SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A brief review of remote sensing state-of-the-art is presented. Emphasis is placed on an understanding of remote sensing terminology. Passive and active sensors and sensor platforms from the spacecraft program to the ground truth program are described.
Sensitivity requirements of the various measurements obtained by microwave sensors, and radiometry techniques are described. Analytical techniques applied to detailed sharing analyses are discussed. A bibliography of publications pertinent to the scientific justification of frequency requirements for passive microwave remote sensing is included.
Microwave images of sea ice obtained by Nimbus-5 and the NASA CV-990 airborne laboratory are used to determine the time variation of the sea-ice concentration and multiyear ice fraction within the pack ice in the Arctic Basin. The images, constructed from data acquired from the electrically scanned microwave radiometer, are analyzed for four seasons during 1973-1975. Observations indicate significant variations in the sea-ice concentration in the spring, late fall, and early winter. Sea-ice concentrations as low as 50% were detected in large areas in the interior of the Arctic polar sea-ice pack. The applicability of passive-microwave remote sensing for monitoring the time dependence of sea-ice concentration is considered.
Recent results indicate that microwave radiometry has the potential for inferring the snow depth and water equivalent information from snowpacks. In order to assess this potential for determining the water equivalent of a snowpack, it is necessary to understand the microwave emission and scattering behavior of the snow at various wavelengths under carefully controlled conditions. Truck-mounted microwave instrumentation was used to study the microwave characteristics of the snowpack in the Colorado Rocky Mountain region during the winters of 1977 to 78 and 7978 to 79. The spectral signatures of C, X, K sub u, and K sub a band radiometers with dual polarization were used, together with measurements of snowpack density, temperature an ram profiles, liquid water content, and rough characterization of the crystal sizes. These data compared favorably with calculated results based on recent microscopic scattering models.
The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.
It was necessary to identify the most promising measurement techniques and strategies and to understand those candidate systems in detail. The emphasis was on passive microwave remote-sensing techniques. A brief background in passive microwave and hybrid techniques for measuring precipitation, key problem areas and strategies for dealing with those problems, a precipitation measurement system, and specific recommendations are presented.
The measurements of wind speed and rain rate over a large dynamic range has been demonstrated by using passive microwave remote sensing measurements by a C-band radiometer flying above a hurricane. The measurements were obtained by using a unique variable frequency radiometer, the Stepped Frequency Microwave Radiometer (SFMR), which is capable of near simultaneous measurements at several widely spaced frequencies in a near octave bandwidth in the C-band microwave frequency region. In addition, an algorithm was developed which computes the surface wind speed and rain rate from the SFMR measured radiometric brightness temperature at two frequencies, and this algorithm was tested using experimental data collected during flights into Hurricane Allen during 1980. Results showed a reasonable agreement between the SFMR measured data and measurements obtained by weather radar.
The implementation of high resolution passive radiative remote sensing of the cloudiness volume in the atmospheric window between 10.5-12.5 microns is described. Airborne radiometers, the NASA/Cloud Top Scanner, were used to obtain radiances during several passages over two merging cumulus clouds, with the data being converted into equivalent blackbody temperatures. Data were also gathered in the 0.55-0.70 micron visible bands as part of the SESAME-79 experiment. The number of points observed in the IR channel were adjusted to account for the viewing angle and areal extents were calculated. A relationship was assumed to exist between the brightness temperatures of the cloud surface and the level of cloudiness at a given atmospheric altitude. Further measurements with lidar scans are indicated in order to reduce the error levels associated with the method.
Microwave hydrology, as the term in construed in this trilogy, deals with the investigation of important hydrological features on the Earth's surface as they are remotely, and passively, sensed by orbiting microwave receivers. Microwave wavelengths penetrate clouds, foliage, ground cover, and soil, in varying degrees, and reveal the occurrence of standing liquid water on and beneath the surface. The manifestation of liquid water appearing on or near the surface is reported by a microwave receiver as a signal with a low flux level, or, equivalently, a cold temperature. Actually, the surface of the liquid water reflects the low flux level from the cosmic background into the input terminals of the receiver. This trilogy describes and shows by microwave flux images: the hydrological features that sustain Lake Baykal as an extraordinary freshwater resource; manifestations of subsurface water in Iran; and the major water features of the Congo Basin, a rain forest.
This document addresses the task of developing and executing a plan for validating the algorithm used for initial processing of sea ice data from the Special Sensor Microwave/Imager (SSMI). The document outlines a plan for monitoring the performance of the SSMI, for validating the derived sea ice parameters, and for providing quality data products before distribution to the research community. Because of recent advances in the application of passive microwave remote sensing to snow cover on land, the validation of snow algorithms is also addressed.
For active and passive microwave remote sensing of sea ice, a correlation function of exponential form is extracted from the photograph of a horizontal thin section taken from a sample of artificially grown saline ice that closely resembled Arctic congelation sea ice. It is found that the extracted correlation lengths are consistent with the published average size of brine pockets. With the application of strong fluctuation theory and the bilocal approximation, the effective permittivity tensor is derived in the low-frequency limit for an unbounded uniaxial random medium with two-phase mixtures. Using the extracted correlation lengths, the effective permittivity tensor is computed as a function of fractional volume of brine inclusions and compared with in situ measurements at 4.8 and 9.5 GHz.
The inversion of snow parameters from passive microwave remote sensing measurements is performed with a neural network trained with a dense media multiple scattering model. A constrained iterative inversion scheme is used. Inversion of four parameters is performed from five brightness temperatures. The four parameters are: mean grain size of ice particles in snow, snow density, snow temperature, and snow depth. The five brightness temperatures are that of 19-GHz vertical polarization, 19-GHz horizontal polarization, 22-GHz vertical polarization, 37-GHz vertical polarization, and 37-GHz horizontal polarization. Based on the neural network constrained iterative inversion algorithm, synthetic mapping of the terrain is performed. The retrieval of synthetic mapping has been achieved. The incorporation of ground truth information is considered.
A balloon-borne triple-etalon Fabry-Perot Interferometer, observing the Doppler shifts of absorption lines caused by molecular oxygen and water vapor in the far red/near infrared spectrum of backscattered sunlight, has been used to evaluate a passive spaceborne remote sensing technique for measuring winds in the troposphere and stratosphere. There have been two successful high altitude balloon flights of the prototype UCL instrument from the National Scientific Balloon Facility at Palestine, TE (May 80, Oct. 83). The results from these flights have demonstrated that an interferometer with adequate resolution, stability and sensitivity can be built. The wind data are of comparable quality to those obtained from operational techniques (balloon and rocket sonde, cloud-top drift analysis, and from the gradient wind analysis of satellite radiance measurements). However, the interferometric data can provide a regular global grid, over a height range from 5 to 50 km in regions of clear air. Between the middle troposphere (5 km) and the upper stratosphere (40 to 50 km), an optimized instrument can make wind measurements over the daylit hemisphere with an accuracy of about 3 to 5 m/sec (2 sigma). It is possible to obtain full height profiles between altitudes of 5 and 50 km, with 4 km height resolution, and a spatial resolution of about 200 km, along the orbit track. Below an altitude of about 10 km, Fraunhofer lines of solar origin are possible targets of the Doppler wind analysis. Above an altitude of 50 km, the weakness of the backscattered solar spectrum (decreasing air density) is coupled with the low absorption crosssection of all atmospheric species in the spectral region up to 800 nm (where imaging photon detectors can be used), causing the along-the-track resolution (or error) to increase beyond values useful for operational purposes. Within the region of optimum performance (5 to 50 km), however, the technique is a valuable potential complement to existing wind measuring systems and can provide a low cost addition to powerful active (LIDAR) wind measuring systems now under development.
There were several tangible products that resulted from the reflector antenna research program. The initial technical effort was to develop techniques to compensate for distortions over the surface of the main reflector of a large reflector antenna system. An in-depth investigation of this problem resulted in a new technique for the electronic correction of surface errors. A journal article on the findings describe the use of the iterative sampling method. Shortly after the 'Mission to Planet Earth' program started, we began investigating the use of large reflector antennas in geostationary orbit for passive earth remote sensing. A study panel was coordinated by Virginia Tech to set technical goals for the effort. These were used to guide the design of several antennas. The original interest stemmed from an industrial (Reynolds Metals) need and currently involves work with industry (Prodelin Corporation) on high technology, low cost reflectors. The intervening years (1987 - 1993) is the period of this report and Virginia Tech's reflector antenna activity then was exclusively with NASA LaRC.
Aperture synthesis is a new technology for passive microwave remote sensing from space which has the potential to overcome the limitations set in the past by antenna size. This is an interferometric technique in which pairs of small antennas and signal processing are used to obtain the resolution of a single large antenna. The technique has been demonstrated successfully at L-band with the aircraft prototype instrument, ESTAR. Proposals have been submitted to demonstrate this technology in space (HYDROSTAR and MIRAS).
The Atmospheric Infrared Sounder (AIRS) is a key facility instrument in the NASA Earth Observing System (EOS) program, being implemented to obtain comprehensive long-term measurements of earth processes affecting global change. The instrument performs passive IR remote sensing using a high resolution grating spectrometer with a wide spectral coverage (3.7 - 15.4 m) directing radiation onto a hybrid HgCdTe IRFPA operating at 58K in a vacuum package cooled to 155K. The hybrid HgCdTe FPA consists of twelve modules, 10 with multiplexed photovoltaic detectors and two with individually leaded out photoconductive detectors. The complex FPA has a large optical footprint, 53 mm x 66 mm, and receives energy dispersed from the grating through a precision filter assembly containing 17 narrow band filters. The backside illuminated PV detector arrays are fabricated from P-on-n double layer LPE grown heterojunction detectors in a bilinear format of 50 m x 100 m detectors, with from 232 to 420 detectors per module. For the MWIR bands four PV modules cover the 3.7 m to 8.22 m region. Low detector capacitance and low noise preamplifiers in the ROIC are key to achieving high sensitivities in these bands. Uniform quantum efficiencies and detectivities exceeding 3E13 cm-rtHz/W have been achieved. The LWIR region is covered by six PV modules spanning 8.8 m to 13.75 m. High detector resistance and very low ROIC preamplifier input noise are key to achieving high sensitivity. A detectivity exceeding 2E11 cm-rtHz/W has been achieved at the longest wavelength. Two additional PC modules cover the longest spectral bands out to 15.4 m. This high performance multispectral focal plane has been built and integrated with the dewar assembly, and is currently being integrated with the complete AIRS sensor.
Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.
The objective of this project is to understand the current and future impacts and feedbacks of seasonally frozen ground on the regional and global climate system and the ecosystem as a whole. More specifically, we proposed to: investigate the dynamics of the seasonally freezing and thawing processes and their relations to current climatic conditions through in situ data analysis and numerical modeling; develop a comprehensive algorithm to detect surface soil freeze/thaw status for snow-free land surface using passive microwave remote sensing data and for snow-covered land surface using numerical modeling, and validate the algorithm and numerical model using available ground-based measurements; investigate seasonal and inter-annual variations of frozen soils in the GAPP regions using data generated from the new validated algorithm and their relations to the environmental factors such as air temperature, snow cover, surface morphology, soil type and soil moisture; generate a frozen soil data set which describes the timing, duration, thickness, and area extent of seasonally frozen ground for the period from 1978 to present. The proposed research will be accomplished through data analysis, remote sensing, and numerical modeling.