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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 37 records · Page 2
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NASA NTRS1991

Diurnal changes in the dielectric properties and water status of eastern hemlock and red spruce from Howland, ME

The diurnal characteristics of microwave dielectric properties and water potential of two conifer species were investigated in July and September, 1990. P-band and C-band radial dielectric profiles of hemlock and red spruce, as well as hemlock diurnal water potential and dielectric profiles, are presented. The resulting radial dielectric profiles matched the regions of the functional sapwood (water transport component of the active xylem) in both species such that the sapwood was characterized by a higher dielectric than the bark and heartwood tissues. This is probably due to characteristic differences in the water content of each tissue. As the hemlocks progressed through their diurnal water potential pattern, the dielectric profile remained static until mid-afternoon. As the tension in the water column relaxed (2 to 3 bars) the dielectric constant decreased by 30 to 40 percent. There are several possible explanations for this phenomenon, and these may relate to the dependency of the dielectric measurements on temperature, salinity, and volumetric water content.

Salas, W. A.↗
NASA NTRS1992

On the application of multifrequency polarimetric radar observations for sea-ice classification

The use of multifrequency polarimetric radar imagery to enhance the ability to separate different sea-ice types using single-frequency, single-polarization synthetic aperture radar (SAR) data is investigated. Backscatter characteristics of six radiometrically and polarimetrically distinct sea-ice types are selected in an unsupervised range-dependent analysis of multifrequency polarimetric SAR data using the maximum a posteriori (MAP) polarimetric classifier. Maximum ice discrimination is achieved with combined C- and L-band full polarimetry, and collocated passive microwave imagery suggests greater than 90 percent classification accuracy. C-band VV-pol alone achieves only 68 percent relative accuracy because it confuses multiyear and rough compressed first year ice. L-band, relative classification accuracy is 75 percent, 83 percent, and 85 percent, using HH-pol, HH- and VV-combined, or the full polarimetry, respectively. P-band is less accurate. Combinations of two frequencies at a single polarization show the greatest improvement over a single channel.

Rignot, Eric↗
NASA NTRS1993

Application of Cloude's target decomposition theorem to polarimetric imaging radar data

In this paper we applied Cloude's decomposition to imaging radar polarimetry. We show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multifrequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a frosted area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. However, the scattering for the forested area is still dominated by scattering from randomly oriented cylinders. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominates in this case.

Vanzyl, Jakob J.↗
NASA NTRS1993

Multifrequency observations

Analyses of synthetic aperture radar (SAR) image data were performed at DLR to classify various kinds of vegetation and different terrain types. The data were collected both with the DLR experimental synthetic aperture radar (E-SAR) in X-band, C-band, and L-band and with the NASA/JPL DC-8 SAR in C-band, L-band, and P-band. E-SAR is a single frequency and single polarization system (both parameters can be selected) but several flights were used to collect multifrequency/multipolarization data which were geometrically matched after processing. Classification of different crop types was based on comparison of the backscatter coefficients of calibrated SAR data in different frequency bands and polarizations. The DC-8 STAR collects polarimetric data in different bands simultaneously. Data acquired with the NASA/JPL DC-8 STAR are qualified for scientific investigations by reducing the cross-talk and channel imbalance to a tolerable extent. The data are absolutely calibrated by using reference targets with known backscattering cross-sections. The signatures and polarimetric features of terrain types, such as grassland, concrete, sea, forest (coniferous; deciduous) and urban areas, are extracted and discussed with respect to frequency and incidence angle dependence. A multifrequency polarimetric feature vector was applied for classification. The results of this new approach for separating and classifying different object classes are presented.

Glitz, R.↗
NASA NTRS1992

Preliminary results of polarization signatures for glacial moraines in the Mono Basin, Eastern Sierra Nevada

The valleys of the Mono Basin contain several sets of lateral and terminal moraines representing multiple stages of glaciation. The semi-arid climate with slow weathering rates preserved sequences of nested younger moraines within older ones. There is a well established relative chronology and recently exposure dating provided a new set of numerical dates. The moraines span the late Wisconsin (11-25 ka) to the Illinoian (130-190 ka) glaciations. The Mono Basin area was used as a 'calibration site' to establish remote dating techniques for eventual transfer to the more inaccessible but geomorphically and climatically similar moraines of the South American Andes Mountains. Planned polarimetric synthetic aperture radar (SAR) imagery acquired by JPL AIRSAR (South American Campaign) and SIR-C (Andes super-site) are analyzed to establish chronologies of previously undated moraine sequences in a study of Pleistocene climatic change in the Southern Hemisphere. The dry climate and sparse vegetation is also favorable for correlation of ground surface roughness with radar polarization signature. The slow weathering processes acting over thousands of years reduce the size, frequency, and angularity of surface boulders while increasing soil development on the moraines. Field observations based on this hypothesis result in relative ages consistent with those inferred from nested position within the valley. Younger moraines, therefore, will appear rougher than the older smoother moraines at scales measurable at AIRSAR wavelengths. Previously documented effects of ground surface roughness on polarization signatures suggest that analysis of moraine polarization signatures can be useful for relative dating. The technique may be extended to predict numerical ages. The data set reported were acquired on 8 Sep. 1989 with the JPL Airborne SAR (AIRSAR) collecting polarimetric imagery at C- (5.6 cm), L- (24 cm), and P-band (68 cm) with a flight-line parallel to the strike of the mountains. Phase calibration was performed on the analyzed scene by setting the co-phase of a smooth lake to zero as described. Absolute amplitude calibration was not possible because corner reflectors were not deployed.

Forster, Richard R.↗
NASA NTRS1992

Extraction of quantitative surface characteristics from AIRSAR data for Death Valley, California

Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were collected for the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley, California, USA, in Sep. 1989. AIRSAR is a four-look, quad-polarization, three frequency instrument. It collects measurements at C-band (5.66 cm), L-band (23.98 cm), and P-band (68.13 cm), and has a GIFOV of 10 meters and a swath width of 12 kilometers. Because the radar measures at three wavelengths, different scales of surface roughness are measured. Also, dielectric constants can be calculated from the data. The AIRSAR data were calibrated using in-scene trihedral corner reflectors to remove cross-talk; and to calibrate the phase, amplitude, and co-channel gain imbalance. The calibration allows for the extraction of accurate values of rms surface roughness, dielectric constants, sigma(sub 0) backscatter, and polarization information. The radar data sets allow quantitative characterization of small scale surface structure of geologic units, providing information about the physical and chemical processes that control the surface morphology. Combining the quantitative information extracted from the radar data with other remotely sensed data sets allows discrimination, identification and mapping of geologic units that may be difficult to discern using conventional techniques.

Kierein-Young, K. S.↗
NASA NTRS1992

Fitting a three-component scattering model to polarimetric SAR data

A new technique for fitting a three-component scattering mechanism model to the polarimetric synthetic aperture radar (SAR) data itself, without utilizing any ground truth measurements, is presented. The three scattering mechanism components included in the model are volume scatter from randomly oriented dipoles, first-order Bragg surface scatter and a dihedral scattering mechanism for two surfaces with different dielectric constants. The model fit yields an estimate of the contribution to the total backscatter of each of the three components. The backscatter contributions can also be compared to give the relative percentage weight of each. The model fit has an equal number of input parameters (the polarimetric radar backscatter measurements) and output parameters (the backscatter parameters describing them). The model can be applied to entire images or to small areas within an image to give a first-order estimate of the relevant scattering mechanisms. The model was applied to many C-, L- and P-band Airborne SAR (AIRSAR) images of different types of terrain. Results were presented at the workshop.

Freeman, A.↗
NASA NTRS1992

Processing of polarimetric SAR data for soil moisture estimation over Mahantango watershed area

Microwave remote sensing technique has a high potential for measuring soil moisture due to the large contrast in dielectric constant of dry and wet soils. Recent work by Pults et al. demonstrated the use of X/C-band data for quantitative surface soil moisture extraction from Airborne Synthetic Aperture Radar (SAR) system. Similar technique was adopted using polarimetric SAR data acquired with the JPL-AIRSAR system over the Mahantango watershed area in central Pennsylvania during July 1990. The data sets reported include C-, L-, and P-bands of 10, 13, 15, and 17 July 1990.

Rao, K. S.↗
NASA NTRS1993

Classification of simple vegetation types using POLSAR image data

Mapping basic vegetation or land cover types is a fairly common problem in remote sensing. Knowledge of the land cover type is a key input to algorithms which estimate geophysical parameters, such as soil moisture, surface roughness, leaf area index or biomass from remotely sensed data. In an earlier paper, an algorithm for fitting a simple three-component scattering model to POLSAR data was presented. The algorithm yielded estimates for surface scatter, double-bounce scatter and volume scatter for each pixel in a POLSAR image data set. In this paper, we show how the relative levels of each of the three components can be used as inputs to simple classifier for vegetation type. Vegetation classes include no vegetation cover (e.g. bare soil or desert), low vegetation cover (e.g. grassland), moderate vegetation cover (e.g. fully developed crops), forest and urban areas. Implementation of the approach requires estimates for the three components from all three frequencies available using the NASA/JPL AIRSAR, i.e. C-, L- and P-bands. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration.

Freeman, A.↗
NASA NTRS1993

Application of Cloude's target decomposition theorem to polarimetric imaging radar data

We apply Cloude's decomposition to imaging radar polarimetry. We derive the general expressions for the eigenvalues and eigenvectors for the case of terrain with reflection symmetry, and show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multi-frequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a forested area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. The scattering for the forested area is still dominated by scattering from randomly oriented cylinders, however. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominate in this case.

Vanzyl, Jakob J.↗
NASA NTRS1993

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

Wang, L.↗
NASA NTRS1990

River and lake ice conditions as determined from AIRSAR imagery

Synthetic aperture radar (SAR) imagery data can provide information on types and distribution of river and lake ice needed for studying river ice processes and dynamics, monitoring ice during winter navigation, and formulating ice control strategies. Visible and IR remote sensing systems cannot provide such data and present field methods are inadequate for characterizing ice conditions over long river reaches. Our ongoing analysis of JPL's AIRSAR imagery data and concurrent ground truth of ice conditions on the Tanana River and surrounding lakes near Fairbanks, Alaska, in March 1988, has resulted in several findings: hummocked ice covers and zones of variable ice surface roughness within them can be differentiated; C- and L-band data are more sensitive than P-band to the range of surface roughnesses encountered; smooth, level ice that is clear or contains small bubbles produces little backscatter; snow-covered river ice, whether rough or smooth, is distinguishable from snow-covered river sediments on exposed river beds and unvegetated bars; and open water leads are readily distinguished.

Melloh, Rae A.↗
NASA NTRS1990

Preliminary results from the MAESTRO 1 Campaign over the Black Forest

The Joint Research Center (JRC) Ispra and the European Space Agency (ESA) have co-sponsored the deployment of the National Aeronautics and Space Agency (NASA) and Jet Propulsion Laboratory (JPL), C-, L-, and P-band polarimetric synthetic aperture radar (SAR) in Europe in mid-August 1989. This deployment represents the first opportunity for European agencies and institutes to evaluate the current state of the art of multifrequency polarimetric imaging technology over European Test Sites. Of particular interest to the Joint Research Center (JRC) Ispra is the Black Forest Test Site at Freiburg in the Federal Republic of Germany. This Test Site incorporates the Villingen region of the Black Forest to the south-west of Germany. This paper reports upon the activities undertaken in preparation for the MAESTRO 1 Campaign in the Black Forest Test Site. In particular this paper reports upon the ground data collection campaign for the Freiburg Test Site where extensive and intensive ground data measurements were undertaken. These measurements were based upon standard ground data collection protocols developed for forestry by the JRC and utilized throughout Europe for the MAESTRO 1 Campaign. The paper then goes on to present preliminary results derived from the SAR data using the JRC-developed software for polarimetric data interpretation, POLTOOL.

Churchill, P. N.↗
NASA NTRS1993

Forest investigations by polarimetric AIRSAR data in the Harz mountains

The Harz Mountains in the North of Germany have been a study site for several remote sensing investigations since 1985, as the mountainous area is one of the forest regions in Germany heavily affected by forest decline, especially in the high altitudes above 800 m. In a research program at the University of Berlin, methods are developed for improving remote sensing assessment of forest structure and forest state by additional GIS information, using several datasets for establishing a forest information system. The Harz has been defined as a test site for the SIR-C/X-SAR mission which is going to deliver multifrequency and multipolarizational SAR data from orbit. In a pilot project let by DLR-DFD, these data are to be investigated for forestry and ecology purposes. In preparing a flight campaign to the SIR-C / X-SAR mission, 'MAC EUROPE 1991', performed by NASA/JPL, an area of about 12 km in the Northern Harz was covered with multipolarizational AIRSAR data in the C-, L- and P-band, including the Brocken, the highest mountain of the Harz, with an altitude of 1142 m. The multiparameter AIRSAR data are investigated for their information content on the forest state, regarding the following questions: (1) information on forest stand parameters like forest types, age classes and crown density, especially for the separation of deciduous and coniferous forest; (2) information on the storm damages (since 1972) and the status of regeneration; (3) information on the status of forest destruction because of forest decline; and (4) influence of topography, local incidence angle and soil moisture on the SAR data. Within the project various methods and tools have been developed for the investigation of multipolarimetric radar backscatter responses and for discrimination purposes, in order to use the multipolarization information of the compressed Stokes matrix delivered by JPL.

Keil, M.↗
NASA NTRS1993

Comparison of inversion models using AIRSAR data for Death Valley, California

Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were collected for the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley, California, USA, in September 1989. AIRSAR is a four-look, quid-polarizaiton, three frequency instrument. It collects measurements at C-band (5.66 cm), L-band (23.98 cm), and P-band (68.13 cm), and has a GIFOV of 10 meters and a swath width of 12 kilometers. Because the radar measures at three wavelengths, different scales of surface roughness are measured. Also, dielectric constants can be calculated from the data. The scene used in this study is in Death Valley, California and is located over Trail Canyon alluvial fan, the valley floor, and Artists Drive alluvial fan. The fans are very different in mineralogic makeup, size, and surface roughness. Trail Canyon fan is located on the west side of the valley at the base of the Panamint Range and is a large fan with older areas of desert pavement and younger active channels. The source for the material on southern part of the fan is mostly quartzites and there is an area of carbonate source on the northern part of the fan. Artists Drive fan is located at the base of the Black Mountains on the east side of the valley and is a smaller, young fan with its source mostly from volcanic rocks. The valley floor contains playa and salt deposits that range from smooth to Devil's Golf course type salt pinnacles.

Kierein-Young, Kathryn S.↗
NASA NTRS1993

Soil moisture retrieval in the Oberpfaffenhofen testsite using MAC Europe AIRSAR data

Soil moisture content is an important parameter in many disciplines of science like hydrology, meteorology, agriculture and others. Microwave remote sensing technique has a high potential in measuring the dielectric constant of soils, which is strongly governed by the soil moisture. Much excellent work has been done on investigating the relationship between backscattering coefficient and soil moisture. Most of these studies are measured in a laboratory or are carried out with a multitemporal data set. This means, that the variation in the backscattering coefficient is only related to the soil moisture because all other parameters influencing the backscattering like surface roughness, vegetation cover, plant geometry, phenology of plants and row direction are kept constant. In this study the sensitivity of the backscattering coefficient to soil moisture of corn fields is investigated. In the framework of the MAC-Europe Campaign in June 1991, the NASA/JPL three-frequency polarimetric AIRSAR system collected data over the test site Oberpfaffenhofen. The AIRSAR campaign in Oberpfaffenhofen was complemented with intensive ground truth measurements. The sampled corn fields are nearly in the range of the same incidence angle (approximately 20 deg) and belong to different soil types. The evaluation was carried out at a single data set. The results show that the backscattering, measured at P-band, can be described with only two parameters very well. The main parameter influencing the backscattering is the soil moisture content; the second subordinated parameter is the row direction.

Wever, Tobias↗
NASA NTRS1993

(abstract) Sensitivity to Forest Biomass Based on Analysis of Scattering Mechanism

The estimation of forest biomass on a global scale is an important input to global climate and carbon cycle models. Remote sensing using synthetic aperture radar offers a means to obtain such a data set. Although it has been clear for some time that radar signals penetrate forest canopies, only recently has it been demonstrated that these signals are indeed sensitive to biomass. Inasmuch as the majority of a forest's biomass is in the trunks, it is important that the radar is sensing the trunk biomass as opposed to the branch or leaf biomass. In this study we use polarimetric AIRSAR P- and L-band data from a variety of forests to determine if the radar penetrates to the trunk by examining the scattering mechanism as determined using van Zyl's scattering interaction model, and the levels at which saturation occurs with respect to sensitivity of radar backscatter to total biomass. In particular, the added sensitivity of P-band relative to L-band is addressed. Results using data from the Duke Forest in North Carolina, the Bonanza Creek Experimental Forest in Alaska, Shasta Forest in California, the Black Forest in Germany, the temporate/boreal transition forests in northern Michigan, and coastal forests along the Oregon Transect will be presented.

forest canopy biomass radar scattering mechanism↗