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Improved Mapping Accuracy of Planetary Surfaces Using Super- Resolution of Thermal Infrared Data

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Improved Mapping Accuracy of Planetary Surfaces Using Super- Resolution of Thermal Infrared Data IMPROVED MAPPING ACCURACY OF PLANETARY SURFACES USING SUPER- RESOLUTION OF THERMAL INFRARED DATA by Christopher Gerald Hughes B.S. Computer Science, Dickinson College, 1996 Submitted to the Graduate Faculty of Arts and Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2011 UNIVERSITY OF PITTSBURGH ARTS AND SCIENCES This dissertation was presented by Christopher Gerald Hughes It was defended on November 18, 2010 and approved by Thomas H Anderson, Professor, University of Pittsburgh Daniel J Bain, Assistant Professor, University of Pittsburgh Joshua L Bandfield, Research Assistant Professor, University of Washington William Harbert, Professor, University of Pittsburgh Charles E Jones, Lecturer, University of Pittsburgh Dissertation Advisor: Michael S Ramsey, Associate Professor, University of Pittsburgh ii Copyright © by Christopher Gerald Hughes 2011 iii IMPROVED MAPPING ACCURACY OF PLANETARY SURFACES USING SUPER- RESOLUTION OF THERMAL INFRARED DATA Christopher Gerald Hughes, PhD University of Pittsburgh, 2011 Super-Resolution is the process of obtaining a spatial resolution greater than that of the original resolution of a data source. This can be done through the fusion of original data with an additional source that has the desired resolution. These approaches can either be qualitative for visual appeal, quantitative for data accuracy, or some combination of both. The super-resolution approach offers an alternative to traditional sub-pixel deconvolution identification and provides higher resolution TIR data for Earth and Mars. The Thermal Emission Imaging System (THEMIS) has provided the highest spatial resolution (100 meter / pixel) thermal infrared (TIR) data of the Mars surface to date. These data have enabled the discovery of small-scale compositional units and helped to constrain surface processes operating at these scales. Higher resolution visible instruments have revealed smaller- scale differences, creating a need to detect compositional variability using TIR data at scales below 100 meters. Putative chloride deposits identified on Mars are one such area. These deposits have a unique spectral signature in the TIR and are present within topographic lows. The super-resolution algorithm helped constrain the local mineral assemblages and stratigraphic order. This data reveals that associated phyllosilicate-rich units may be part of a common lithostratigraphic unit with a phyllosilicate-poor ST-2 material. iv Lunar Lake playa, located ~100 km northeast of Tonopah, Nevada, has been used as an analog site for multiple planetary surfaces and as a vicarious calibration site for Earth-orbiting satellites. As such, the ability to obtain higher resolution data through super-resolution has the potential to improve Earth data and give to insight into the formation of similar environments on other planetary surfaces. Super-resolved data show Lunar Lake playa to be more compositionally heterogeneous than previously thought. A gradation of mineralogy exists within the playa, seen in both super-resolved data and in samples collected during fieldwork. The composition of the playa is influenced by the immediate surroundings, with variation existing between the western side of the playa, bounded by basaltic units, and the eastern, bounded by rhyolitic tuff. As the surrounding material weather, different clasts are transported onto the playa, and weather into different mineral assemblies. v TABLE OF CONTENTS ACKNOWLEDGMENTS ......................................................................................................... XX 1.0 SUPER-RESOLUTION OF THEMIS THERMAL INFRARED DATA: COMPOSITIONAL RELATIONSHIPS OF SURFACE UNITS BELOW THE 100 METER SCALE ON MARS ........................................................................................................ 1 1.1 INTRODUCTION ............................................................................................... 1 1.1.1 Super-Resolution ............................................................................................. 3 1.1.2 Instrument Datasets ........................................................................................ 7 1.2 METHODOLOGY .............................................................................................. 9 1.2.1 Current Approach ........................................................................................... 9 1.2.2 Modifications to the Super-Resolution Methodology ................................. 11 1.2.3 Identification of Acceptable Data ................................................................. 13 1.2.4 Data Preprocessing Prior to Super-Resolution ........................................... 15 1.3 RESULTS ........................................................................................................... 17 1.4 DISCUSSION ..................................................................................................... 36 1.5 CONCLUSIONS ................................................................................................ 43 2.0 MODIFICATION AND ANALYSIS OF A SUPER-RESOLUTION ALGORITHM ............................................................................................................................. 46 2.1 INTRODUCTION ............................................................................................. 46 vi 2.2 MODIFICATION OF THE ALGORITHM ................................................... 47 2.2.1 Step 1: Convolution with the Point Spread Function ................................. 48 2.2.2 Step 2: Identifying Homogeneous Pixels ..................................................... 49 2.2.3 Step 3: The Cluster Tree ............................................................................... 50 2.2.4 Step 4: Assignment of Super-Resolved Values............................................ 51 2.2.5 Step 5: Radiometric Correction ................................................................... 52 2.3 TESTING METHODOLOGY ......................................................................... 53 2.3.1 Datasets ........................................................................................................... 53 2.3.2 Step 1 Testing Methodology ......................................................................... 57 2.3.3 Step 2 Testing Methodology ......................................................................... 57 2.3.4 Step 3 Testing Methodology ......................................................................... 58 2.3.5 Step 4 Testing Methodology ......................................................................... 58 2.3.6 Step 5 Testing Methodology ......................................................................... 59 2.4 RESULTS ........................................................................................................... 60 2.4.1 Step 1 Results ................................................................................................. 60 2.4.2 Step 2 Results ................................................................................................. 62 2.4.3 Step 3 Results ................................................................................................. 63 2.4.4 Step 4 Results ................................................................................................. 66 2.4.5 Step 5 Results ................................................................................................. 66 2.5 DISCUSSION ..................................................................................................... 71 2.5.1 Step 1 Discussion ............................................................................................ 71 2.5.2 Step 2 Discussion ............................................................................................ 72 2.5.3 Step 3 Discussion ............................................................................................ 73 vii 2.5.4 Step 4 Discussion ............................................................................................ 75 2.5.5 Step 5 Discussion ............................................................................................ 77 2.6 CONCLUSION .................................................................................................. 78 3.0 SUPER-RESOLUTION OF A PUTATIVE CHLORIDE SITE ON MARS ........ 81 3.1 INTRODUCTION ............................................................................................. 81 3.1.1 Evaporites on Earth....................................................................................... 83 3.1.2 Putative Chlorides on Mars .......................................................................... 84 3.1.3 Approach ........................................................................................................ 86 3.2 METHODOLOGY ............................................................................................ 87 3.2.1 Data Collection ............................................................................................... 87 3.2.2 Site Location ................................................................................................... 88 3.2.3 Super-Resolution ........................................................................................... 89 3.2.4 Linear Deconvolution .................................................................................... 92 3.3 RESULTS ..........................................................................................................
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