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Paper presents statistical approach to analysis of texture in synthetic-aperture-radar (SAR) images. Objective: to extract intrinsic spatial variability of distributed target from overall spatial variability of SAR image.
Imaging radar is an important contributing source of information for a range of geological problems and environments. Airborne SAR and ERS-1 data integrated with other geoscience datasets are being used in an attempt to characterize the crustal fracturing associated with the Sudbury structure. This presentation highlights examples of integrated and composite images aimed at facilitating the interpretation of the Sudbury structure. This work is the result of an ongoing cooperative multidisciplinary SAR study of the basin carried out by the Canada Center for Remote Sensing, Ontario's provincial Remote Sensing Office, the Ontario Geological Survey, and the Geological Survey of Canada.
The Shuttle Imaging Radar-C (SIR-C) is the third in a series of space shuttle based synthetic aperture radars (SAR) sponsored by the National Aeronautics and Space Administration (NASA). The SIR-C ground data processing system is to process the playbacked SAR signal data into a variety of data products for distribution to the science community. An overview of the end-to-end ground data processing system with emphasis on the unique characteristics involved in the system design is presented. Included in the discussion are science requirements, radar system specifications, input data format specifications, system operations design, data products design, processing algorithm design, hardware architecture design, and software design.
The Surface Wave Dynamics Experiment (SWADE) has gathered SAR observations of the Gulf Stream that show a change in ocean surface brightness; this may be due to the effects of a change in air-sea temperature difference across the observed edge, where the boundary is defined by warm, quickly flowing Gulf Stream water and cooler, relatively stationary shelf water. The two images discussed indicate the possibility of deepening understanding of Gulf Stream front dynamics by using the abundant spatial data of SAR imagery, in conjunction with more conventional (point-like) data on hydrography and currents.
A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarimetric backscatter characteristics is presented. Classes of polarimetric backscatter are selected on the basis of a multidimensional fuzzy clustering of the logarithm of the parameters composing the polarimetric covariance matrix. The clustering procedure uses both polarimetric amplitude and phase information, is adapted to the presence of image speckle, and does not require an arbitrary weighting of the different polarimetric channels; it also provides a partitioning of each data sample used for clustering into multiple clusters. Given the classes of polarimetric backscatter, the entire image is classified using a maximum a posteriori polarimetric classifier. Four-look polarimetric SAR complex data of lava flows and of sea ice acquired by the NASA/JPL airborne polarimetric radar (AIRSAR) are segmented using this technique. The results are discussed and compared with those obtained using supervised techniques.
A set of multidate, multilook angle polarimetric SAR data, acquired in Pennsylvania during July 1990 was recorded to determine the effect of local incidence angle. Cosine-based and polynomial models are found to be equally good for correcting SAR data for local incidence angle effects. A modified approach, considering the correction factor as additive rather than multiplicative, gave better results. The standard error in the estimation of soil moisture improves from 8.1 to 5.8 after applying corrections to incidence angle effects.
Terrain height variations in mountainous areas cause problems in radiometric corrections of synthetic aperture radar (SAR) images. To determine the elevation angle and the height at the different parts of an image, an application of the monopulse principle is proposed. From the ratios of images radiometrically modulated by the difference and sum antenna pattern in range it is possible to calculate the appropriate elevation angle at any point in the image. Design considerations for a corresponding airborne SAR-system are presented, and some estimates of error influences (e.g., ambiguities), expected performance and precision in topographic mapping are given.
A study of algorithm development and testing for soil moisture retrieval for bare fields using L-band synthetic aperture radar (SAR) imagery is reported. First-order surface scattering models predict that the copolarization ratio is sensitive to soil moisture but not to surface roughness. All possible ratios of the co-polarization signals and their linear combinations are evaluated. The best sensitivity to soil moisture is achieved from measurements as predicted by the first-order surface scattering model. The effects of system noise and volume scattering of soil are evaluated. To minimize the effect of the volume scattering, an algorithm which includes both the surface and volume scattering has been developed and tested using Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) data. The results show that the estimation of soil moisture can be improved after removing the system noise and including the volume scattering effect at large incidence angles.
Preliminary results from an analysis of the multitemporal radar backscatter signatures of tree species acquired by European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data are presented. Significant changes in radar backscatter are detected. Correlation of these differences with ground truth observations indicate that these are due to changes in soil and liquid water content as a result of freeze/thaw events. C-band observations acquired by the NASA/Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) instrument demonstrate the potential of a C-band radar instrument to monitor drought/flood events. The potential of ERS-1 for monitoring phenologic changes in the forest and for classifying tree species is less promising.
An ice motion tracker has been implemented as part of the Ice/Ocean Geophysical Processor System (GPS) at the Alaska Synthetic Aperture Radar (SAR) Facility. The motion tracker operates in an unsupervised mode and utilizes a combination of feature-based and area-based matching to construct the displacement field from time-separated SAR imagery. The tracker is used to generate routine motion products for investigations of the kinematics and dynamics of sea ice in the polar regions. A number of filters for elimination of outliers and incorrect matches have been implemented to maintain the quality of the motion vector product. Preliminary evaluation of the tracking algorithm with European Space Agency Remote Sensing Satellite (ERS-1) data indicate that these requirements are satisfied. The performance and shortcomings of the motion tracker are discussed.
Synthetic aperture radar (SAR) focusing can be achieved either based on accurate ephemeris data or on an autofocusing process. For the Magellan project, such a decision must be made in the early phase of Magellan SAR system design. The analysis of the emphemeris requirement is complicated. The analysis given by the author leads to the conclusion that empheris data obtained from the Magellan navigation system provide sufficient accuracy to meet the Magellan image resolution requirement.
The results of a calibration analysis performed on ERS-1 synthetic aperture radar (SAR) images produced by the Alaska SAR facility (ASF) are presented, together with some preliminary results on change detection on the Alaskan north slope derived from the same images. Image quality, geometric and radiometric fidelity, and repeat pass radiometric stability have all been determined to be satisfactory. A calibration workstation has been designed and implemented for use in operational data quality analysis of ASF data products. Higher-level data analysis programs have been developed for interferometry, texture analysis, and change detection.
In order to study mechanisms of scattering and their relative contributions to synthetic aperture radar (SAR) and inverse SAR images, a special measurement facility has been constructed. It can be used to generate images in which the target is illuminated from a constant direction as the receiver is rotated in azimuth, and the target is illuminated from various directions as the receiver is rotated in azimuth. The imaging system performance is discussed, and images obtained using both approaches are compared, for a variety of simple targets and statistically known randomly rough surfaces.
The MACHYDRO-90 was a multi-sensor aircraft campaign conducted to study drainage basin hydrology and the role of soil moisture in defining hydrologic characteristics and patterns. The results from the synthetic aperture radar (SAR) are presented. Data were collected over a period in which the soil conditions changed from dry to wet and then through a drying period which was close to ideal. Radar backscatter data are compared to detailed soil moisture samples taken to define soil moisture gradients within a watershed. The analysis also includes 40-MHz bandwidth SAR data, which provide very high spatial resolution. It is shown these data can be interpreted for hydrology and their application to hydrologic modeling is discussed.
Improved method of determining radiation pattern of synthetic-aperture radar (SAR) antenna with respect to elevation-angle coordinate (angle of roll about flight path) devised. Essence of method is solving radar equation in such way as to enable extraction of antenna pattern from SAR images of uniform distributed targets. Needed because radiation pattern in flight can differ from that observed in laboratory test of antenna. Computations include subtraction of noise, test for uniformity, and least-squares estimate.
Report summarizes development of airborne interferometric synthetic-aperture-radar system (SAR) for topographic mapping. Basic principle of topographic mapping by use of interferometric SAR and performance of earlier version of system described in "Topographical Mapping With Synthetic-Aperture Radar" (NPO-16665).
Method of unsupervised segmentation of polarimetric synthetic-aperture-radar (SAR) image data into classes involves selection of classes on basis of multidimensional fuzzy clustering of logarithms of parameters of polarimetric covariance matrix. Data in each class represent parts of image wherein polarimetric SAR backscattering characteristics of terrain regarded as homogeneous. Desirable to have each class represent type of terrain, sea ice, or ocean surface distinguishable from other types via backscattering characteristics. Unsupervised classification does not require training areas, is nearly automated computerized process, and provides nonsubjective selection of image classes naturally well separated by radar.
Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.