Engineering topics
Publications and source records attributed to Rignot, E..
High-resolution radar images of Moreno Glaciar, Argentina, acquired by the Shuttle Imaging Radar C (SIR-C) on October 9 and 10 1994, at 24-cm wavelength (L-band), are utilized to map the glacier velocity both interferometrically and using a novel feature tracking technique.
ERS images of the two end points of the ice front Ronne Ice Shelf were processed to obtain interferograms which reveal the rate of the deformation of the ice shelf, due to tides and viscous creep, and the mechanisms of iceberg formation.
ERS radar interferometry is a powerful new technique to map the grounding line of outlet glaciers, or more precisely to located the limit of tidal flexing of their floating sections, or hinge line.
Repeat-pass, interferometric, radar observations of tropical rain-forest collected by the Shuttle Imaging Radar C (SIR-C) in the state of Rondonia, Brazil, reveal signal coherence is destroyed at C-band (5.6-cm) in the forest, whereas L-band (24-cm) radar signals remain strongly coherent over the entire landscape. At L-band, the rms difference in inferred topographic height between the forest and adjacent clearings is 5 m, equivalent to the height noise. Atmospheric delays are large, however, forming kilometer-sized anomalies with a 1.2-cm rms one way. Radar interferometric studies of the humid tropics must therefore be conducted at long radar wavelengths, with kilometric baselines or with two antennas operating simultaneously.
Quantitative results are to be provided (in the full paper) for two synthetic aperture radar (SAR) data missions from a space shuttle using the SIR-C/X-SAR in April and October 1994.
Synthetic-aperture radar (SAR) interferograms produced from ESA's ERS-1 satellite, provide the first synoptic view of ice flow dynamics of the western sector of the Greenland Ice Sheet. Glacial motion is detected in the radar ranging direction at millimetric scales, across a complete sequence of snow accumulation and melting regimes, despite significant varations in their radar scattering properties. Ice flow evolves from a slow, regular motion at the higher elevations. At lower elevations, motion is strongly convoluted by meter-scale undulations in surface topography, which have a unique interferometric signature that enables a novel approach for retrieving flow direction. Inferred flow directions, combined with surface displacements in the radar ranging direction, yield ice velocity estimates that are within 6% of in-situ measurements gathered along a 40 km survey line. Application of repeat-pass SAR interferometry to the entire Greenland Ice Sheet should enable precise mapping of its ice flow dynamics at an unprecedented level of spatial detail.
This paper reviews research since 1988 into the capabilities of synthetic aperture radar (SAR) for monitoring, classification, and characterization of the Bonanza Creek Experimental Forest on the floodplain of the Tanana River and adjacent uplands.
In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne synthetic-aperture radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity structure and moisture characteristics.
A number of planetary objects exhibit unusual radar polarizaion properties and more recently a similar behavior has been observed over a vast portion of the Earth's surface: the percolation facies of the Greenland Ice Sheet.
Automated recording stations have been installed at the Bonanza Creek Experimental Forest, a Long Term Ecological Research (LTER) site located near Fairbanks, Alaska, in a forest stand of the Tanana River floodplain underlain by discontinuous permafrost. These stations provide a continuous record of dielectric constant and temperature of tree trunks, and soil moisture and temperature profiles down to the root zone. Along with the weather stations deployed at the same location, these measurements provide a continuous record of the environmental and phenologic conditions of the forest during a complete seasonal cycle. At the same time, ERS-1 SAR imaged the study site repeatedly from space to provide radar backscatter measurements of the forest approximately three times a month. Here, we examine the temporal dynamic of ERS-1 SAR measurements in relation with the changing environmental and phenologic state of the forest canopy and of the forest ground layers during the winter/spring and fall/winter transitions of 1992 and 1993. During these transitions, we examine whether changes in radar backscatter observed by ERS-1 may be related to freezing or thawing of the soil and vegetation in order to determine the start and end of the growing season for the forest. The results of this analysis are used in turn to determine whether similar changes are observed over larger regions. Mosaics of SAR data generated along three different North-South Alaskan ERS-1 transects that intercept with our study site are used in combination with hourly air temperature and daily precipitation rates gathered at airport weather stations by the National Weather Service. Results obtained using ERS-1 data collected from January 1992 to mid-1993 will be discussed.
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Synthetic aperture radar (SAR) images of the Greenland ice sheet collected by an airborne system clearly reveal the four melting facies of this sheet defined 30 years ago from snow stratigraphy studies by glaciologists. In particular, the radar echoes from the percolation facies have radiometric and polarimetric characteristics that are unique among terrestrial surfaces, but that resemble the exotic radar echoes recorded from the icy Galilean satellites. There, the radar signals interact with subsurface, massive ice features created in the cold, dry snow by seasonal melting and refreezing events. The subsurface features act as efficient reflectors of the incident radiation most likely via internal reflections. In the soaked-snow facies, the radar reflectivity is much lower because radar signals are attenuated by the wetter snow before they can interact with subsurface structures. Inversion algorithms to derive geophysical information from the SAR data are developed in both cases to estimate snow wetness in the soaked-snow facies and the mass of ice water retained in the percolation facies.
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Changes in the seasonal CO(sub 2) flux of the boreal forests may result from increased atmospheric CO(sub 2) concentrations and associated atmospheric warming. To monitor this potential change, a combination of remote sensing information and ecophysiological models are required. In this paper we address the use of synthetic aperture radar (SAR) data to provide some of the input to the ecophysiological models: forest type, freeze/thaw state which limits the growing season for conifers, and leaf on/off state which limits the growing season for deciduous species. AIRSAR data collected in March 1988 during an early thaw event and May 1991 during spring breakup are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off and soil freeze/thaw transitions. Finally, a CO(sub 2) flux algorithm which utilizes SAR data and an ecophysiological model to estimate CO(sub 2) flux is presented. CO(sub 2) flux maps are generated from which areal estimates of CO(sub 2) flux are derived.
We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.
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.
This paper describes the results of monitoring environmental conditions in Alaskan Taiga forests using ERS-1 SAR dara.
This paper presents examples of quantitative improvements in classification accuracy of six winter ice conditions using SAR data resulting from the combination of multiple polarizations and frequencies.