenna (LSA) Science Panel was to evaluate the science benefits that can be realized with a 25-meter class antenna in a microwave/millimeter wave remote sensing system in geostationary orbit. The panel concluded that a 25-meter or larger antenna in geostationary orbit can serve significant passive remote sensing needs in the 10 to 60 GHz frequency range, including measurements of precipitation, water vapor, atmospheric temperature profile, ocean surface wind speed, oceanic cloud liquid water content, and snow cover. In addition, cloud base height, atmospheric wind profile, and ocean currents can potentially be measured using active sensors with the 25-meter antenna. Other environmental parameters, particularly those that do not require high temporal resolution, are better served by low Earth orbit based sensors.

Stutzman, Warren L.↗
NASA NTRS2018

NASA's Experiences with Microwave Radiometers from Ground to Space

Passive microwave sensing is sensitive to a wide variety of geophysical parameters in the atmosphere, oceans, cryosphere, and on land. For example, spaceborne passive microwave atmospheric sounders provide the highest-impact observations for state-of-the-art weather forecast models used by meteorological agencies around the world. The ability of passive microwave sensors (radiometers) to observe day or night through cloud cover and other obstacles (wavelength dependent, of course) partially compensates for their sometimes large footprint size compared to other sensor types. Examples will be presented of radiometers deployed on the ground, on aircraft, and on satellites. Each of these environments presents different challenges in obtaining accurate observations. And while many standard radiometer designs and techniques have been developed, every user re-discovers that even the "standard" approach requires careful attention in order to achieve full potential.

calibration↗
NASA NTRSDate not supplied

Active/Passive Remote Sensing of a Mature Soybean Canopy at L-band

This paper reports on development of a scattering model of a soybean canopies at L-band. The scattering model will be used for active and passive remote sensing of soybean plants with an emphasis on mature soybeans where the presence of pods is important to the observed microwave signal. The active problem is treated using the Distorted Born Approximation (DBA) and the passive problem is analyzed using Peake's method. These results are compared with field measurements made in 2012 by the truck-mounted ComRAD system, which is a combined radar and radiometer instrument operating at L-band. Investigation of backscatter from the soybean canopy shows good agreement between the radar measurement data and modeling results. The results also indicate that the L-band radar backscatter can be used to monitor both the soil moisture and the growth of the soybean pods. Past passive modeling efforts have not considered soybeans late in the growing season when pods are important. A new passive radiation model of soybean canopy will be developed based on the backscatter model.

Yiwen Zhou↗