Ứng dụng Radar SAR phân cực lập bản đồ địa chất và thăm dò tài nguyên Bắc Cực

Western University Scholarship@Western Electronic Thesis and Dissertation Repository 12-14-2017 1:30 PM Polarimetric Synthetic Aperture Radar (SAR) Application for Geological Mapping and Resource Exploration in the Canadian Arctic Byung-Hun Choe, The University of Western Ontario Supervisor: Osinski, Gordon R., The University of Western Ontario Co-Supervisor: Neish, Catherine D., The University of Western Ontario Co-Supervisor: Tornabene, Livio L., The University of Western Ontario A thesis submitted in partial fulfillment of the requirements for the Doctor of Philosophy degree in Geology © Byung-Hun Choe 2017 Follow this and additional works at: https://ir.ca/etd Part of the Geology Commons Recommended Citation Choe, Byung-Hun, "Polarimetric Synthetic Aperture Radar (SAR) Application for Geological Mapping and Resource Exploration in the Canadian Arctic" (2017). Electronic Thesis and Dissertation Repository.ca/etd/5133 This Dissertation/Thesis is brought to you for free and open access by Scholarship@Western. It has been accepted for inclusion in Electronic Thesis and Dissertation Repository by an authorized administrator of Scholarship@Western. For more information, please contact wlswadmin@uwo.

Abstract The role of remote sensing in geological mapping has been rapidly growing by providing predictive maps in advance of field surveys. Remote predictive maps with broad spatial coverage have been produced for northern Canada and the Canadian Arctic which are typically very difficult to access. Multi and hyperspectral airborne and spaceborne sensors are widely used for geological mapping as spectral characteristics are able to constrain the minerals and rocks that are present in a target region. Rock surfaces in the Canadian Arctic are altered by extensive glacial activity and freeze-thaw weathering, and form different surface roughnesses depending on rock type.

Different physical surface properties, such as surface roughness and soil moisture, can be revealed by distinct radar backscattering signatures at different polarizations. This thesis aims to provide a multidisciplinary approach for remote predictive mapping that integrates the lithological and physical surface properties of target rocks. This work investigates the physical surface properties of geological units in the Tunnunik and Haughton impact structures in the Canadian Arctic characterized by polarimetric synthetic aperture radar (SAR). It relates the radar scattering mechanisms of target surfaces to their lithological compositions from multispectral analysis for remote predictive geological mapping in the Canadian Arctic.

This work quantitatively estimates the surface roughness relative to the transmitted radar wavelength and volumetric soil moisture by radar scattering model inversion. The SAR polarization signatures of different geological units were also characterized, which showed a significant correlation with their surface roughness. This work presents a modified radar scattering model for weathered rock surfaces. More broadly, it presents an integrative remote predictive mapping algorithm by combining multispectral and polarimetric SAR parameters.

i Keywords Polarimetric SAR, physical surface properties, radar scattering mechanism, surface parameter inversion, polarization signature, multispectral analysis, remote predictive geological mapping, meteorite impact structures, Canadian Arctic. ii Co-Authorship Statement Chapter 2. Remote predictive mapping of the Tunnunik impact structure in the Canadian Arctic using multispectral and polarimetric SAR data fusion: All data were collected and processed by Byung-Hun Choe and Dr. The manuscript was written by Byung-Hun Choe.

Osinski, and Jennifer D. Newman contributed to interpretations on image processing and sample collection and analysis, and provided editorial suggestions and comments. It is currently in revision in Canadian Journal of Remote Sensing for publication titled ‘Remote predictive mapping of the Tunnunik impact structure in the Canadian Arctic using multispectral and polarimetric SAR data fusion’. A modified semi-empirical radar scattering model for weathered rock surfaces: All data were collected and processed by Byung-Hun Choe, and the manuscript was written by Byung-Hun Choe.

Neish, and Dr. Tornabene contributed to interpretations with editorial suggestions and comments. It is currently in preparation to be submitted to IEEE Transactions on Geoscience and Remote Sensing for publication titled ‘A modified semi-empirical radar scattering model for weathered rock surfaces’. Polarimetric SAR signatures for characterizing geological units in the Canadian Arctic: All data were collected and processed by Byung-Hun Choe, and the manuscript was written by Byung-Hun Choe.

Neish, and Dr. Tornabene contributed to interpretations with editorial suggestions and comments. It is currently in preparation to be submitted to IEEE Transactions on Geoscience iii and Remote Sensing for publication titled ‘Polarimetric SAR signatures for characterizing geological units in the Canadian Arctic’. iv Dedication I can do all this through him who gives me strength.

-Philippians 4:13- v Acknowledgments Now I finally have a chance to thank my amazing supervisors for their encouragement and support throughout my Ph. First of all, I am grateful to Dr. Gordon Osinski for bring me into the Canadian Arctic and impact cratering studies. Catherine Neish, thank you for infecting me with her RADAR love.

My little RADAR background could be advanced through insightful discussions with her. Livio Tornabene, thank you for guiding and teaching me multispectral remote sensing from the bottom up. They are really a perfect combination for my thesis. Also, I need to gratefully acknowledge the financial and logistical supports for this work provided by Canadian Space Agency (CSA) through Science Operational Applications Research (SOAR), Natural Resource Canada (NRCan) through Polar Continental Shelf Program (PCSP), and Polar Knowledge Canada through Northern Scientific Training Program (NSTP).

I would like to thank the 2015/2016 Arctic field expedition crews, Shamus Duff, Etienne Godin, Taylor Haid, Elise Harrington, Jean Filion, Cassandra Marion, Robert Misener, Jennifer Newman, Alexandra Pontefract, Racel Sopoco, Michael Zanetti, and William Zylberman for their support making the field works successful. Also, many thanks to the space rocks lab and CPSX members for sharing their expertise and enthusiasm on planetary sciences. I would like to extend my thanks to my former M. Duk-jin Kim and SATGEO lab members at Seoul National University for helping me get started on this path and for encouraging me to be a better scientist every time I meet them at conferences.

I cannot forget to thank my parents and parents-in-law for believing and supporting me with love and patience. Special thanks to my mother-in-law for her dedicated support going back and forth between Canada and South Korea whenever I was away for fields and needed a hand, without whom I would not have completed this in time. Last but not least, I truly thank my lovely wife, Ji Yeon Lim, without whom I would not be where I am today. Thank you for being my lifetime partner with endless love and support.

I have truly enjoyed the journey with you, and expect much more for the rest of our journey with the amazing kids, Aine and Ian. vi Table of Contents Abstract. i Co-Authorship Statement. vi Table of Contents.

vii List of Tables. x List of Figures. xi List of Appendices. xvii List of Acronyms .2 SAR remote sensing .3 SAR applications for geological mapping .4 Impact structure-based mapping approach .5 Geological setting of study areas .6 Thesis objectives and outlines.

34 2 Remote predictive mapping of the Tunnunik impact structure in the Canadian Arctic using multispectral and polarimetric SAR data fusion .2 Methods and datasets used .1 Spectral datasets, calibration, and methods .2 RADARSAT-2 dataset, calibration, and methods .3 Remote Predictive Mapping (RPM) and additional supporting datasets: Quickbird and Canadian Digital Elevation Model (CDEM) .4 Ground-truth and subsequent sample analysis .1 ASTER TIR emissivity .2 Landsat 8 VNIR/SWIR reflectance .3 Polarimetric SAR decomposition .4 High-resolution Quickbird and CDEM .4 Remote predictive mapping .1 Synthesis of remote sensing observations.2 Decision-tree based algorithm .5 Ground truth: field and laboratory observations .6 Discussion and conclusions. 74 3 A modified semi-empirical radar scattering model for weathered rock surfaces .2 Polarimetric SAR data and ground truth collection .4 Modified model for weathered rock surfaces .2 Combined inversion algorithm .5 Discussion and conclusions. 100 4 Polarimetric SAR signatures for characterizing geological units in the Canadian Arctic .2 Polarimetric SAR data and ground truth collection .2 Polarization basis change and 3-dimentional signature plot .3 Pedestal height and standard deviation of linear co-polarizations (SDLP) .4 Results and discussion .1 Summary and general discussion. 156 ix List of Tables Table 1.

SAR application studies for geological mapping in northern and Arctic Canada. Specifications of remote sensing datasets used in Chapter 2. Colour scheme and characteristics of each unit derived from different remote sensors. Specifications of RADARSAT-2 data used in Chapter 3.

78 x List of Figures Figure 1. SAR side-looking imaging geometry (right; θ: incidence angle, ground range=slant range/𝑠𝑖𝑛𝜃) and nadir-looking geometry (left). Figure modified from Elachi et al. Sinusoidal wave plot (left; λ: wavelength, A: amplitude, and ϕ: phase) and its expression on the complex plane (right).

Brighter areas have higher radar backscattering coefficients. Radar backscatter is a function of a surface’s physical properties: its roughness, structure, and dielectric constant. Locations of the Tunnunik (red star) and the Haughton (blue star) impact structures. Simplified geological map of the Tunnunik impact structure and northwestern Victoria Island (left, modified from Dewing et al.

(2015)) and stratigraphic column of northwestern Victoria Island (right, from Dewing et al. The white square represents the coverage of the remote sensing datasets used in Chapter 2. Simplified geological map of the Haughton impact structure (left, modified from Osinski et al. (2015)) and stratigraphic column of the target sequence at the Haughton impact structure (right, from Osinski et al.

MNF transformed ASTER TIR emissivity RGB color composite (upper, R; MNF band 1, G; band 2, B; band 3 by applying a linear 2% stretch) and TIR emissivity spectra matching results (bottom). Vegetation and water bodies in the MNF composite were masked out in black. The white numbers on the MNF composite represent the 4 spectral units discussed in the text. The coloured lines are the averaged TIR emissivity spectra (solid) of representative 30 samples from each unit and its standard deviation (dashed with markers); (a) orange-yellow, (b) cyan, (c) green, and (d) magenta units.

The solid black lines are the best matching rock spectra from the ASU Ward’s whole-rock spectral library (Christensen et al. The black numbers xi (10-14) on the top X axis represent ASTER TIR bands corresponding to wavelengths listed in Table 2. ASTER TIR band ratio images. They were coloured in purple (low) to red (high) at the range of (a) 1.05, respectively by applying a linear 2% stretch.

Vegetation and water bodies were masked out in black. Landsat 8 OLI band ratio color composite (R; b4/b2 (1.49) by applying a Gaussian stretch with a standard deviation of 3). The majority of densely vegetated areas and water bodies were masked out in black. Remaining pixels dominated by green around channels and lakes are vegetated areas that were difficult to remove without adversely effecting mineral- and rock- dominated spectral units.

The numbers represent the 4 spectral units discussed in the text. The white arrows indicate the dumbbell- shaped (left) and tadpole-shaped (right) features, respectively. RADARSAT-2 polarimetric decomposition results. The RGB composites of the Pauli and Freeman-Durden decomposition represent double-bounce scattering (red), multiple scattering (green), and single-bounce scattering (blue), respectively.

The Pauli and Freeman-Durden histograms were linearly stretched at the same range from -25 to 0 dB. High-resolution Quickbird image (a, the RGB colour image was stretched by applying the histogram equalization for enhancing image contrast and classification), CDEM (b), and Quickbird image close-ups for each unit ((c) Unit 1, (d) Unit 2, (e) Unit 3, and (f) Unit 4). The blue numbers in (a) represent the locations of the close-ups. A decision-tree based algorithm for remote predictive mapping (‘Veg.’=vegetated surfaces, ‘L8’=Landsat8 VNIR/SWIR band ratio, ‘AST’=ASTER TIR band ratio, ‘RS2 MS’=RADARSAT-2 multiple-scattering, ‘H’=high threshold, and ‘L’=low threshold).

Remote predictive geological map of the Tunnunik impact structure. Vegetation and water bodies are masked out in black. Field photos from each unit. A scale card of 9 by 5 cm (a-e), a ~2.5 cm diameter coin (f), and a tripod-mounted LiDAR of 1.6 m height (g) for scale.

Example of in situ measurements of surface roughness and soil moisture. (a) LiDAR scanning weathered rock surfaces at the Tunnunik (~1.7m tripod-mounted LiDAR for scale). (b) Surface topography in a 3-D point clouds generated from the LiDAR scan.