Richard Carande

Ocean surface features and currents measured with synthetic aperture radar interferometry and HF radar

This paper describes the results of the first quantitative comparison between high-resolution ocean surface current fields extracted from interferometric synthetic aperture radar (INSAR) measurements and those from a high-frequency (HF) ocean surface current radar (OSCR) system. Data from each of these radar systems along with supporting measurements from shipboard and buoy-mounted sensors were collected during the High-Resolution Remote Sensing Experiment (High-Res) on June 20, 1993, on the continental shelf off the coast of Cape Hatteras, North Carolina. Both components of the surface current were obtained from the INSAR system at roughly 10-m resolution from two orthogonal flight legs over the region separated in time by about 30 min. The OSCR system measured two-dimensional surface current vectors at about 1-km resolution over this same region, while the USNS Bartlett was collecting hydrographic samples and near-surface current measurements. Two-dimensional wave spectra as well as meteorological and additional current measurements were collected at two buoys within the experimental area. We discuss in the paper two techniques for eliminating the effect of surface wave motion on the INSAR current estimates. One method relies on some knowledge of the local wind and wave field and the use of a microwave scattering model. The other method makes use of a few in situ current measurements spaced at different range locations across the INSAR image. Using either of these techniques, we find that the agreement between the INSAR and OSCR current estimates is generally very good. Furthermore, the INSAR current and magnitude imagery show the presence of undulating surface features where abrupt changes in the current speed and direction occurred. The ship surveys indicate that these features were caused by the collision of water masses of different density. We show for the first time in this paper a high-resolution, area-extensive vector surface current map derived from the INSAR of the two-dimensional flow in the vicinity of these features. Our results demonstrate convincingly that high-resolution oceanic surface current vectors can be derived from INSAR current measurements and that these measurements may be very beneficial for detailed studies of the dynamics of small-scale surface features in regions of strong current divergences or shears.

Space Geodetic Imaging of Rapid Ground Subsidence in Mexico City

Since the late 1950s, several areas of Mexico City have undergone accelerated ground subsidence and have developed associated fracturing and faulting. New interferometric synthetic aperture radar (InSAR) and global positioning system (GPS) data indicate that rates of current land subsidence in Mexico City exceed 350 mm/yr. These rates are close to historical maximum levels of the mid-twentieth century, when mitigation efforts were fi rst undertaken to reduce damage to urban infrastructure. The locus of maximum subsidence has shifted from its historical location in the old city center to the east. Correlation of our InSAR results with seismically mapped stratigraphic units suggests that subsidence is primarily controlled by compaction of Quaternary lacustrine clays and silts. We also evaluate spatial gradients in subsidence and suggest that this, rather than subsidence magnitude, is the key factor in risk assessment. Subsidence represents a major geologic risk for Mexico City and imposes serious constraints to any further urban development.

Coherence region shape extraction for vegetation parameter estimation in polarimetric SAR interferometry

Polarimetric SAR interferometry (POLINSAR) provides volumetric information about electromagnetic scattering processes, whereas standard INSAR assumes that only surface scattering is present. Instead of a single complex interferometric coherence for each pixel, POLINSAR observes a polarization-dependent coherence function whose range is called the coherence region. To estimate canopy parameters, the shape of this region must be matched to predictions from scattering models. For computational efficiency, the region must be represented by a small number of samples. Current sampling methods find the stationary points of coherence magnitude or phase; it is questionable whether the coherence region can be characterized adequately with so few samples. We have developed an algorithm for sampling the outer boundary of the coherence region. We formulate the problem of finding the minimum and maximum real part of the coherence as an eigenvalue problem. The solutions specify two points on the boundary. Other points are found by applying a phase shift to the POLINSAR cross-correlation matrix. The mathematical literature shows that the coherence region is convex, and hence the algorithm rinds the entire boundary. We present a comparison of boundary sampling to standard methods on L-band POLINSAR data from the SIR-C platform. It is evident that boundary sampling describes the shape of the coherence region more thoroughly than other methods.

Direct estimation of vegetation parameters from covariance data in polarimetric SAR interferometry

Polarimetric SAR interferometry (POLINSAR) is an emerging technique for the characterization of volumetric scattering processes. Each pixel of a POLINSAR interferogram is a 6/spl times/6 matrix of complex sample covariances among the polarimetric channels in the image pair. A model of polarimetric scattering from vegetation specifies the expected covariance matrix as a function of the vegetation parameters. The data matrix obeys a complex Wishart probability distribution that depends on the expected covariance. Using this, one can rind the maximum-likelihood estimate of the parameters from the data matrix. This paper presents the formula for the expected covariance matrix, as predicted by the model of Treuhaft and Siqueira for a random canopy over flat ground. An algorithm for computing the maximum-likelihood parameter estimate is derived. We test the algorithm on simulated data and compare its results to estimates derived from coherence samples. We conclude by discussing the extension of the direct estimation technique to more general POLINSAR scattering models.

Neural network classification with IFSAR and multispectral data fusion

The authors present neural network classification results for interferometric SAR (IFSAR) and multispectral imagery data, and describe a classification fusion scheme for the combination of the two classification results to reduce ambiguities and false classification rates. Two multilayer perceptron (MLP) neural networks were developed for the classification of IFSAR and multispectral data, separately. Classes include tree area, road, building, bare earth, water, etc. A classification fusion scheme that examines both the IFSAR and multispectral classification results at a pixel location and decides the fusion class for various cases is then discussed. Classification fusion results, especially the building classification and detection results, are presented. The results show that the scheme is effective in reducing false classification rate for buildings detection in the remotely sensed imagery data.

Robust inversion of vegetation structure parameters from low-frequency, polarimetric interferometric SAR

The Cloude model provides an approach to estimating vegetation structure parameters, such as bald Earth elevation, tree height, and canopy attenuation, using polarimetric interferometry techniques. We show that the model contains a degeneracy that allows the bald Earth elevation to be solved for reliably, but prevents accurate estimation of the other model parameters unless simplifying assumptions are made. We present results using UWB UHF data from the P-3 FOPEN sensor.

An extended model for characterizing vegetation canopies using polarimetric SAR interferometry

Effective exploitation of polarimetric SAR interferometry data over vegetated areas requires the use of a vegetation model of sufficient complexity to capture the underlying scattering processes. The standard Treuhaft model (randomly oriented vegetation + ground) makes a number of assumptions that may not be true in general. This paper presents a two-layer extended model that allows canopy attenuation to be a function of polarization, does not require the canopy to extend all the way to the ground, and allows the ground to be sloped. It is shown that many cases exist in which the two models predict similar coherence region shapes for significantly different structural parameters. It is argued that a minimum of two baselines is required for robust model selection and inversion.

Automated rapid mapping with interferometric synthetic aperture radar data

This paper describes automated algorithms that generate map products in a rapid fashion with interferometric synthetic aperture radar (IFSAR) data set. The input IFSAR data set consists of backscatter, elevation and correlation images and the automatically extracted map elements include land-use polygons, transportation networks, buildings/man-made structures, bare soil elevation contours and hydrology networks. A calculator computes five feature images from the IFSAR data set and the five feature images serve as inputs to a hybrid unsupervised classification algorithm which segments the scene into five classes. The five classes include fields, trees, urban area/man-made structure, water and unknown. The classification results allows a bare soil terrain model to be extracted from the IFSAR terrain model using a novel algorithm. The difference between the bare soil elevation and the original IFSAR elevation can be used in conjunction with the classification map to identify and estimate the heights of buildings, man-made structures and trees. Elevation contours and hydrology networks derived front the bare soil model can be shown to be more accurate than that derived from the IFSAR model. Transportation networks are identified using a road extraction technique based on rotational energy summation. Sample map products are shown to demonstrate the efficiency and accuracy of the automated algorithms.

InSAR-based hydrology of the Everglades, South Florida

New space-based observations of South Florida reveal spatially detailed, quantitative images of water levels in the Everglades, the focus of the largest wetlands restoration project yet attempted. The new data capture dynamic water level topography, providing the first three-dimensional regional-scale picture of wetland sheet flow. We observe localized radial sheet flow in addition to well-known southward unidirectional sheet flow. Our study shows that space-based hydrological observations can provide critical information for monitoring, understanding and managing wetland sheet flow, and contribute to wetland restoration