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At least 955 records · Page 53

Detection of land degradation with polarimetric SAR

Multispectral radar polarimeter data were collected over the Manix Basin Area of the Mojave desert using an airborne SAR. An analysis of the data reveals unusual polarization responses which are attributed to the formation of wind ripples on the surfaces of fields that have been abandoned for more than 5 years. This hypothesis has been confirmed through field observations, and a second-order perturbation model is shown to effectively model the polarization responses. The results demonstrate the usefulness of remote sensing techniques for the study of land degradation at synoptic scales.

Ray, Terrill W.↗

Calibration Of NASA/JPL DC-8 SAR Data

Report describes recent improvements in calibration of data gathered by polarimetric synthetic-aperture-radar (SAR) system operated by NASA's Jet Propulsion Laboratory. Improvements are: relocation of calibration site; JPL POLCAL software; and ANTENCAL software. Presents analysis of calibration performance over number of sites during years 1989 and 1990.

Freeman, Anthony↗

Algorithms For Segmentation Of Complex-Amplitude SAR Data

Several algorithms implement improved method of segmenting highly speckled, high-resolution, complex-amplitude synthetic-aperture-radar (SAR) digitized images into regions, within each backscattering characteristics similar or homogeneous from place to place. Method provides for approximate, deterministic solution by two alternative algorithms almost always converging to local minimums: one, Iterative Conditional Modes (ICM) algorithm, which locally maximizes posterior probability density of region labels; other, Maximum Posterior Marginal (MPM) algorithm, which maximizes posterior marginal density of region labels at each pixel location. ICM algorithm optimizes reconstruction of underlying scene. MPM algorithm minimizes expected number of misclassified pixels, possibly better in remote sensing of natural scenes.

Rignot, Eric J. M.↗

SAR data processing adaptation for Magellan Cycle II

The authors describe the effort made at the Magellan SAR Data Processing Facility in adapting existing data processors to handle data collected from various imaging experiments. The different data processing requirements imposed by the various types of data are discussed, the tradeoffs and compromises made to work within the constraint of the existing systems are explained, and summary processing results obtained to date are given.

Leung, K.↗

Robustness of Spann-Wilson segmentation on SAR imagery

The performances of the Spann-Wilson algorithm on simulated synthetic aperture radar (SAR) images with varying degrees of speckle (one to four looks and varying amounts of white noise) is described. One hundred forty-eight test images are considered, of which the algorithm segmented most without any adjustment to the algorithm's parameters. The effect of speckle on fractal boundaries is studied. The effect of varying multiplicative and additive noise distributions for a fixed set of segmentation parameters is examined. The modified Spann-Wilson algorithm on four-look imagery is evaluated.

Daida, Jason M.↗

Measurement of pressure ridges in SAR images of sea ice - Preliminary results on scattering theory

Sea ice ridges and keels (hummocks and bummocks) are important in sea ice research for both scientific and practical reasons. A long-term objective is to make quantitative measurements of sea ice ridges using synthetic aperture radar (SAR) images. The preliminary results of a scattering model for sea ice ridge are reported. The approach is through the ridge height variance spectrum Psi(K), where K is the spatial wavenumber, and the two-scale scattering model. The height spectrum model is constructed to mimic height statistics observed with an airborne optical laser. The spectrum model is used to drive a two-scale scattering model. Model results for ridges observed at C- and X-band yield normalized radar cross sections that are 10 to 15 dB larger than the observed cross sections of multiyear ice over the range of angles of incidence from 10 to 70 deg.

Vesecky, J. F.↗

Modeling of SAR returns from a red pine stand

Bright P-band radar returns from red pine forests have been observed on synthetic aperture radar (SAR) images in Bangor, Maine. A plot of red pine trees was selected for the characterization and modeling to understand the cause of the high P-band returns. The red pine stand under study consisted of mature trees. Diameter at breast height (DBH) measurements were made to determine stand density as a function of tree diameter. Soil moisture and bulk density measurements were taken along with ground rough surface profiles. Detailed biomass measurements of the needles, shoots, branches, and trunks were also taken. These site statistics have been used in a distorted Born approximation model of the forest. Computations indicate that the direct-reflected or the double-bounce contributions from the ground are responsible for the high observed P-band returns for HH polarization.

Lang, R. H.↗

Estimation of bare soil evaporation using multifrequency airborne SAR

It is shown that for homogeneous areas soil moisture can be derived from synthetic aperture radar (SAR) measurements, so that the use of microwave remote sensing can given realistic estimates of energy fluxes if coupled to a simple two-layer model repesenting the soil. The model simulates volumetric water content (Wg) using classical meterological data, provided that some of the soil thermal and hydraulic properties are known. Only four parameters are necessary: mean water content, thermal conductivity and diffusitivity, and soil resistance to evaporation. They may be derived if a minimal number of measured values of Wg and surface layer temperature (Tg) are available together with independent measurements of energy flux to compare with the estimated values. The estimated evaporation is shown to be realistic and in good agreement with drying stage theory in which the transfer of water in the soil is in vapor form.

Soares, Joao V.↗

A new clustering algorithm applicable to multispectral and polarimetric SAR images

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

Wong, Yiu-Fai↗

Software For Calibration Of Polarimetric SAR Data

POLCAL (Polarimetric Radar Calibration) software tool intended to assist in calibration of synthetic-aperture radar (SAR) systems. In particular, calibrates Stokes-matrix-format data produced as standard product by NASA/Jet Propulsion Laboratory (JPL) airborne imaging synthetic aperture radar (AIRSAR). Version 4.0 of POLCAL is upgrade of version 2.0. New options include automatic absolute calibration of 89/90 data, distributed-target analysis, calibration of nearby scenes with corner reflectors, altitude or roll-angle corrections, and calibration of errors introduced by known topography. Reduces crosstalk and corrects phase calibration without use of ground calibration equipment. Written in FORTRAN 77.

Van Zyl, Jakob↗

Software For Analysis Of SAR Data

MacSigmaO is interactive program for Macintosh computer enabling user to display and make computations from data collected by JPL AIR-SAR, ERS-1, JERS-1, and Magellan radar systems. Provides four basic functions: synthesis of images (if necessary), statistical analysis of selected areas, analysis of corner reflectors as calibration measure (if appropriate and possible), and informative mouse tracking. Written in C for use on Macintosh series of computers.

Norikane, Lynne↗

SAR Processing Based On Two-Dimensional Transfer Function

Exact transfer function, ETF, is two-dimensional transfer function that constitutes basis of improved frequency-domain-convolution algorithm for processing synthetic-aperture-radar, SAR data. ETF incorporates terms that account for Doppler effect of motion of radar relative to scanned ground area and for antenna squint angle. Algorithm based on ETF outperforms others.

Chang, Chi-Yung↗

Sea ice radar signatures from ERS-1 SAR during late Summer and Fall in the Beaufort and Chukchi Seas

A study which examines ERS-1 C band SAR (Synthetic Aperture Radar) imagery of sea ice obtained in the Beaufort and Chukchi Seas from mid Summer through Fall freeze up and early Winter in 1991 is presented. Radar backscatter statistics of sea ice were obtained from the imagery, using common floes tracked through consecutive repeat images whenever possible. During the Summer months, strong fluctuations in ice signatures of several dB are observed over 2 to 3 day periods, which are found to be closely related to air temperature excursions above and below freezing that alters the phase of the ice surface. As air temperatures drop steadily below freezing in the Fall, the signatures of the pack ice increase in brightness and become more stable with time. Multiyear ice is distinguished from rough and smooth first year ice. There are also variations in the multiyear signatures with latitude. Large variations are seen in new ice and open water contained within leads which results in ambiguous classification.

Holt, Benjamin↗

A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary constraints for this particular problem are that the method must be reasonably robust and fast. Unlike most geological features, the small volcanoes of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include (1) a circular planimetric outline, (2) known diameter frequency distribution from preliminary studies, (3) a limited number of basic morphological shapes, and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Burl, M. C.↗

SAR sensor electronics: T/R modules

A discussion concerning the architecture of transmit/receive (T/R) modules in synthetic aperture radar (SAR) systems is presented. Module requirements are discussed in the context of the following: requirements traceability; antenna configuration; and typical module specifications/requirements. Finally, module technology development in the L-, C-, and X-bands is discussed.

Hasan, Mohd A.↗

Advanced antennas for SAR spacecraft

Single and multi-frequency antenna concepts were developed to evaluate the feasibility of building large aperture polarimetric synthetic aperture radar (SAR) systems to be launched in low cost vehicles such as the Delta 2. The antennas are 18.9 m long by 2.6 m wide (L-band) and achieve single polarization imaging to an incidence angle of 55 degrees and dual/quad imaging to 42 degrees. When combined with strawman spacecraft designs, both concepts meet the mass and volume constraints imposed by a Delta 2 launch.

Gail, William B.↗

A snow wetness retrieval algorithm for SAR

The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

Shi, Jian-Cheng↗