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Pattern Recognition and Feature Extraction Using Lidar-Derived

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Pattern Recognition and Feature Extraction Using Lidar-Derived PATTERN RECOGNITION AND FEATURE EXTRACTION USING LIDAR-DERIVED ELEVATION MODELS IN GIS: A COMPARISON BETWEEN VISUALIZATION TECHNIQUES AND AUTOMATED METHODS FOR IDENTIFYING PREHISTORIC DITCH-FORTIFIED SITES IN NORTH DAKOTA A Thesis Submitted to the Graduate Faculty of the North Dakota State University of Agriculture and Applied Science By Matthew Jeffery Radermacher In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Major Department: Sociology and Anthropology October 2016 Fargo, North Dakota North Dakota State University Graduate School Title Pattern recognition and feature extraction using lidar-derived elevation models in GIS: a comparison between visualization techniques and automated methods for identifying prehistoric ditch-fortified village sites in North Dakota By Matthew J. Radermacher The Supervisory Committee certifies that this disquisition complies with North Dakota State University’s regulations and meets the accepted standards for the degree of MASTER OF SCIENCE SUPERVISORY COMMITTEE: Jeffrey T. Clark Chair Thomas Riley Stephanie Day Michael Michlovic Approved: 10/11/2016 Jeffrey Bumgarner Date Department Chair ABSTRACT As technologies advance in the fields of geology and computer science, new methods in remote sensing, including data acquisition and analyses, make it possible to accurately model diverse landscapes. Archaeological applications of these systems are becoming increasingly popular, especially in regards to site prospection and the geospatial analysis of cultural features. Different methodologies were used to identify fortified ditch features of anthropogenic origin using aerial lidar from known prehistoric sites in North Dakota. The results were compared in an attempt to develop a system aimed at detecting similar, unrecorded morphological features on the landscape. The successful development of this program will allow archaeological investigators to review topography and locate specific features on the surface that otherwise could be difficult to identify as a result of poor visibility in the field. iii ACKNOWLEDGMENTS This research would not have been possible without the hard work and dedication of the talented individuals from the Computer Science, Geoscience, and Sociology/Anthropology departments at North Dakota State University. The members of this multi-disciplinary team brought distinct expertise and skills to make this project a success. These individuals include Project Director and GIS specialist Stephanie Day, Professor Emeritus of Geology Donald Schwert, Professor of Anthropology Jeffrey Clark, Assistant Professor of Anthropology (University of Hawaii) Seth Quintus, Professor of Computer Science Anne Denton, and graduate students Shuhang Li and Nolita Motu. Special thanks to ND NASA EPSCoR for providing the seed money and the original grant writers for making this project a reality. Lastly, none of this would have been possible without funding and support from North Dakota State University. This institution provided the technology that made this project a possibility and without that, it would have been nothing more than an idea. Thanks to Thesis committee members Jeffrey Clark (Chair), Thomas Riley, Stephanie Day, and Michael Michlovic for providing advice and guidance throughout this entire process. Special thanks to Kate Ulmer for assisting with administrative support. Finally, I would like to thank Ava, Eli, my wife Trista, and the rest of my family and friends, for tolerating me during the last couple of years and giving me the motivation and will to complete this… it would not have been possible without any of you. iv TABLE OF CONTENTS ABSTRACT ................................................................................................................................... iii ACKNOWLEDGMENTS ............................................................................................................. iv LIST OF TABLES ....................................................................................................................... viii LIST OF FIGURES ....................................................................................................................... ix LIST OF ABBREVIATIONS ....................................................................................................... xii LIST OF APPENDIX TABLES .................................................................................................. xiii CHAPTER 1. INTRODUCTION .................................................................................................. 1 Environmental Setting ........................................................................................................ 3 Sites and Features ............................................................................................................... 5 Research Questions ............................................................................................................. 6 Thesis Organization ............................................................................................................ 7 CHAPTER 2. BACKGROUND .................................................................................................... 9 Computer Applications and Archaeology ........................................................................... 9 GIS and Spatial Technologies ........................................................................................... 10 Remote Sensing and lidar ................................................................................................. 13 Visualization Techniques .................................................................................................. 17 Automatic Feature Extraction ........................................................................................... 20 CHAPTER 3. RESEARCH OBJECTIVES AND METHODS ................................................... 23 Research Objectives .......................................................................................................... 23 Methods............................................................................................................................. 24 Data Acquisition, Preprocessing, and Visualization Tools ................................... 24 Semi-automated Feature Detection ....................................................................... 27 Automated Extraction Algorithm ......................................................................... 29 v Visual Inspection and Output Analysis................................................................. 33 CHAPTER 4. LOCAL ENVIRONMENT AND CULTURES ................................................... 34 Bend Region...................................................................................................................... 34 Cultural Traditions ............................................................................................................ 35 Fortification Ditches ......................................................................................................... 37 Test Sites ........................................................................................................................... 39 Shea Site (32CS101) ............................................................................................. 40 Sprunk Site (32CS4478) ....................................................................................... 41 Biesterfeldt Site (32RM1) ..................................................................................... 43 Lucas Site (32RM225) .......................................................................................... 44 Peterson Site (32RM401) ...................................................................................... 46 Nelson Site (32RM402 ......................................................................................... 47 Summary ........................................................................................................................... 48 CHAPTER 5. RESULTS AND DISCUSSION ........................................................................... 49 Visualization Results ........................................................................................................ 49 Semi-automated Detection Results ................................................................................... 56 Automated Extraction Results .......................................................................................... 87 Discussion ......................................................................................................................... 91 Visualizations ........................................................................................................ 91 Semi-automated Detection .................................................................................... 93 Automated Extraction ........................................................................................... 94 Troubleshooting .................................................................................................... 95 CHAPTER 6. CONCLUSIONS .................................................................................................. 97 Additional Areas ............................................................................................................... 99 Moving Forward ............................................................................................................. 101 vi
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