Statistics for Spatial Data.

[1] The Shuttle Radar Topography Mission produced the most complete, highest-resolution digital elevation model of the Earth. The project was a joint endeavor of NASA, the National Geospatial-Intelligence Agency, and the German and Italian Space Agencies and flew in February 2000. It used dual radar antennas to acquire interferometric radar data, processed to digital topographic data at 1 arc sec resolution. Details of the development, flight operations, data processing, and products are provided for users of this revolutionary data set.

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The Shuttle Radar Topography Mission

Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used.

Permanent scatterers in SAR interferometry

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.

/pdf/a-new-algorithm-for-surface-deformation-monitoring-based-on-ot8ep5chnm.pdf

A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms

On February 22, 2000 Space Shuttle Endeavour landed at Kennedy Space Center, completing the highly successful 11-day flight of the Shuttle Radar Topography Mission (SRTM). Onboard were over 300 high-density tapes containing data for the highest resolution, most complete digital topographic map of Earth ever made. SRTM is a cooperative project between NASA and the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense. The mission was designed to use a single-pass radar interferometer to produce a digital elevation model (DEM) of the Earth's land surface between about 60 deg north and 56 deg south latitude. When completed, the DEM will have 30 m pixel spacing and about 15 m vertical accuracy. Two orthorectified image mosaics (one from the ascending passes with illumination from the southeast and one from descending passes with illumination from the southwest) will also be produced.

Saturn's rings: Particle size distributions for thin layer models

A method of remotely measuring near-surface ocean currents with a synthetic aperture radar (SAR) is described. The apparatus consists of a single SAR transmitter and two receiving antennas. The phase difference between SAR image scenes obtained from the antennas forms an interferogram that is directly proportional to the surface current. The first field test of this technique against conventional measurements gives estimates of mean currents accurate to order 20 percent, that is, root-mean-square errors of 5 to 10 centimeters per second in mean flows of 27 to 56 centimeters per second. If the full potential of the method could be realized with spacecraft, then it might be possible to routinely monitor the surface currents of the world's oceans.

https://science.sciencemag.org/content/sci/246/4935/1282.full.pdf

Remote sensing of ocean currents.

The advent of interferometric synthetic aperature radar for geophysical studies has resulted in the need for accurate, efficient methods of two-dimensional phase unwrapping. Inference of the lost integral number of cycles in phase measurements is critical for three-pass surface deformation studies as well as topographic mapping and can result in an order of magnitude increase in sensitivity for two-pass deformation analysis. While phase unwrapping algorithms have proliferated over the past ten years, two main approaches are currently in use. Each is most useful only for certain restricted applications. All these algorithms begin with the measured gradient of the phase field, which is subsequently integrated to recover the unwrapped phases. The earliest approaches in interferometric applications incorporated residue identification and cuts to limit the possible integration paths, while a second class using least-squares techniques was developed in the early 1990’s. We compare the approaches and find that the residue-cut algorithms are quite accurate but do not produce estimates in regions of moderate phase noise. The least-squares methods yield complete coverage but at the cost of distortion in the recovered phase field. A new synthesis approach, combining the cuts from the first class with a least-squares solution, offers greater spatial coverage with less distortion in many instances.

/pdf/phase-unwrapping-algorithms-for-radar-interferometry-residue-3f28hi8fyk.pdf

Phase unwrapping algorithms for radar interferometry: residue-cut, least-squares, and synthesis algorithms

[1] Radar interferograms provide precise (millimeter level) measurements of crustal deformation at fine resolution over wide areas. The dominant error source in many interferograms results from spatial heterogeneity of the wet component of atmospheric refractivity, resulting in excess path length of the radar signal propagating through the neutral atmosphere. In this report, we introduce a method to compensate for atmospheric phase artifacts in a radar interferogram using spatially interpolated zenith wet delay (ZWD) data obtained from a network of Global Positioning System (GPS) receivers in the region imaged by the radar. Our method, based on Taylor's “frozen-flow” hypothesis, uses GPS data recorded prior to and after the individual radar acquisition times to infer denser spatial networks of control points for interpolation than is suggested by the sparse and irregular spatial distribution of GPS receivers. We test this approach by correcting phase fluctuations observed in a radar interferogram over an area covered by the Southern California Integrated GPS Network stations, using maps of atmospheric delay interpolated from the denser network of GPS ZWD measurements generated by our method. We find that the largest improvement results from removing an altitude-dependent model derived from the GPS data: the uncorrected interferogram in our example has an RMS fluctuation of 16.1 mm, which falls to 8.6 mm after the altitude correction. A map derived from ZWD measurements recorded only at the instances of radar acquisition reduced overall fluctuations in the data from 8.6 to 8.1 mm RMS, while using the inferred denser network reduces the error further to 7.5 mm RMS. Most of this residual variation is due to decorrelation of the signal and does not result from atmospheric propagation, however. After smoothing to remove decorrelation noise, the residual drops from 4.7 to 3.9 mm (GPS stations only) and then to 2.7 mm RMS when the denser network algorithm is used.

Correction for interferometric synthetic aperture radar atmospheric phase artifacts using time series of zenith wet delay observations from a GPS network

This computing environment is the next generation of geodetic image processing technology for repeat-pass Interferometric Synthetic Aperture (InSAR) sensors, identified by the community as a needed capability to provide flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. This software allows users of interferometric radar data the flexibility to process from Level 0 to Level 4 products using a variety of algorithms and for a range of available sensors. There are many radar satellites in orbit today delivering to the science community data of unprecedented quantity and quality, making possible large-scale studies in climate research, natural hazards, and the Earth's ecosystem. The proposed DESDynI mission, now under consideration by NASA for launch later in this decade, would provide time series and multiimage measurements that permit 4D models of Earth surface processes so that, for example, climate-induced changes over time would become apparent and quantifiable. This advanced data processing technology, applied to a global data set such as from the proposed DESDynI mission, enables a new class of analyses at time and spatial scales unavailable using current approaches. This software implements an accurate, extensible, and modular processing system designed to realize the full potential of InSAR data from future missions such as the proposed DESDynI, existing radar satellite data, as well as data from the NASA UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), and other airborne platforms. The processing approach has been re-thought in order to enable multi-scene analysis by adding new algorithms and data interfaces, to permit user-reconfigurable operation and extensibility, and to capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods based on recent research, including object-oriented scripts controlling legacy and new codes, abstraction and generalization of the data model for efficient manipulation of objects among modules, and well-designed module interfaces suitable for command- line execution or GUI-programming. The framework is designed to allow users contributions to promote maximum utility and sophistication of the code, creating an open-source community that could extend the framework into the indefinite future.

Howard A. Zebker

Papers

Saturn's rings: Particle size distributions for thin layer models

Remote sensing of ocean currents.

Phase unwrapping algorithms for radar interferometry: residue-cut, least-squares, and synthesis algorithms

Correction for interferometric synthetic aperture radar atmospheric phase artifacts using time series of zenith wet delay observations from a GPS network

InSAR Scientific Computing Environment