A Comprehensive Forward Model for Imaging under Irregular Terrain Using RF Tomography

Imaging of tunnel networks under irregular terrain using RF tomography is generalized to include the possibility of magnetic dipoles (i.e., electric loops) either as transmitting or receiving devices. Forward scattering models are presented, and a generalized method for computing numerical dyadic Green’s functions is detailed. Explicit formulas for fast numerical implementation are also presented. The paper is corroborated with numerical simulations aimed at validating formulas

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Sparse 3D Seismic Imaging in the Kylylahti Mine Area, Eastern Finland: Comparison of Time Versus Depth Approach

A 10.5 km2 3D seismic survey was acquired over the Kylylahti mine area (Outokumpu mineral district, eastern Finland) as a part of the COGITO-MIN (COst-effective Geophysical Imaging Techniques for supporting Ongoing MINeral exploration in Europe) project, which aimed at the development of cost-effective geophysical imaging methods for mineral exploration. The cost-effectiveness in our case was related to the fact that an active-source 3D seismic survey was accomplished by using the receiver spread originally designed for a 3D passive survey. The 3D array recorded Vibroseis and dynamite shots from an active-source 2D seismic survey, from a vertical seismic profiling experiment survey, as well as some additional “random” Vibroseis and dynamite shots made to complement the 3D source distribution. The resulting 3D survey was characterized by irregular shooting geometry and relatively large receiver intervals (50 m). Using this dataset, we evaluate the effectiveness of the standard time-imaging approach (post-stack and pre-stack time migration) compared to depth imaging (standard and specialized Kirchhoff pre-stack depth migration, KPreSDM). Standard time-domain processing and imaging failed to convincingly portray the first ~1500 m of the subsurface, which was the primary interest of the survey. With a standard KPreSDM, we managed to obtain a good image of the base of the Kylylahti formation bordering the extent of the mineralization-hosting Outokumpu assemblage rocks, but otherwise the image was very noisy in the shallower section. The specialized KPreSDM approach (i.e., coherency-based Fresnel volume migration) resulted in a much cleaner image of the shallow, steeply dipping events, as well as some additional deeper reflectors, possibly representing repetition of the contact between the Outokumpu assemblage and the surrounding Kalevian metasediments at depth

3-D multiobservable probabilistic inversion for the compositional and thermal structure of the lithosphere and upper mantle: III. Thermochemical tomography in the Western-Central U.S.

Acknowledgments We are indebted to F. Darbyshire and J. von Hunen for useful comments on earlier versions of this work. This manuscript benefited from thorough and constructive reviews by W. Levandowski and an anonymous reviewer. We also thank J. Connolly, M. Sambridge, B. Kennett, S. Lebedev, B. Shan, U. Faul, and M. Qashqai for insightful discussions about, and contributions to, some of the concepts presented in this paper. The work of J.C.A. has been supported by two Australian Research Council Discovery grants (DP120102372 and DP110104145). Seismic data are from the IRIS DMS. D.L.S. acknowledges support from NSF grant EAR-135866. This is contribution 848 from the ARC Centre of Excellence for Core to Crust Fluid Systems (http://www.ccfs.mq.edu.au) and 1106 in the GEMOC Key Centre (http://www.gemoc.mq.edu.au).Peer reviewedPublisher PD

Investigations of polygonal patterned ground in continuous Antarctic permafrost by means of ground penetrating radar and electrical resistivity tomography: Some unexpected correlations

The results of a combined geophysical and geomorphological investigation of thermal-contraction-crack polygons near Gondwana station (Germany) in northern Victoria Land (Antarctica) are reported. An area of about 20,000 m2 characterized by random orthogonal polygons was investigated using integrated ground penetrating radar, electrical resistivity tomography, geomorphological surveys, and two trench excavations. The polygons are well developed only at elevations higher than 6–7 m above current sea level on Holocene-age raised beaches. It is concluded that the polygons are composite in nature because the shallow linear depressions that outline the polygons are underlain by fissures that can contain both sandy gravel and foliated ice (i.e., ice wedges) even in the same polygon network and at distances of just a few meters. Unexpectedly, most of the polygons follow the border of the raised beaches and develop in correspondence with stratigraphic layers dipping toward the sea, imaged by ground penetrating radar (GPR) profiles and interpreted as prograding layers toward the present-day shoreline

GIS-based spatial analysis coupled with geophysical imaging to identify and evaluate factors that control the formation of karst sinkholes in southwestern Missouri

Sinkholes are inherent features of the karst terrain underlying much of Greene County, Missouri. These features present hazards and engineering challenges to existing infrastructure unknowingly constructed on a seemingly benign ground surface. The primary objective of this research was to investigate the physical processes chiefly responsible for triggering the seemingly random distribution of sinkholes in the study area. This research employed an integrated approach encompassing regional scale GIS-based spatial analyses and site-specific geophysical data. GIS-based spatial analysis was employed to identify significant physical factors that appeared to influence the formation and distribution of sinkholes. Seven out of the twelve most cited factors influencing sinkhole development were identified in the study area. These factors were: overburden thickness, depth-to-groundwater, slope of the ground surface, distance to the nearest water course, distance to the nearest geologic structures, distance to nearest springs, and distance to the nearest roads. In the site-specific geophysical investigations, two dimensional (2D) and pseudo three dimensional (3D) - ERT, MASW, and borehole data were used to characterize the subsurface morphology of the karstified soil-bedrock interface in five selected sinkholes. From the interpretation of the 2D and pseudo 3D-ERT profiles, it was determined that four of the five sinkholes occurred at the intersections of regional systematic joint sets. The joint sets are characterized by a linear, visually prominent zones of low resistivity. The relatively low resistivity values are attributed to vertical seepage and the associated piping of fine-grained soils through preexisting fractures (often widened by solutioning) --Abstract, page iv

Regional scale rain-forest height mapping using regression-kriging of spaceborne and airborne lidar data : application on French Guiana

LiDAR data has been successfully used to estimate forest parameters such as canopy heights and biomass. Major limitation of LiDAR systems (airborne and spaceborne) arises from their limited spatial coverage. In this study, we present a technique for canopy height mapping using airborne and spaceborne LiDAR data (from the Geoscience Laser Altimeter System (GLAS)). First, canopy heights extracted from both airborne and spaceborne LiDAR were extrapolated from available environmental data. The estimated canopy height maps using Random Forest (RF) regression from airborne or GLAS calibration datasets showed similar precisions (~6 m). To improve the precision of canopy height estimates, regression-kriging was used. Results indicated an improvement in terms of root mean square error (RMSE, from 6.5 to 4.2 m) using the GLAS dataset, and from 5.8 to 1.8 m using the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on canopy height estimates precision, six subsets were derived from the initial airborne LiDAR dataset. Results indicated that using the regression-kriging approach a precision of 1.8 m on the canopy height map was achievable with a flight line spacing of 5 km. This precision decreased to 4.8 m for flight line spacing of 50 km

Passive RF Tomography: Signal Processing and Experimental Validation

Radio frequency (RF) tomography is an imaging technique based upon a set of distributed transmitters and receivers surrounding the area under observation. This method requires prior knowledge of the transmitters\u27 and receivers\u27 locations. In some circumstances the transmitters may be uncooperative, while in other cases extrinsic emitters may be used as source of opportunity. In these scenarios, RF tomography should operate in a passive modality. A previous work postulated the principles and feasibility of passive RF tomography. This research further develops the underlying theory through concise and ad-hoc signal processing. Experimental verification and validation corroborate the effectiveness of passive RF tomography for object detection and imaging

SAR image reconstruction and autofocus by compressed sensing

Cataloged from PDF version of article.A new SAR signal processing technique based on compressed sensing is proposed for autofocused image reconstruction on subsampled raw SAR data. It is shown that, if the residual phase error after INS/GPS corrected platform motion is captured in the signal model, then the optimal autofocused image formation can be formulated as a sparse reconstruction problem. To further improve image quality, the total variation of the reconstruction is used as a penalty term. In order to demonstrate the performance of the proposed technique in wide-band SAR systems, the measurements used in the reconstruction are formed by a new under-sampling pattern that can be easily implemented in practice by using slower rate A/D converters. Under a variety of metrics for the reconstruction quality, it is demonstrated that, even at high under-sampling ratios, the proposed technique provides reconstruction quality comparable to that obtained by the classical techniques which require full-band data without any under-sampling. (C) 2012 Elsevier Inc. All rights reserved