EXPLORING LEAST COST PATH ANALYSIS: A CASE STUDY FROM THE GÖKSU VALLEY, TURKEY A Thesis Submitted to the Committee of Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Master on Arts in the Faculty of Arts and Science TRENT UNIVERSITY Peterborough, Ontario, Canada (c) Copyright by Nayla Abu Izzeddin (2014) Anthropology M.A. Graduate Program September 2014 Abstract Exploring Least Cost Path Analysis: A Case Study From the Göksu Valley, Turkey Nayla Abu Izzeddin Least cost path analysis is considered by many scholars as being a good proxy for studying movement and interactions between sites in the landscape. Although it is widely used, there are many limitations and challenges yet to be overcome concerning the reliability of the results. The examples used from the Göksu Valley during the late Roman Imperial rule emphasize the need to clearly understand how the tool works in generating least cost paths and how these can be interpreted and related to human movement. The resolution and accuracy of the elevation data used also play an important role in least cost path analysis and these depend on the topographical area being studied. New venues are constantly being sought and the success of any analysis depends on how the results are compared and tested in concert with data obtained from various sources and through more visually advanced mapping software. Keywords: Least cost path; Göksu Valley; late Roman Imperial rule; DEM resolution and accuracy ii Acknowledgments It was that day in April (2011) I was at Istanbul airport running to catch my flight to Beirut, my home town, for a short vacation prior to writing my Masters dissertation for the University of Birmingham. I received two emails from Dr. Hugh Elton in this very brief instant where I had internet connection on my phone. These two minutes or so changed my world, made me realize that I am about to embark on a journey full of challenges and gratifications, filled with excitement and hope, a hope to grow. And this would have not been possible without the support and trust Dr. Elton put in me, a trust which made this opportunity an unforgettable and unmatchable one. I am thankful and honored to have had the opportunity to spend this valuable time with him, learning and growing with every comment or remark I received. Many sincere thanks to Dr. Elton who was an incredible advisor to me. Also many thanks to Dr. James Conolly whom I am honored to have worked with and for always providing his help and support when needed. A special thanks to Dr. Jennifer Moore whom I admire and who inspired me greatly on different levels. I would also like to thank Dr. Jocelyn Williams for trusting and believing in my capabilities and for giving me the opportunity to TA with her again. Many thanks to Kristine Williams for her support and encouragement along the way, and for all her help, and to Kate Dougherty for the great time spent together and for always being available for assistance. Also many big thanks to my colleagues and friends whom made this experience more enjoyable and fun especially in stressful times. Thanks to Amandah for all the time we got to spend together debating and talking about everything and anything, for being patient with me, Kat for the endless provision of wine always, Jessica for iii always pushing me to play squash with her and to Christa, Kristin, Dan, and Jack (it was always fun to bump into you at clubs!!). I would like to thank also all my friends whom made my time spent in Peterborough an unforgettable one and made life so much easier and especially to all who believed in me and my abilities and admired the determination I had towards my endeavors and always encouraged me no matter how stressed and worried I was. Finally I would like to thank my family for all their support and especially my dad, for without him none of this would have been possible. I want to thank him for his countless encouragements (such as “You are Nayla the Great”), for believing in me and supporting my plans no matter how crazy they were. Thank you all for all you have provided me with and big thanks to Trent University for providing such a great environment to work in. iv Table of Contents Abstract ii Acknowledgments iii Table of Contents v List of Tables vii List of Figures vii Chapter 1: GIS, Isauria and the late Roman Imperial period 1 1. Introduction 1 1.2. Movement and GIS 3 1.2.1. GIS development 5 1.3. Isauria and the study area 8 1.3.1. General view 8 1.3.2. The late Roman Imperial rule and the valley 11 1.4. Previous Works 16 1.4.1. GAP survey project 17 1.5. Aims and Objectives 21 Chapter 2: Theory of GIS and Challenges 23 2.1. Least Cost Path Analyses 23 2.1.1. Technical aspect 24 2.1.2. Challenges and Limitations 28 2.2. Previous Works 29 2.2.1. Case studies 31 2.3. Discussion and Conclusion 33 Chapter 3: Digital Elevation Models and GIS 37 3.1. Digital Elevation Models and data capture 37 3.1.1. DEM creation: survey points 37 3.2. Remote Sensing 40 3.2.1. Collection of raw data 41 3.2.2. SRTMs 43 3.3. DEMs in ArcGIS 45 3.3.1. “Size does matter”: 47 3.4. Slope and Cost surfaces 48 v 3.4.1. Creating cumulative cost surfaces 54 3.4.2. Anisotropism and direction of movement 55 3.4.3. Slope in ArcGIS 59 3.5. Conclusion: 60 Chapter 4: Cost Surfaces and Least Cost Paths 62 4.1. Resolution and Accuracy 62 4.2. Least Cost Path Analysis: 64 4.2.1. Distance Analysis 65 4.2.2. Least Cost Path and neighborhoods selection 67 4.3. Conclusion 71 Chapter 5: A case study from the Göksu Valley 73 5.1. Working with the DEM 74 5.1.1. DEM values: 74 5.2. DEM cell size, resolution, resampling 79 5.2.1. Resampled DEMs: interpolation 81 5.2.2. Resampled DEMs: resolutions 86 5.3. Adding Rivers and Bridges 90 5.3.1. The Göksu River cost surface 92 5.4. Analysis 3: Dağpazarı -Karaman 97 5.4.1. Google Earth 104 5.5. Conclusion 108 Chapter 6: Interpretation and Conclusion 111 6.1. Summary 112 6.2. Results 114 6.2.1. Late Roman Isauria 115 6.3. Computers vs. Humans 117 6.4. Conclusion 121 Appendix 1: Trip report 123 Appendix 2: Least Cost Path Analysis in ArcGIS 10 133 Bibliography 140 vi List of Tables Table 1. Data types definition. 27 Table 2. Raster Data. 28 Table 3. Variation in generating least cost paths 57 Table 4. Least Cost Path Analysis from Mut to Ermenek: Adjusting cell values 76 Table 5. Resampling the DEM: four interpolation options. 84 Table 6. Least cost paths from Mut to Ermenek on different resolutions. 87 Table 7. Least cost path analysis with river and bridges: Mut-Ermenek and Mut- Adrassus 95 Table 8. Least Cost Path Comparison of two different topographical areas. 98 Table 9. Least cost path generated from resampled DEMs 101 Table 10. Topographical differences between both areas. 103 List of Figures Figure 1. The Göksu Valley Study Area 12 Figure 2. Location of sinks in the DEM 45 Figure 3. Slope calculation in degrees and percent rise 51 Figure 4. Figure extracted from Bell et al. 2002: 175 52 Figure 5. Least Cost Path Analysis from Mut to Ermenek: Adjusting cell values 79 Figure 6. Resampling the DEM: four interpolation options. 85 Figure 7. Least cost paths from Mut to Ermenek on different resolutions 89 Figure 8. Figure representing the slope effort based on Bell et al (2002) and taken from Newhard et al. (2008) 92 Figure 9. Least cost path analysis with river and bridges: Mut-Ermenek and Mut- Adrassus 96 Figure 10. Least cost path from Dağpazarı to Karaman. 99 Figure 11. Least cost path analysis from Dağpazarı to Karaman 102 Figure 12. Least cost path analysis from Dağpazarı to Karaman 103 Figure 13. Least cost path analysis in the Göksu Valley 106 Figure 15. Google Earth, least cost path in the Göksu Valley 107 Figure 16. Google Earth, least cost path in the Göksu Valley 108 Figure 17. ArcGIS data frame and search tool engine. 133 Figure 18. Working with the DEM. 135 Figure 19. Setting the coordinates framework. 136 Figure 20. Buffer tool. 138 Figure 21. Reclassifying the slope raster. 139 vii Chapter 1: GIS, Isauria and the late Roman Imperial period 1. Introduction The main objective of the research presented here is to take a critical look at GIS software and in particular at the least cost path tool provided by ArcGIS 10. Much of the constructive criticism that has been made concerning the limitation of this tool relies on failure of the software to take into account the cognitive and behavioral aspects when quantifying past human movement in a landscape. Less focus in the literature is found concerning the technical capabilities and limitations of GIS software; in particular, rarely does any study made so far explore in detail how the tool works; and most show less awareness that many different results could be generated for the same route that is being predicted. The challenge remains in choosing the path that fits best the research questions and objectives of any given study. The case study used in this thesis denotes technical and computational issues within GIS by using an example from the Göksu Valley locating potential roads and exploring movement and interactions between the late Roman cities of Mut and Ermenek on the one hand and Karaman and Dağpazarı on the other.