The use of polarimetric and interferometric SAR data in floodplain mapping
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C-, L-, and P-band polarimetric signatures of wet snow surfaces have been analyzed, based on airborne synthetic aperture radar (AIRSAR) surveys of an Alpine test site. The importance of surface roughness is evident in the C- and L-band signatures, whereas the diffuse scattering contribution by internal inhomogeneities in the snowpack increases from the C- to the P-band at incidence angles below 50 deg due to increasing penetration.
In this paper a fuzzy classification procedure is applied to polarimetric radar measurements, and street pixels are detected. These data are successively grouped into consistent roads by means of a dynamic programming approach based on the fuzzy membership function values. Further fusion of the 2D road network extracted and 3D TOPSAR measurements provides a powerful way to analyze urban infrastructures.
It is necessary to calibrate SAR data in order to use the data for science applications. When both polarimetric and interferometric data are collected simultaneously, these SAR data can be used for cross-calibration and verification.
A fine resolution polarimetric FM SAR was developed for optimization of polarimetric SARs and interpretation of SAR data via controlled experiments with surface-base sensors. The system is designed for collecting polarimetric data at 5.3 and 10 GHz over incidence angles from 0 to 60 deg. Features of the system include broad bandwidth to obtain fine range resolution, phase stabilization and linearization loop circuitry, and digital signal processing capability. The system is used in a research program to collect polarimetric backscatter data from artificial sea ice research and design trade-offs, laboratory and field evaluation, as well as results from experiments on artificial sea ice are presented.
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SAR interferometry has enabled two important science applications: surface change detection and topographic mapping.
We investigate how multifrequency and polarimetric synthetic aperture radar (SAR) imagery enhances present capability to discriminate different ice conditions in single-frequency, single-polarization satellite SAR data. Frequencies considered are C- (lambda = 5.6cm), L- (lambda = 24cm) and P- (lambda = 68cm) band. Radar backscatter characteristics of six radiometrically and polarimetrically distinct ice types are selected from a cluster analysis of the multifrequency polarimetric SAR data and used to classify SAR images. Validation of these ice conditions is based on information provided by aerial photos, weather and ice surface measurements acquired at an ice camp, together with airborne passive microwave imagery, and visual analysis of the SAR data. The six identified sea-ice types are: (1) multiyear sea-ice; (2) compressed first year ice; (3) first year rubble and ridges; (4) first year rough ice; (5) first year smooth ice; and (6) thin ice. Open water is absent in all analyzed data. Classification of the SAR imagery into those six ice types is performed using a Bayesian Maximum A Posteriori classifier. Two complete scenes acquired at different dates in different locations are classified. The scenes were chosen such that they are representative of typical ice conditions in the Beaufort Sea in March 1988 and because ancillary information is available for validating the segmentation of various ice surface conditions.
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In 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1 hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform Lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community.
A statistical approach to the analysis of spatial statistics in polarimetric multifrequency SAR data, which is aimed at extracting the intrinsic variability of the target by removing variability from other sources, is presented. An image model, which takes into account three sources of spatial variability, namely, image speckle, system noise, and the intrinsic spatial variability of the target or texture, is described. It is shown that the presence of texture increases the image variance-to-mean square ratio and introduces deviations of the image autocovariance function from the expected SAR system response. The approach is exemplified by sea-ice SAR imagery acquired by the Jet Propulsion Laboratory three-frequency polarimetric airborne SAR. Data obtained indicate that, for different sea-ice types, the spatial statistics seem to vary more across frequency than across polarization and the observed differences increase in magnitude with decreasing frequency.
Polarimetric synthetic aperture radars, operating at L-, C- and P-band, were designed to replace and upgrade a system destroyed in an aircraft accident. Ground and flight tests were conducted, and the radar was flown over a calibration site in a sequence of experiments designed to calibrate the system. The radar also took part in science campaigns.
In this paper, we present ionospheric effects on polarimetric and interferometric SAR images, especially at low frequencies.
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.
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