Thierry Toutin

Complex faulting confounds earthquake research in the Charlevoix Seismic Zone, Quebec

Following every earthquake felt in eastern North America, journalists ask the eternal question, “Which fault is responsible for this earthquake?” In intraplate environments,such as the Charlevoix Seismic Zone (CSZ), Quebec, Canada, a definite answer seldom exists. Seismologists face major difficulties: most earthquakes occur at mid-crustal depths, the Precambrian basement where most earthquakes occur is geologically complex, and fault locations are poorly known. Fortunately, seismologists receive help from other geoscientific fields and exploration techniques, most notably remote sensing, seismic methods, and potential fields. The integration of these geophysical tools is helping us to better understand the earthquake-fault connection in the CSZ, which is eastern Canadas most seismically active zone. Most microearthquakes— the type that occur frequently in the CSZ—occur within highly fractured blocks bounded by regional geological faults. Our interpretation is different from the common assumption that earthquakes, independent of their size, occur along regional faults.

Geometric Correction of Remotely Sensed Images

Remotely sensed images usually contain geometric distortions so significant that they cannot be used directly with base map products in a geographic information system (GIS). Consequently, multi-source data integration (raster and vector) for cartographic applications, such as forestry, requires geometric and radiometric processing adapted to the nature and characteristics of the data in order to keep the best information from each image in the composite ortho-rectified image.

Digital Terrain Modeling and Glacier Topographic Characterization

The Earth’s topography results from dynamic interactions involving climate, tectonics, and surface processes. In this chapter our main interest is in describing and illustrating how satellite-derived DEMs (and other DEMs) can be used to derive information about glacier dynamical changes. Along with other data that document changes in glacier area, these approaches can provide useful measurements of, or constraints on glacier volume balance and—with a little more uncertainty related to the density of lost or gained volume—mass balance. Topics covered include: basics on DEM generation using stereo image data (whether airborne or spaceborne), the use of ground control points and available software packages, postprocessing, and DEM dataset fusion; DEM uncertainties and errors, including random errors and biases; various glacier applications including derivation of relevant geomorphometric parameters and modeling of topographic controls on radiation fields; and the important matters of glacier mapping, elevation change, and mass balance assessment. Altimetric data are increasingly important in glacier studies, yet challenges remain with availability of high-quality data, the current lack of standardization for methods for requiring, processing, and representing digital elevation data, and the identification and quantification of DEM error and uncertainty.

Subpixel image matching based on Fourier phase correlation for Radarsat-2 stereo-radargrammetry

Image matching is the major step in the radargrammetric process to measure elevation parallax. To extract parallax from stereo synthetic aperture radar images the subpixel image matching method based on Fourier phase correlation was implemented with an algorithm using the hierarchical multiresolution approach and applied to Fine Quad mode Radarsat-2 data. The experimental results with simulated images show that a decrease in intersection angle leads to an increase in matching accuracy of up to 0.06 of a pixel. To validate the matching results a digital surface model was extracted from the real stereo pair and compared with accurate lidar data. The statistics show that there are good improvements (in the order of 10%–20%) in the accuracy over results extracted using a traditional image matching technique based on the normalized cross-correlation. The analysis of the mutual dependence of matching accuracy and stereo pair configurations shows that the application of subpixel matching allows us to make the radargrammetric process flexible in the choice of stereo pairs.

DEM generation over ice fields in the Canadian Arctic with along-track SPOT5 HRS stereo data

A digital elevation model (DEM) was generated using a SPOT5 HRS stereo pair acquired over a challenging ice field and fjord study site in Nunavut (80% of the area was ice covered and almost 50% of the area had 40° slopes). The DEM was thus evaluated by comparison with a topographic 1959 DEM and ICESat data, over and outside the ice fields and as a function of slope. The DEM generation did not need any reference cartographic data for collecting ground control points. The method could be applied to ice-covered areas with a 15 m accuracy (1 σ) over less than 5° slopes or a 22 m accuracy (1 σ) over less than 40° slopes. In addition, a systematic elevation lowering of 8–10 m computed between 1959 DEM and recent elevation data (HRS and ICESat) could be due to ice field wastage over the last 50 years.

StereoPol Radarsat-2 data fusion in radargrammetry

With new Radarsat-2 capabilities the complex polarimetric data can be included in the radargrammetry by fusing stereo polarimetric (stereopol) data into intensity stereo images. In this study the different fusion techniques, based on the combination of complex polarimetric data and polarimetric decompositions, are investigated. The stereo matching capability of the fusion techniques was quantitatively evaluated with textural parameters and cross-correlation coefficient and by comparing stereo-extracted digital surface models (DSM) with airborne lidar data. The textural parameters, calculated from gray level co-occurrence matrix (correlation and contrast), and the cross-correlation coefficient were found to be potential indicators of stereo matching of fused images. The application of the Pauli decomposition showed that stereo matching accuracy, evaluated by the difference between lidar and DSM, depends on the scattering mechanism.

Impact of Orthorectification on Simulated Compact Polarimetric RCM Data With Accurate Lidar DSM

Orthorectification using digital terrain models is a key issue for polarimetric complex synthetic aperture radar (SAR) data because resampling the complex data can corrupt the polarimetric phase, mainly in terrain with relief. Orthorectification will be also a sensitive issue with the compact polarimetric data of the future Canadian Radar Constellation Mission (RCM) sensor to be launched in 2018. Two orthorectification methods for the complex SAR data are thus proposed and compared: performing polarimetric processing in the image space before the geometric processing or in the ground space after the geometric processing. RCM compact polarimetric data using the requirements of the very high resolution (VHR) mode were simulated at the Canada Centre for Mapping and Earth Observation from fine-quad Radarsat-2 data acquired with different look angles over a hilly relief study site. Quantitative evaluations between the two methods, using a basis-invariant parameter (the entropy), were thus performed to evaluate the impact of orthorectification on the simulated VHR RCM data. To avoid the propagation of elevation errors into the final error budget, an accurate lidar digital surface model was used in the orthorectification. The results demonstrated that the oversampling and the noise floor that is used to generate the simulated VHR RCM data are the main factors, which corrupted the simulated VHR RCM data during its orthorectification with the ground-space method.