Relationship Between Settlement Location and Morphological Landform: a Gis Method Applied to Çankiri Province

RELATIONSHIP BETWEEN SETTLEMENT LOCATION AND MORPHOLOGICAL LANDFORM: A GIS METHOD APPLIED TO ÇANKIRI PROVINCE

A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF THE MIDDLE EAST TECHNICAL UNIVERSITY

BİRİCİK GÖZDE SÜRMELİ

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN THE DEPARTMENT OF GEODETIC AND GEOGRAPHIC INFORMATION TECHNOLOGIES

JULY 2003

Approval of the Graduate School of Natural and Applied Sciences

Prof. Dr. Canan ÖZGEN Director

I certify that this thesis satisfies all the requirements as a thesis for the degree of Master of Science.

Assoc. Prof. Dr. Oğuz IŞIK Head of Department

This is to certify that we have read this thesis and that in our opinion it is fully adequate, in scope and quality, as a thesis for the degree of Master of Science.

Assoc. Prof. Dr. Vedat TOPRAK Supervisor

Examining Committee Members

Assoc. Prof. Dr. Oğuz IŞIK

Assoc. Prof. Dr. Vedat TOPRAK

Assist. Prof. Dr. Mustafa TÜRKER

Assist. Prof. Dr. Zuhal AKYÜREK

Assist Prof. Dr. Şebnem DÜZGÜN

ABSTRACT

RELATIONSHIP BETWEEN SETTLEMENT LOCATION AND MORPHOLOGICAL LANDFORM: A GIS METHOD APPLIED TO ÇANKIRI PROVINCE

Sürmeli, Biricik Gözde M. Sc., Department of Geodetic and Geographical Information Technologies Supervisor: Assoc. Prof. Dr. Vedat Toprak

July 2003, 96 pages

This study aims to develop a method to investigate the relationship between settlement locations and the morphological landforms using geographical information systems (GIS). The method is applied to Çankırı province, a mountainous terrain, which is covered in seventy-seven sheets of topographic maps at 1:25.000 scale.

Three databases are created and used in this study: 1) Settlement database comprising various topographic and landform attributes of 891 settlements, 2) Morphological landform database composed of 4042 landform polygon elements digitized from 1:25.000 topographic maps, and 3) Topographic database containing the digital elevation model of the area and its derivatives.

The first step in the algorithm is to classify the area into four main landform classes, namely, valley, slope, flood and top. Unsuitable landforms are then clipped out based on the thresholds derived from three topographic properties (elevation, slope and aspect). Accordingly, about 2 % of the settlements and 12 % of the area are removed. The relationship is investigated using the percentages of remaining settlements and landform classes. Further analyses such as position of the settlement within the landform polygon and type of the nearest landforms are carried out for final interpretation.

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Following conclusions are reached on the relationship between settlement location and morphological landforms: - Percentages of settlements for flood, valley, slope and top are 8.37, 27.52, 58.60 and 5.50, respectively. Considering the percentages of the landforms provided in the area, however, valley is the most preferred landform followed by flood type. Slope and top landforms are less preferred. About 86 % of the settlements are concentrated along valley-slope boundary. - Morphological boundaries of flood and top landforms are consistent with the settlement zones. The valley-slope boundary, on the other hand, which is the most populated area, cross-cut the settlements zones.

Keywords: Geographical Information Systems, settlement location, landform classification, topography, Çankırı

ÖZ

YERLEŞİM YERİ VE ARAZİ ŞEKLİ İLİŞKİSİ: ÇANKIRI İLİNE UYGULANAN BİR CBS YÖNTEMİ

Sürmeli, Biricik Gözde Yüksek Lisans, Jeodezi Ve Coğrafi Bilgi Teknolojileri Tez Yöneticisi: Doç. Dr. Vedat Toprak

Temmuz 2003, 96 sayfa

Bu çalışma coğrafi bilgi sistemleri (CBS) kullanılarak yerleşim yerleri ile arazi biçimi arasındaki ilişkiyi inceleyen bir yöntem geliştirmeyi amaçlamaktadır. Yöntem, dağlık bir alan olan ve 77 adet 1:25.000 ölçekli topoğrafik haritayı kapsayan Çankırı ilinde uygulanmıştır.

Bu çalışmada üç veritabanı oluşturulmuş ve kullanılmıştır: 1) 891 yerleşimin topografik ve arazi şekli ile ilgili öznitelik verilerini içeren yerleşim veritabanı, 2) 1:25.000 ölçekli haritalardan sayısallaştırılan 4042 adet arazi şekli poligonuna ait verileri içeren morfolojik veritabanı, ve 3) Alanın sayısal yükseklik modeli ve bundan üretilen türevleri içeren topografik veritabanı.

Algoritmanın birinci aşaması alanı dört ana arazi biçimine (taşkın, vadi, yamaç ve tepe) sınıflamak olmuştur. Uygun olmayan alanlar, üç topografik parametreden (yükseklik, eğim ve bakı) elde edilen eşik değerler kullanılarak çıkarılmıştır. Buna gore yerleşimlerin % 2’si, alanın ise % 12’si elenmiştir. Geriye kalan yerleşim ve arazi yüzdeleri kullanılarak ikisi arasındaki ilişki incelenmiştir. Son yorumlara ulaşabilmek için, yerleşimin arazi şekli poligonu içindeki konumu ve yerleşime en yakın diğer arazi şekli gibi ek analizler yapılmıştır.

v Yerleşim yerleri ile arazi şekli arasındaki ilişki hakkında şu sonuçlara ulaşılmıştır.:

- Taşkın, vadi, yamaç ve tepe arazi şekilleri içindeki yerleşim yüzdeleri sırasıyla, 8.37, 27.52, 58.60 ve 5.50’dir. Ancak alanda sağlanan yüzdeler gözönüne alındığında, en fazla tercih edilen arazi biçimi vadi olup, bunu taşkın takip etmektedir. Yamaç ve tepe daha az tercih edilmiştir. Yerleşimlerin yaklaşık % 86 ‘sı vadi-yamaç sınırında yoğunlaşmıştır. - Taşkın ve tepe arazi şekillerinin morfolojik sınırları yerleşim kuşakları ile uyumlu çıkmaktadır. Öte yandan, en yoğun olarak kullanılan vadi-yamaç sınırı, yerleşim kuşaklarını kesmektedir.

Anahtar Kelimeler: Coğrafi Bilgi Sistemleri, yerleşim yeri, arazi şekli sınıflandırılması, topoğrafya, Çankırı

To My Family

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ACKNOWLEDGMENTS

I am happy to find many people around along the way of preparation of this thesis. The word “thank you” is not enough to express my feelings but it is all I have right now.

At first, I am sincerely in debt to my advisor Dr.Vedat Toprak for his fantastic guidance, continuous support and unlimited thrust at every stage of this study. He is not only a good advisor and a teacher but also a very good friend. It has been my good fortune to be able to study with him. Thank you so much...

I would like to express my special thanks to Dr.M.Lütfi Süzen, Dr.Arda Arcasoy and Dr.Nuretdin Kaymakcı for their valuable contributions, support and help. It was great to see different point of views each time. Thank you for sharing your ideas and your time without any hesitation. Thanks a lot...

I want to thank to Çağıl Kolat for her efforts to help me and trying to find something that she can do for me. Most of times you thought with me and owned my problems like yours, it is really inestimable. Thank you for your patience, your helps and friendship. It is nice to have meals with you!!! And I still believe that you should not listen to Chicago so much!!! Thank you... Deniz Gerçek is thanked for the technical aid and giving me her precious time so much and teaching me a lot of things. If she were not be there, TNTMips would be a big big problem for me. It is nice to meet you.

I would like to thank to my professor Dr.Oğuz Işık for his helps, sharing his ideas and wonderful guiding not only during this program but also throughout my undergraduate studies.

I gratefully acknowledge to my professors in Geodetic and Geographical Information Technologies Department, METU, for giving me their valuable time and for sharing their valuable comments during this graduate program.

viii Balkan Uraz, you are the one always encouraging and guiding. Great thanks for your helps and for your brain-storming sessions. It is nice to have a friend to ask anything at any time without hesitating. Özgün Balkanay, even you have a lot of problems you owned my problems as yours and tried to solve them with me. Kıvanç Ertuğay should be thanked for his effort to try to answer my questions. I thank to Mahmut Arıkan for thinking hard on my problem even he was so busy. All of you may be aware of it or may be not but it is a fact that each of you helped me a lot not only throughout the preparation of this thesis but also during these two years. Specially Ayşegül Domaç, Ece Aksoy, Dilek Koç, Ebru Akpınar, İpek Yavuzer, Nilhan Çiftçi, Taner San. It is glad to share those two years with you. But the most I want to thank all of you for your smiling faces. Thank you...

My friends are thanked for their support and presence. All of you belive in me not only throughout this study but for every step in my life. I am so happy to be one of your friend. Among them, thanks to Geray Aktimur for giving me his time and chatting me during the times I was desperate. Thanks to İpek Yavuzer (again) for your friendship, your helps and your dance lessons. Those were really enjoyable and great discharging times.

I want to express my deep thanks to my relatives (not only the ones being with me as physical means but also the ones in the heaven) for being with me during this study. I am so glad to be a part of this big and golden family. Your “presence” and “spirit” give me the power to achieve so many difficulties in every part of my life.

I would like to express my special thanks to A. Arda Özacar for being one of my best friends and supporters. Thank you for being so patient to me and thank you for your unlimited encouragements and sorry if I had afflicted you so much throughout this work. It is unbelievable that you believe in me more than I do! You are the special one. Thank you...

Finally but the most, I send my very special thanks to my family. I would like to show them my sincere gratitude to my lovely parents Tülin and B. Aksın Sürmeli and my dearest brother M.Göker Sürmeli and my sweetest Çakıl for their unbelievable supports even I did wrongs throughout my life. They are the ones believing in me every time the most. Thank you for your continuous encouragements, patience and trust. I know this study is not a big one but I would be happy if you accept my dedication of this work to you.

At last I want to express my apologies all of you for my irritating moods (if any!!!!) during this study. And I know that I will need all of you and your supports with me in the future. I hope each of you will be there in some way. Thanks to all of you...

TABLE OF CONTENTS

ABSTRACT ...... iii ÖZ ...... v DEDICATION ...... vii ACKNOWLEDGMENTS ...... viii TABLE OF CONTENTS ...... x LIST OF TABLES ...... xii LIST OF FIGURES ...... xiii CHAPTER 1. INTRODUCTION ...... 1 1.1. Purpose and Scope ...... 1 1.2. Study Area ...... 2 1.3. Method of Study ...... 4 1.4. Organization of Thesis ...... 4 2. PREVIOUS STUDIES ...... 5 2.1. Studies on the Classification of Morphological Landforms ...... 5 2.2. Studies on the Location of Settlements ...... 11 3. DATA AND DATA PRODUCTION ...... 19 3.1. Topographic Data ...... 19 3.1.1. Elevation Map ...... 21 3.1.2. Slope Map ...... 22 3.1.3. Aspect Map ...... 22 3.2. Morphological Landform Classes ...... 25 3.2.1. Flood Landform ...... 31 3.2.2. Valley Landform ...... 33 3.2.3. Slope Landform ...... 35 3.2.4. Top Landform ...... 37 3.3 Settlement Data ...... 39 3.3.1. Settlement and Topography ...... 41 3.3.2. Settlement Location and Morphological Landform ...... 42

x 4. METHOD AND DATA ANALYSIS ...... 45 4.1. Removing Unsuitable Areas ...... 47 4.1.1. Masking Analysis ...... 47 4.1.2. Weighting Analysis ...... 53 4.1.3. Evaluation of Discarded Data ...... 55 4.2. Investigation of Relationship between Settlement Locations and Morphological Landform Classes ...... 61 4.2.1. Settlement Location versus Morphological Landform Class . . 61 4.2.2. Distance Ratio ...... 63 4.2.3. Nearest Landform ...... 66 4.3. Interpretation of Results ...... 67 5. DISCUSSION ...... 68 5.1. Algorithm and Structure of Method ...... 68 5.2. Data and Process ...... 69 5.3. Results of the Analyses ...... 71 6. CONCLUSIONS AND RECOMMENDATIONS ...... 73 REFERENCES ...... 75 APPENDIX Settlement Database ...... 79

LIST OF TABLES

TABLES

2.1. Landform classification used by Dikau et al. (1991) ...... 7 2.2. GIS layers and their rankings assigned by Choquette and Valdal (2000) ...... 17 3.1. Aspect ranges applied in this study ...... 22 3.2. Basic statistics of landform classes digitized in this study ...... 30 3.3. Frequency and percentages of settlements for each landform class ...... 42 4.1. Comparison of landform percentages for settlements and the area ...... 45 4.2. Topographic thresholds for masking analysis ...... 47 4.3. Final score of any pixel with different combinations of 3 topographic parameters . . 49 4.4. Percentages of the eight classes shown in Figure 4.3 ...... 50 4.5. Weights calculated for the intervals of topographic parameters ...... 53 4.6. Relative weights of three topographic parameters ...... 54 4.7. Discarded settlements and areas due to three different methods ...... 56 4.8. Topographic and landform properties of discarded settlements ...... 56 4.9. Percentages of discarded landform due to masking analysis ...... 58 4.10. Final scores of the landforms ...... 61 4.11. Frequency and percentages of the settlements for 3 scores ...... 61 4.12. Results of the Nearest Landform Analysis ...... 66

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LIST OF FIGURES

FIGURES

1.1. Location map of the study area ...... 3 2.1. The major classes, sub-classes and resultant map of Hammond’s (1964) method ...... 6 2.2. The six categories of morphometric features illustrated by the relationship between a central DEM cell and its eight neighbors ...... 8 2.3. Morphological landform classification for Çankırı province ...... 10 2.4. Simplified algorithm of “contextual merging” ...... 11 2.5. Results of Romstad’s (2001) method ...... 12 2.6. Time-slice snapshots representing change in a lake and settlement pattern . . . . 18 3.1. Simplified flowchart showing data production for further analysis ...... 20 3.2. Digital Elevation Model of the study area with 100 m cell size ...... 23 3.3. Elevation (A), Slope (B), and Aspect (C) maps of the study area ...... 24 3.4. Histograms and descriptive statistics for elevation, slope and aspect maps . . . . . 26 3.5. The Landform classes used in this study ...... 28 3.6. Morphological landform map of the area ...... 29 3.7. Spatial distribution of each morphological landform class ...... 30 3.8. Distribution percentages of morphological landform classes on the topography . . . 31 3.9. Examples of flood areas ...... 32 3.10. Topographic attributes of flood landform ...... 33 3.11. Examples of valley areas ...... 34 3.12. Topographic attributes of valley landform ...... 35 3.13. Examples of slope areas ...... 36 3.14. Topographic attributes of slope landform ...... 37 3.15. Examples of top areas ...... 38 3.16. Topographic attributes of slope landform ...... 40 3.17. A general view of Çankırı ...... 40 3.18. Distribution of 891 settlements (red points) in the study area ...... 41 3.19. Histograms and basic statistics of topographic parameters for settlements . . . . 42

xiii 3.20. Settlement morphological landform class histogram ...... 43 3.21. Examples of settlements in relation to landform classes ...... 44 4.1. Flowchart of the method ...... 46 4.2. Histograms obtained by subtracting settlement percentages from the topography percentages for elevation, slope and aspect ...... 48 4.3. Spatial distribution of eight classes based on three topographic parameters . . . . 50 4.4. Areas discarded due to all three topographic parameters (-3 score) ...... 52 4.5. Areas discarded due to at least two topographic parameters (-3 and -1 scores) . . 52 4.6. Results of the weighting analysis showing final scores over the whole area . . . . . 54 4.7. Areas discarded after the weighting analysis ...... 55 4.8. Location of discarded settlements ...... 57 4.9. Examples of removed flood landforms ...... 58 4.10. Examples of removed valley landforms ...... 58 4.11. Examples of removed slope landforms ...... 58 4.12. Examples of removed top landforms ...... 58 4.13. Distribution of discarded landform within the study area ...... 60 4.14. Resultant histogram showing preferred and avoided landform classes ...... 62 4.15. Measuring required distances ...... 64 4.16. Histograms for the distance ratio for four landform settlements ...... 65 4.17. Final interpretation of settlement positions ...... 67

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CHAPTER I

INTRODUCTION

1.1. Purpose and Scope

Settlements refer to the land, on which people are living, used for human habitation. Settlements are the embodied appearances of the social interactions and organizations of space (Roberts, 1996). As it has been asked for a long time “why settlements are founded in particular places, why some places are settled and others are not?” (Hugget and Cheesman, 2001) there can be several various answers to such questions. Variety of answers is a result of different point of views of various disciplines, different interest areas which shows that settlement locations are not influenced by only one factor. In order to answer such questions natural environment, social and cultural factors and economic activities of the people are important points.

Huggett and Cheesman (2001) define topography as the lie of the land or the general configuration of the land surface, including its relief and the location of its features, natural and human made. Since topography has a role as an environmental factor influencing the natural events such as climate, flora, resources, morphological landforms, soil types etc., it affects the locations of settlements because settlement sites are the manifestations of the various events which are the results of natural environment and also social, cultural and economic activities.

Morphological landforms are the results of biophysical processes that shape the land and create the differences between one place to another (Hough 1990). Morphological landform studies are going on over several different disciplines such as archaeology, geography, geomorphology etc. Each discipline develops a morphological landform concept according to their own point of view. This causes problems on exchanging ideas between different disciplines and on confusing concepts. As Bourassa (1991) pointed out, morphological landform classification must be based on explicit definitions since it is a fact that different observers view the landscape in different way.

1 Even though landscapes are heterogeneous in nature, it is necessary to identify homogeneity in order to classify them. Evidence of people's understanding of landform classification is demonstrated by common daily words, such as "mountainous", “flat" or “valley” etc. which are describing morphological landform classes. People dealing with the settlements for long years try to find out some relations between the locations of settlements and the morphological factors that control this location.

The main objective of this thesis is to investigate the relationship between settlement sites and the morphological landform classes. The study does not attempt to create substantive rules of morphological landform classes but focuses only on the relationship between settlement and previously defined landform classes.

The study attempts to develop a method to seek a relationship between landform classes and settlement sites. GIS is used as a tool in the study to understand this relationship. One of the main assumptions in this study is that the method does not take the factors influencing the settlement locations other than topographic conditions into consideration. Examples of such influencing factors are suitable climate, soil type, vegetation type, proximity to natural resources, and other social, cultural and economic activities.

The method will be applied to Çankırı Province because of data availability and suitable topographic conditions in the region. Çankırı Province is characterized by a mountainous landform that possesses different landform classes.

This study intends to offer a framework for anyone interested in the investigation of this relationship. People dealing with the prediction of historical settlement sites and investigating such relations between settlement locations and various factors, including researchers interested in archaeology, geo-archaeology, physical geography, geomorphology etc. concerned with the implementations of GIS will find material of interest in this thesis.

1.2. Study Area

The study area, Çankırı Province, encloses northeast of Ankara, Turkey, covering approximately an 8380 km2 (Figure 1.1). The projection system is defined as Universal Transverse Mercator (UTM) with 36 North Zone in European 1950 Mean Datum. The study area is covered within seventy-seven 1:25.000 scale topographic maps. There are several major rivers crossing the area. Kızılırmak, Devrezçayı, Acıçay, Melançayı, Soğançay, Termeçay and Uluçay are examples of these streams. Elevation in the area ranges from 400 m to 2400 m at Ilgaz Mountain.

28 29 30 31 32

F28-c1 F28-c2 F29-d1 F29-d2 F29-c1 F29-c2 F30-d1 F30-d2 F30-c1 F30-c2 F31-d1 F31-d2 F31-c1 F31-c2

F Ovacik

F28-c4 F28-c3 F29-d4 F29-d3 F29-c4 F29-c3 F30-d4 F30-d3 F30-c4 F30-c3 F31-d4 F31-d3 F31-c4 F31-c3

Bayramoren Eskipazar Ilgaz G28-b1 G28-b2 G29-a1 G29-a2 G29-b1 G29-b2 G30-a1 G30-a2 G30-b1 G30-b2 G31-a1 G31-a2 G31-b1 G31-b2 G32-a1 G32-a2 Devrez Kursunlu Cerkes Atkaracalar

G28-b4 G28-b3 G29-a4 G29-a3 G29-b4 G29-b3 G30-a4 G30-a3 G30-b4 G30-b3 G31-a4 G31-a3 G31-b4 G31-b3 G32-a4 G32-a3

G Korgun Yaprakli

G29-d1 G29-d2 G29-c1 G29-c2 G30-d1 G30-d2 G30-c1 G30-c2 G31-d1 G31-d2 G31-c1 G31-c2 G32-d1 G32-d2 Orta CANKIRI G29-c4 G29-c3 G30-d4 G30-d3 G30-c4 G30-c3 G31-d4 G31-d3 G31-c4 G31-c3 G32-d4 G32-d3 Eldivan

Sabanozu H29-b1 H29-b2 H30a-1 H30-a2 H30b-1 H30-b2 H31-a1 H31-a2 H31-b1 H31-b2 H32-a1 H32-a2 H N Kýzýlýrma k Kizilirmak H30-a4 H30-a3 H30-b4 H30-b3 H31-a4 H31-a3 H31-b4 H31-b3 H32-a4 H32-a3

Figure 1.1. Location map of the study area. Grey rectangles are 1:25.000 scale topographic maps. Blue lines show major streams in the study area.

3 1.3. Method of Study

Most of this thesis is completed as an office work. Daily field trips are organized to the area in order to get familiar to morphological landform and to take pictures.

The office work is composed mainly of computer utilities such as digitizing, creation of database and processing. Following software packages are used during the studies: - TNTMips 6.2 for georefrencing, digitizing, editing and raster operations. - ArcGIS 8.1 for getting slope and aspect maps. - Excel XP for comparing each result and getting histograms. - Map Info 6.5 for converting data.

1.4. Organization of Thesis

The rest of this thesis is organized as follows:

Chapter 2 reviews related works on landform classification studies and prediction of settlement location studies. Chapter 3 presents data that are used in the study. In that chapter, three data sets, the processing steps and the results are introduced. Chapter 4 describes the method and the analysis carried out for the investigation of the relationship between settlement locations and the morphological landform classes. Chapter 5 is the discussion part of the thesis. The results and also the problems faced are discussed and explained. Chapter 6 presents conclusion and recommendations for the future studies.

CHAPTER II

PREVIOUS STUDIES

In this chapter the previous studies compiled from literature will be explained. The chapter is divided into two parts as: 1) Studies on the classification of morphological landform, 2) Studies investigating location of settlements. Studies in each section will be explained in chronological order starting from the oldest one. Literature on the spatial distribution of settlements, different models applied to evaluate this distribution, patterns formed by such distributions and related subjects are excluded in this compilation. Such applications are common search topics among archaeologists and uses basically statistical methods to evaluate the data sets. A comprehensive example of such study is Hodder and Clive’s (1976) book that explains various statistical models applied to settlement database.

2.1. Studies on the classification of morphological landforms

The main interests of this type of studies are classification of landform types, extraction of landform components, accuracy of Digital Elevation Model (DEM) and modeling of landform.

Hammond (1964) suggests a method based on explicit, quantitative procedures to describe different landforms. For each landform he calculates: 1) percentage of area where the ground was flat or gentle (less than 8 % slope), 2) relative relief (max - min elevation), and 3) profile type (relative proportion of flat or gently sloping terrain in upland areas). He groups the resulting values for all samples into four, six, and four classes respectively (Fig.2.1). He then uses the unique combination of these three attributes to form the landform sub-classes. This process can provide as many as 96 landform units. However, he considers only 45 sub-classes that are common in the U.S. Finally, he groups the landforms into five classes and 24 sub-classes based on three tier hierarchy of landform units.

Dikau et al. (1991) attempts to develop an automated process that simulate Hammond’s (1964) manual method and tests it in New Mexico using a 200 m cell size DEM. Different from Hammond’s (1964) process Dikau’s et. al (1991) can identify all of the 96 landform units very easily. Dikau et al. (1991) use a window size of 9.8 km by 9.8 km that moved in 200 m steps where Hammond (1964) uses a 9.65 km by 9.65 km window that moves along in 9.65km steps. Therefore, in the latter one the entire area within the window is generalized to one landform class. On the other hand, Dikau et al. (1991) calculates a generalized window

5 value for each step, which is to the focal cell of the window. For that reason, Dikau et al.’s (1991) automated process produces significantly more accurate output. A summary of the major characteristics of their landform classes is summarized in Table 2.1.

Figure 2.1. The major classes, sub-classes and resultant map of Hammond’s (1964) method.

6 Table 2.1. Landform classification used by Dikau et al. (1991)

Tankagi and Shibasaki (1995) evaluated accuracy of DEM in relation to fixed spatial resolution. While they evaluate the existing methods, they claim that profile method has much error in elevation value; window method has much error in slope gradient value. According to them, the main reason for these errors is the distance between contour lines. They notice that, in their application, if contour line interval becomes over 300 m, possibility of getting a correct DEM is less than 50%. Therefore, they develop an interpolation method based on an intermediate contour line generation based on “buffering”. They believe that the intermediate contour line can be drawn using a buffering method. They consider four topographic parameters, namely, elevation, inclination, aspect and undulation in their applications. In their conclusion, they point out the relationship between a contour interval and an accuracy of generated DEM.

Brabyn (1996) tries to develop a methodology for an automated classification of landscape. He claims that automated landscape classification is difficult because of the complex nature of landscapes. According to him, classification needs to be based on theory, but there is a distinct lack of landscape theory. However, he believes that GIS provides a suitable platform to facilitate this evolution. He suggests that a landscape classification needs to incorporate landform, vegetation, naturalness, and water. He believes that the classes should be based on the “public’s perception” and should incorporate “movement and exploration”. He proposes a three-phase landscape classification process: 1) Selection of attributes, 2) Definition and classification of the attributes to six levels of generalization, and 3) Creation of landscape classes from compositions of the attributes. He applied his method to the South Island of New Zealand and compared the results with Hammond’s (1964) manual landform classification. The study has demonstrated the power and ease with which GIS can manipulate and analyze information traditionally obtainable from hard copy maps.

7 Friedrich (1996) presents an applicable procedure for geomorphic relief structuring (such as slope, aspect, and curvature) that follows a statistical approach. The goal of the procedure is to draw a boundary of homogenous relief units by free choice of relief map generalization. They claim that derivation of homogenous geomorphologic relief units, independent of landscape type, is possible with the method described in the study.

Tankagi (1996) attempts to evaluate DEM accuracy based on the spatial resolution of digitized topographic contours. He works on DEMs with various resolutions (100m, 150m, and 200m grid size) and tests his method in a mountainous area. According to his conclusions the accuracy of DEM is depending upon contour line interval. High-density contour line information is required for a high accurate DEM.

Wood (1996) aims to develop a set of tools that describe the general morphometric characteristics of a surface. He wishes to use these features for an automated landform classification. According to him the most widely used set of morphometric characteristics is the subdivision of all points on a surface into one of following six features: 1) pits, 2) peaks, 3) channels, 4) ridges, 5) passes, and 6) planes (Figure 2.2). He claims that these features should be described in terms of rates of change of three orthogonal components (neighbor features). He performs a standard method to identify morphometric features by passing a local (3 by 3) window over the DEM and examine the relationships between a central cell and its neighbors. He believes that this is a simplified and improved algorithm for classification, which preserves the continuity of line-based channels and ridges to a far greater extent. This provides an advantage over traditional methods of feature selection based on logical comparison of neighbors.

Figure 2.2. The six categories of morphometric features illustrated by the relationship between a central DEM cell and its eight neighbors (Wood, 1996).

8 Brabyn (1998) proposes an improved version of automatic classification of macro morphological landforms initially developed by Dikau et al. (1991). The method is using GIS and DEM, and is applied to the South Island of New Zealand. It defines macro landforms that are greater than 10 km2 and less than 1000 km2 in size. The method works well except for sudden landform changes such as from plains to mountainous areas. He suggests some new processes to overcome such problems.

Kuiper and Wescott (1999) uses GIS-based predictive mapping to locate areas of high potential for archaeological sites. This is a subject, which is becoming increasingly popular among archeologists. In their study, they first produce GIS layers representing the distribution of the environmental variables and then analyze these layers to identify locations where combinations of environmental variables match patterns observed at known prehistoric sites. The study is carried out in the Upper Chesapeake Bay region where more than 500 known archaeological sites exist. Three main steps in their analysis are: 1) developing an archaeological database, 2) collecting GIS layers representing the distribution of environmental variables for the known sites, and 3) examining the data with descriptive statistics. Finally, the model is run and results are visualized and compared to known sites. Site data included a polygon location in the GIS, site type, distance to water, type of water source (brackish or fresh), soil type, topographic setting, slope, elevation, aspect, geomorphic setting, time period and dimensions. They conclude that good results can be achieved from archaeological predictive modeling with available data.

Toprak et al. (2000) suggested a morphological landform classification for the settlements within the Çankırı province. Landform characteristics of 902 settlements are derived from 1:25.000 scale topographic maps. Four major classes of settlement landforms are identified in the area (Figure 2.3). These are “top”, “slope”, “valley”, and “flood” type settlements. For each major class several sub-classes are differentiated based on minor topographic modifications or location of the settlement on different parts of this landform category.

Dehn et al. (2001) draw the attention to the problems formed by various definitions made by different disciplines, which creates a big problem in the exchange of ideas. They emphasize importance of bringing together different perceptions, concepts and definitions from different disciplines. The approach regards geometric form as a basic property, extended by topological considerations and other semantic definitions. This is discussed in the paper with its potentials and limitations by the “hill slope” case study. The authors ask the questions: 1) how can one define where the valley ends and the mountain begins, 2) where exactly is the transitional unit hill slope located? They further claim that because of the discipline perception of landform types, various features cannot be defined by their internal properties alone. Therefore, definitions must be developed within the context of neighboring landform units. 9

“TOP” settlements

ta tb tc hilltop saddle spur

“SLOPE” settlements

sa sb sc sd se sf uniform convex concave break on slope saddle on slope ridge

“VALLEY” settlements

va vb vc vd valley base valley side junction valley sides

“FLOOD” settlements

fa fb fc fd on flood plain river mouth on flood island in flood slope above flood

Higher elevation Settlement

Alluvium Stream & flow direction Lower elevation

Figure 2.3. Morphological landform classification for Çankırı province (Toprak et al., 2000)

10 Romstad (2001) proposes an automatic classification of relief attributes into meaningful morphological units. The approach taken in his study is to use the algorithm suggested by Friedrich (1996) to break up the study area into homogenous landscape units. Because each cell’s relation to its neighborhood, or context, determines whether or not it should be generalized, this process is referred to as “contextual merging”. For each of the relief units, new attribute values are calculated and used as input to a cluster analysis that classified the units into more general landform types (Figure 2.4). He applies the method to a small area close to Ny-Ålesund, Spitsbergen. The following four variables are used as input to the algorithm in the study: 1) Slope (magnitude of the maximum slope angle between each cell and its eight neighbors), 2) Profile curvature (the curvature of the land surface in the direction of the maximum slope), 3) Planform curvature (the curvature of the land surface perpendicular to the maximum slope), 4) Wetness index (defined as ln(As/tanB) where As is the upslope contributing area and B is the slope) (Figure 2.5).

Figure 2. 4. Simplified algorithm of “contexual merging” suggested by Romstad (2001). Original continuous datasets (left), after the contextual merging the study area is divided into unique areas with internal homogeneity (middle). These areas are then classified into more general landform types by iterative cluster analysis (right).

2.2. Studies on the Location of Settlements

Settlement studies often provided data on site location and their distribution and researchers attempt to predict unknown site locations and attempt to understand the relations between the settlement locations and the environment by these information. According to Kohler and Parker (1986) predictive modeling is a technique to predict, at a minimum, the location of archaeological sites or materials in a region, based either on the observed pattern in a sample or on assumptions about human behavior. The first steps in the modeling process involved research and analysis to identify landscape features that would be used to simulate or predict areas of archaeological potential using a GIS.

Figure 2.5. Results of Romstad’s (2001) method. Left: a) terrain model with the mapped talus cones, b) contextually merged relief units, Right: a) classification with contextual merging, b) classification without contextual merging.

Parker (1985) introduces a formal predictive modeling technique for studying archaeological site distributions with an application in Sparta Research Area. She discusses the relevant anthropological theory serving as a foundation and a justification for the technique and its methodology. She selects certain variables based on basic life support properties. These properties are water, food resources (floral and wild, faunal and wild, floral and domestic), firewood, construction materials, slope of the location, drainage of the location and exposure-protection of the location.

Kvamme (1985) presents an approach designed to detect particular environmental features in the archaeological sites that prehistoric people were influenced in selecting their settlement locations. These features include water, a good view of environment, a good shelter, a south facing aspect, a level ground surface, a gentle local relief. He offers a model of the site selection process regarding the empirical findings of the application. The model based on observations in the ecological and ethnographic literature views human uses of the environment.

Kvamme (1990) examines several interpolation methods to generate elevation and examines various algorithms in order to get slope data. The effects of the differences between methods and algorithms are examined on the results of an archaeological location model developed for an east-central Arizona study area. He claims that the accuracy of computer generated data should be questioned.

12 Carmichael (1990) presents a predictive model of prehistoric site distributions located in an 8500 square mile area of north-central Montana. This model is based on logistic regression and does not predict the actual location of sites; but rather the method provides a statement about the probability that given area will contain a site. The area from which the prediction is constructed must have comparable variables to areas where prediction is to be made. He tries to construct “control areas” since he aims to develop a site patterning for the prediction. These control areas are created from locations containing known archaeological sites. Eight variables seems to be good predictors are: 1) Horizontal distance to permanent water, 2) Horizontal distance to any water, 3) Vertical distance to permanent water (difference in elevation between a site and the closest water source), 4) Vertical distance to any water, 5) Aspect, measured in degrees from UTM North, 6) Slope, measured in % grade, 7) Relief (difference between maximum and minimum elevation within 500 m of data point), 8) Elevation.

Zubrow (1990) studies the spread of European populations through the state of New York and their interaction with the native, prehistoric and ethno-historic populations. He used GIS techniques to simulate various models of demographic migration and settlement in order to determine more accurately the process of settlement of a frontier and determine the limiting factors of growth and migration. In the application he models the spread of colonial population using various river valleys as migration corridors. Then he compares the output of these models with the historical documentations.

Hasenstab and Resnick (1990) examine a model developed for the prediction of historic archaeological resources by GIS in a large project area. Researchers evaluate the effectiveness of the model in focusing survey efforts and in identifying historic archaeological sites.

Warren (1990) describes a predictive model of prehistoric site location and discusses the main causes of the model’s deficiencies to outline appropriate solutions.

Lopata and Shaw (1992) study on a simple predictive model for the location of well- preserved shipwrecks in the Sea of Marmara since it is the only waterway between the Black and Aegean seas. Using bathymetry data, colony locations, marble quarry sites, and estimates of the most likely trade routes, the likelihood of finding sunken ships from Hittites, Assyrians, Myceneans and Greeks was calculated. The criteria for this study are: 1) The areas having water depths of greater than 100 meters are selected since this depth is the most likely one to preserve shipwrecks because of the presumed “anoxic conditions”, and 2) The areas within 3000 meters of shorelines (including islands and large rocks) are isolated.

13 By intersecting these two layers researchers produce a large search area for shipwrecks. This area was then narrowed by creating a “probability grid" model done by adding the layers of series of buffers around ancient ports and quarries, navigable straights, and shipping routes. The resulting coverage has a range from 0 to 16 in likelihood, and is categorized into four. The highest potential category is chosen as the target search area. As a qualitative evaluation of the results, the authors note that an area that is previously indicated as having high potential for shipwrecks by a well-known researcher is agreeable to these results.

Dalla Bona (1993) creates a simple and an effective model of the visual possibility of archaeological sites dating from 9000 B.P. through the historic period in the Black Sturgeon Lake study area, north of Thunder Bay, Ontario. Using the value weighted method, five 30- meter-resolution raster layers of environmental variables are used: 1) proximity to water (separated into 6 different subcategories based on permanency), 2) soils, 3) drainage, 4) slope, and 5) aspect. Visual possibility of sites is calculated using different weights. These areas on the map have a range from 12 to 140. The known archaeological sites in the study area are used to evaluate the model, after simplifying the map into low, medium and high possibility areas. The evaluation shows that 80% of the sites occur in the areas identified as high potential, 19.6% are in the medium potential areas and only 0.4%in areas of low potential. The model is evaluated by two field seasons of systematic survey and then the model is updated to include the new data.

Phillips and Duncan (1993) create a correlative predictive model of archaeological sites. The model is based on known site locations and their correlations with one environmental variable: soil type. This was thought to be an indicator based on the idea that soil types are defined by other variables such as slope, drainage, property, texture, composition and vegetation. Due to the long life of soils and their slow rate of change, the authors believed that soil type was better than more “ephemeral variables” such as water sources and vegetation. Soil type is categorized into 50 classes. The resulting model shows the soil class polygons with high probabilities of archaeological deposits and evident. The results are evaluated by 10 transects covering both high and low probability zones. The surveys included visual investigation of the surface as well as shovel test pits every 30 meters in areas of low visibility. The new data showed that the model was quite good for predicting sites in the coastal lowlands. However, for the interior Western Highlands portion of the study area sites were found in areas of zero probability while the areas of high probability yielded no sites.

14 Silbernagel et al. (1997) believe that the distribution of human occupation on a landscape gives a lot of information about how people use the landscape, about patterns of economic development, and about cultural and social activities of the human groups. Distribution over several thousand years, can lead to an evolutionary understanding, not only of the people and their cultural patterns, but also of physical landscape development. The focus of this research is to examine and compare settlement patterns of prehistoric, historic, and present time periods, based on known cultural sites in the Eastern Upper Peninsula of Michigan, USA and to generate hypotheses about the interaction of settlement pattern and landscape change at multiple scales. Patterns of settlement among the three time periods are compared at three geographic scales by sub-regional ecosystems, landscape ecosystems, and terrain characteristics. They extracted “urban” categories from Landsat TM imagery to measure present occupations. Spatial patterns and dynamics of settlement areas in each time period are examined using GIS. Results show a tendency for settlement in all time periods on the bedrock and lowland landscape groups near Great Lakes shorelines. According to the results the slopes less than two percent is occupied. The distribution of present occupations, in terms of slope, aspect and geographic sub-region (multi-scalar), is similar to the distribution of prehistoric occupations. Both prehistoric and present sites are primarily south facing and are frequently found along Green Bay and Lake Michigan shorelines.

Lookabill (1998) believes that archaeologists in the Pacific Northwest have largely ignored the utilization of plants by prehistoric peoples and as a result base predictive models on hunting and fishing. Recently, however, a number of huckleberry processing sites have been discovered in the southern Washington Cascade Mountains area. She proposes a predictive model of huckleberry processing sites in the northern Cascade Mountains of Washington State by utilizing associations between the known sites and environmental variables in the southern Cascade Mountains area. She identifies only elevation as having predictive possibilities since environmental conditions and the nature of the huckleberry plant are changing and predicting getting difficult. She proposes to isolate the significant elevation range and perform a random sampling in that area in search of huckleberry processing sites. She suggests that since huckleberry processing was a female activity, this would be a step on the way toward a more or less male-centered view of past cultures.

Perkins (2000) states that site location may be thought of in two ways: "from the viewpoint of an individual site in the landscape or from the viewpoint of the landscape which is partially occupied by sites." In his analysis of the settlement pattern in the Etruscan period in Tuscany, he employs the second viewpoint because he believes that it is more applicable to complex societies. To do this he uses a chi squared test to show statistically significant associations between settlement locations and categories of altitude, slope, aspect and solid

15 geology. In order to determine if the associations are positive or negative he uses Yule's Q and evaluates the strength of the associations with an f2 test. He explores ten different time periods (centuries) in this way. For each time period and for both positive and negative associations, additive models were created with index values ranging from 1 to 4. The time slices were then divided into three periods for ease of analysis. The results show varying relations between sites and the variables through time, with a pronounced shift in settlement locations after the Roman capture.

Choquette and Valdal (2000) aim to develop an archaeological potential predictive model using GIS. Five main GIS layers used as predictors are summarized in Table 2.2. The potential for the occurrence of archaeological sites is evaluated by the intersecting the prepared layer in a GIS environment and by eco-section using an additive method based on the working hypothesis that archaeological potential should exist where a significant number of predictors occur. As a result of the query, any portion of the landscape is identified as potentially significant to archaeology will be referred as “potential”, and the rest will be referred as “non-potential.” In the study there are four major iterations for the modeling process. Each iteration is compared for success against the known set of archaeological sites. The researchers decided that nothing more could be added to the model after the fourth iteration. The potential and non-potential areas resulting from the fourth iteration queries are considered to be worth field-testing.

Table 2.2. GIS layers and their rankings assigned by Choquette and Valdal (2000)

Predictor (GIS layer) Description Slope Group 1: 0-10% - Highly significant Group 2: 11-30% - Moderately significant Group 3: 30+% - Not significant Aspect Group 1: Flat, South and Southwest - Highly significant Group 2: West and Southeast - Moderately significant Group 3: All other aspects - Not significant Soils - Sediments Group 1: Soils of glacio-lacustrine terraces - High significance Group 2: Soils of gravelly fluvi-oglacial terraces and fans - High significance Group 3: Soils in fine reworked fluvial/aeolian veneers - High significance Group 4: Soils of floodplains - High significance Group 5: All other soils - Not significant Soils-Microenvironment Group 1: Orthic brown chernozem, orthic melanic brunisol - High significance Group 2: Orthic eutric brunisol - Moderate significance Group 3: Subalpine brunisol, cumulic humic regosol - Less significance Group 4: All other soil types - Not significant Water Buffers Lakes 200m Marshes > 1ha 200m Marshes < 1ha 100m Major rivers 200m Definite streams 200m Indefinite streams 50m

16 Meybeck et al. (2001) presents a new classification with 5 main relief patterns. These are; 1) Plains correspond to sub-horizontal terrain, 2) Lowlands have a very low degree of roughness, 3) Platforms and hills have a greater degree of roughness, 4) Plateaus have a medium degree of roughness from 5 to 40‰), 5) Mountains differentiated from hills by their higher mean elevation and from plateaus by their greater roughness. They later divide these quantitative classes into 15 classes and then cluster into 9 basic types. Their study is applied to the Tibet and Altiplano areas characterized by very high plateaus that lack mountains according to their classification.

Özdemir (2002) seeks for a relationship between rock types and settlement locations without considering any other influencing factors. In the study a method is proposed to evaluate the preferred rock for the selection of the settlement locations.

Warren and Asch (2002) proposed a predictive model, which is based on logistic regression analysis of sample data using qualitative and quantitative measures of the natural environment, for prehistoric archaeological site location in a poorly drained upland prairie area.

White (2002) attempts to predict locations likely to contain archaeological material given a statistical relationship between known archaeological sites and their local environment. He assumes that archaeological sites are contemporaneous and the environment is a static entity, which means that “time” factor is an important criterion for the model. He applies his method to Tucson Basin, Arizona since the prehistory of the area is so old. This study also examines how changing site location can be modeled in a GIS environment. In the study three datasets are used: 1) archaeological dataset 2) physical dataset (deposition, erosion, geology, terraces, channels, fans, DEM, roads, land parcels), 3) image dataset (Landsat ETM7, Digital Ortho Quarter Quads). Three major steps in the study are: 1) data is re- organized to become contemporaneous with the time being modeled to the extent possible, 2) the archaeological data is divided into time periods where sites share similar characteristics or were formed by the same culture or shared the same subsistence strategy, and 3) archaeological data in each time period is divided by site type. An example of his output is given in Figure 2.6 where it can be clearly seen that the change is occurring between ‘slices’ (the lake is expanding eastwards, and settlement size, location, and count fluctuates from T1 to T4).

Figure 2.6. Time-slice snapshots representing change in a lake (light) and settlement (circle) pattern. (White 2002).

Woodman and Woodward (2002) describe some of the problems with statistical methods used in site location models that have not yet been addressed. They state that there are three main assumptions for statistical tests that have been ignored in archaeological predictive modeling: 1) data collection or sampling integrity, 2) a well established relationship between the sites and the variable used to predict their location, and 3) complete independence of each variable including the uniqueness of its affect on site location. In regard to the second problem, assumption of a linear relationship between a variable and site location is often ignored in logistical regression. For example, elevation often does not have a linear relationship with the probability of settlement location yet it is often treated that way. The authors try to establish a relationship between site location and the variables used to predict them. Finally, they believe that there is a problem for the relationship between the variables used for the models. Even if they are shown to be completely independent from one another, there can still be confounded and/or interactive relationships with one another.

CHAPTER III

DATA AND DATA PRODUCTION

Three sets of data are used in this thesis. These are: 1) Topographic data, 2) Morphological landform data, and 3) Settlement data. This chapter introduces the nature of these data sets and other related information derived from topographic maps. A simplified algorithm of the processes for data production is given in Figure 3.1.

3.1. Topographic Data

All topographic data are extracted from 1:25.000 scale topographic maps. Topographic maps are scanned at 300 dpi resolution using A0 scanner. They are, then, georeferenced in UTM projection system in the TNTMips environment. The maps are digitized with 50 m interval contour lines from the 1:25.000 scale seventy-seven topographic map sheets. These data were initially provided by Özdemir (2002); however, most of the maps are modified and edited particularly in flat areas. More contour lines are added to gentle areas with 10 m, 5 m, or 1 m intervals if necessary since the spacing of contour lines influences accuracy of DEM as mentioned by Tankagi and Shibasaki (1995).

After digitizing and editing the contour lines, they are exported into MapInfo format and converted into points with 50 m, 100 m, 150 m, and 200 m point intervals. These four point data sets are imported into ArcGIS 8.1 in order to create TIN. Each point data set is processed as input data for triangulation. This is done by Delaunay Method since the input data is a point vector data. Delaunay triangulation method uses the input point data to create triangular network according to its criterion. For each triangle, the circle that passes through all three vertices encloses no other input points. The Delaunay criterion creates triangles that are as small and equilateral as possible and is the rule used in creating TIN data.

19 Hardcopy Topographic Maps (77 sheets, 1/25.000 scale)

Scanning at 300 dpi resolution

Georeferencing

Reading settlement data Digitizing / Editing Deciding major from topographic maps Countour Lines Morphological Landform Classes

Converting settlement data Contour Line into point data Map Digitizing Morphological Landform Converting contour line data Classes Buffering points into point data with 100 m

Creation of TIN data

Settlement Landform Database Database DEM

Extracting DEM derivatives

DEM derivatives of Elevation map DEM derivatives Settlement locations Slope Map of Landform classes Aspect Map

TO ANALYSIS

Figure 3.1. Simplified flowchart showing data production for further analysis.

After getting TIN models for each input point data set, the TINs are examined for different grid intervals. The TINs with 200 m and 150 m point intervals have some corruptions because of the sparse points in some parts of the area. These two models, therefore, are eliminated. Quality of the surface models obtained from 50 m and 100 m grid interval, on the other hand, is very similar to each other. Since the number of the points is less in 100 m grid interval, this model is selected to reduce the process time.

DEM of the area is produced from TIN for 50 m, 100 m, 150 m, 200 m cell sizes with the “linear method” that treats each triangle as a planar surface. When a contour is found to pass between two TIN nodes, the location of its intersection with the triangle edge is determined by linear interpolation from the node Z-values. Each output contour line is made up of straight-line segments (one segment per triangle crossed), with direction changes occurring at the triangle edges. 100 m interval DEM is selected because of the reasons similar to above selection and the suitable size of the DEM (about 16 MB). Accordingly, total number of pixels for the whole area is 842018 (Figure 3.2-A).

Three outputs prepared from the DEM are elevation map, slope map and aspect maps. Basic characteristics of these maps are briefly explained below.

3.1.1. Elevation Map

Elevation of the study area ranges from 400 to 2400 m in the study area. The lowest elevations are dominant around the southeastern part of the area particularly around the flood plains of the Kızılırmak River. The highest elevations, on the other hand, can be observed around Ilgaz Mountains. Southeastern part of the area possesses a relatively smooth surface, whereas the rest of the area is characterized by a rough surface with a series of valleys and ridges elongated in NEE-SWW direction.

The histogram of the area is prepared on the basis of 100 m interval starting with 400 m elevation (Figure 3.3-A). The maximum concentration is observed at 1250 - 1300 meters with a value of about 13 %.

3.1.2. Slope Map

Slope amount changes from 0 to 57 degrees in the study area (Figure 3.2-B, 3.3-B). The slopes are classified with 2-degree intervals starting with 1 degree. Zero slopes are classified as a separate interval since they indicate flat areas. Most of the data are observed between 0 and 18 degrees with a mean at 8 degrees. The slopes above 34 degrees are negligible since their percentages are nearly 0. The slope map indicates that the gentle slopes are more dominated on the Kızılırmak basin and the southeastern parts of the study area.

3.1.3. Aspect Map

Aspect values of the data vary between -1 to 359 in degree. –1 corresponds to flat areas (zero- slope) that do not possess an aspect value. The rest of the range (0 to 359) is divided into 8 major directions with 45-degree intervals. Numerical range of each class is shown in Table 3.1. Aspect map and related histogram are illustrated in Figures 3.2-C and 3.3-C, respectively.

Table 3.1. Aspect ranges applied in this study.

Degree Classes

-1 Flat

338-023 N

024-068 NE

069-113 E

114-158 SE

159-203 S

204-248 SW

249-293 W

294-337 NW

22 A

Figure 3.2. Digital elevation model (A), Slope (B), and Aspect (C) maps of the study area

A 14 12 10 Min 400 8

% Max 2400 6 4 Mean 1159.71 2 Std.Dev. 309.88 0 Median 118 Mode 1300 0-449 550-649 750-849 950-1049 1150-1249 1350-1449 1550-1649 1750-1849 1950-2049 2150-2249 2350-2449 Elevation (meter)

B 16 14 12 Min 0 10 Max 56.2

% 8 6 Mean 5.53 4 Std.Dev. 3.31 2 Median 5 0

0 Mode 2 5-6 11-12 17-18 23-24 29-30 35-36 41-42 47-48 53-54 Slope (degree)

C 16 14 12 Min -1 10 Max 360

% 8 Mean 172.52 6 4 Std.Dev. 103.76 2 Median 169 0 Mode 180 Flat N NE E SE S SW W NW Aspect

Figure 3.3. Histograms and descriptive statistics for elevation (A), slope (B), and aspect (C) maps.

3.2. Morphological Landform Classes

Morphological landform classes constitute the most important input data in this study. To seek a relationship between the settlement location and type of the landform, the whole area should be classified into meaningful polygons each of which corresponds to different landform class. Three major factors to be considered in this classification are: 1) Scale: Scale determines precision or detail of the landform polygon to be digitized. Two available topographic map scales are 1:25.000 and 1:100.000. The former scale provides topographic contours at every 10 m, which is, in most cases more than necessary. The latter one, on the other hand, can produce coarse polygons where medium size topographic elements can be missed. In this study, therefore, 1:25.000 scale topographic maps are used to digitize the landform polygons. 2) Landform classification: Classification of landform into well-defined and commonly accepted types is a problem because these types will be different in different topographic terrains. The difference in the topographic texture of Central Anatolia (characterized by flat areas) and Northern Anatolia (characterized by deeply dissected landform) is an example to this problem. The literature survey given in previous chapter proves the variety of the landform classifications carried out in different regions. In this study the landform classes defined by Toprak et al. (2000) is adopted which suggests four major landform types named as “flood”, “valley”, “slope” and “top” (Figure 2.3). 3) Boundaries of landform classes: There is not a certain rule how and where to draw the boundary of neighbor classes. Although there are several attempts for “automated classification”, most of these classifications are still problematic and can work only in certain areas such as mapping the topographic divide or drainage basin. Some of these studies are summarized in previous chapter. In this study, therefore, the landform classification is made manually based on visual interpretation. An example digitization process is given in Figure 3.4. Map-A is a hypothetical area that comprises all major landform types. The resultant landform map for this area is given in map B.

25 A

Higher elevation

Lower elevation

Top

Slope

Valley

Flood

Figure 3.4. The landform classes used in this study A. Topographic sketch map of an area B. Landform polygons drawn from this map

26 General criteria during the digitization of the landform polygons are as follows (Figure 3.4): 1. An area to be classified as “flood”, it should have an almost flat, alluvial plain. Topographic contours across the plain should be widely spaced; the river flowing in the plain should be “meandering”. Boundary of the flood plain is determined by the sudden change in the slope at the immediate periphery of the flood area 2. “Valley” is characterized by a V-shaped river valley with considerable slopes on both sides. The nature of the river as permanent or intermittent is not important in this classification. Boundary of the valley passes immediately above the present river channel on both sides. 3. “Slope” corresponds to inclined topographic surface. Ideally it is always between a valley at lower elevations and a top at higher elevations. Variations in the slope amount and slope direction (aspect) are not considered as important factors during the digitization. 4. “Top” landform type corresponds to the uppermost part of an inclined surface. Ideally it has a circular or elliptical shape. The lower boundary of this landform is drawn where there is a sudden change in the slope amount. 5. Water bodies (river channels, lakes or other man-made water bodies) are not considered during digitization because it is believed they are present in the area in negligible amount. 6. In general, the typical order of the landform types is, from bottom to top, A) flood, B) valley C) slope, and D) top. In some cases, however, this order may change. For example, on the shoulders of a flood plain the order is from flood landform to slope.

During the digitization process first “flood” and “top” landforms are digitized because they are easily recognized in the topographic maps. This is followed by “valley” type landform; finally “slope” was digitized, which is usually confined to the area between “valley” and “top”.

The whole area is digitized for these major four landforms and a final map is prepared (Figure 3.5). Spatial distribution of individual landform types is given in Figure 3.6.

Morphological landformMorphological map of the area.

Figure 3.5.

each morphological landform class.

Figure 3.6. Spatial distribution of

29 Total number of polygons is 4042. Table 3.2 shows basic characteristics of these polygons for each landform type. As seen in the table, the most common landform in the area is slope with more than 67 %. The rest of the area is shared almost equally by other three landforms.

Topographic attributes and examples of these landforms are given below for each class separately.

Table 3.2. Basic statistics of landform classes digitized in this study

Type of Number of Minimum Maximum Total area Percentage landform polygons Area (km2) Area (km2) (km2) Over area Flood 28 0.0516 320.2709 573.6118 6.25

Valley 1074 0.0017 65.6401 1412.6358 15.39

Slope 450 0.0010 1228.7831 6182.4546 67.34

Top 2490 0.0018 34.9602 1012.7622 11.03

TOTAL 4042 9181.4644

Results given in Table 3.2 indicate that the most common landform is “slope” with 67.34 % and the least one is “flood” with 6.25 %. Small fractional values in “minimum area” column are due to the partial landforms that are dominantly located out of the study area.

80 70 60 50

% 40 30 20 10 0 Flood Valley Slope Top Morphologic Landform Classes

Figure 3.7. Distribution percentages of morphological landform classes on the topography

30 3.2.1. Flood Landform

Flood landforms developed over flood plains are observed along major streams that have gentle slopes. Four examples of this landform are shown in Figure 3.8. Meandering streams are main features of this landform. This landform is the most distinctive class on the maps because the contour lines are, more or less, parallel to the margins on both sides. The width of the flood plains can change from 500 m (Map A) to almost 3 km (Map C). Joining of two flood plains to form a single plain is common in the area (Maps A and B). Although the most common neighbor landform is “slope” (maps A and D), valleys that terminate at floods are also common (Maps B and C).

Topographic characteristics of floods are summarized in Figure 3.9. Elevation of the floods range between 499 and 1550, however, they are mostly confined to lower elevations, between 550 and 650. The slope range of the flood is very typical with very small amounts. Nearly 50 % of the pixels have a slope of 0 degree. The mean value of the slope is calculated as 1.70. About 20 % of the area above 3 degrees should be due to the island-like features within the flood areas. Aspect values for 8 principal directions and flat areas indicate no dominance in certain directions. However, flat areas with no slope and southeasterly facing pixels are more common in flood landform.

A B

C D

Figure 3.8. Examples of flood areas. (Blue: flood; Cyan: valley; Red: Top; and the rest is slope; distance between two grid lines is 1 km).

31 35 30 25 20 Min 499 % 15 10 Max 1575 5 Mean 810 0 Std.Dev. 259.18

0-449 Median 810 550-649 750-849

950-1049 Mode 850 1150-1249 1350-1449 1550-1649 1750-1849 1950-2049 2150-2249 2350-2449 Elevation (meter)

40 Min 0

% 30 Max 33

20 Mean 1.70 Std.Dev. 2.83 10 Median 1 0 Mode 0 0 5-6 11-12 17-18 23-24 29-30 35-36 41-42 47-48 53-54 Slope (degree)

20 18 16 Min -1 14 12 Max 359 10 Mean 144.7 8 6 Std.Dev. 118.10 4 Median 136 2 Mode -1 0 Flat N NE E SE S SW W NW

Figure 3.9. Topographic attributes of flood landform

32 3.2.2. Valley Landform

Valley areas are easily distinguished from flood areas by several characteristic features. These differences are: 1) Valleys have V-shaped valleys with a shorter valley floor across the river, 2) The stream channel is steeper than the basal floor of a flood, therefore, has a shorter contour line distance in plan view, 3) The course of the river is straight compared to meandering rivers.

The boundary of the valley passes almost parallel to the river on both sides (Maps A, B, C and D in Figure 3.10). In most cases a valley ends at a flood (Map A). Usually the topographically the upper neighbor of the valley is slope (Map A, B, C and D). However, in some rare cases, where the slope length is small, the valley can directly underlie a top landform (some valleys in Map A).

Topographic characteristics of valley landform are shown in Figure 3.11. Elevation range of valley is 500-2073, however, an obvious concentration is observed at 1250-1350 m. Slope amount of valley areas ranges from 0 to 54 degrees with a mean at 4,63°. Therefore, the valley is characterized with gentle slope. The amount, however, compared to flood areas is a bit greater. Aspect of the valleys is randomly distributed in almost all directions. A slight dominance of “flat” aspect indicates that bottom of most valleys have zero-slope.

A B

C D

Figure 3.10. Examples of valley areas. (Blue: flood; Cyan: valley; Red: Top; and the rest is slope; distance between two grid lines is 1 km).

20 15 Min 500

% 10 Max 2073 5 0 Mean 1096,30 Std.Dev. 279,17

0-449 Median 1120 550-649 750-849 950-1049 1150-1249 1350-1449 1550-1649 1750-1849 1950-2049 2150-2249 2350-2449 Mode 1300 Elevation (meter)

30 25 Min 0 20 Max 54

% 15 10 Mean 4,63 5 Std.Dev. 4,79 0 Median 3 0 5-6 Mode 0 11-12 17-18 23-24 29-30 35-36 41-42 47-48 53-54 Slope (degree)

20,00 Min -1 15,00 Max 359

% 10,00 Mean 145,9 5,00 Std.Dev. 121,53

0,00 Median 128 Flat N NE E SE S SW W NW Mode -1

Aspect

Figure 3.11. Topographic attributes of valley landform

3.2.3 Slope Landform

Slope landform is produced after all other three landforms (flood, valley and top) are digitized. The rest of the area, therefore, is automatically processed and assigned to slope landform.

The slope landform, in most cases, is observed between valley and top landforms (Maps A and B in Figure 3.12). In some cases, however, a slope area can be observed between two streams without a top landform (Map C in the figure). This is due to a convex topography (ridge) confined between these two valleys. Map D shows a more complicated pattern of slope with the neighboring hanged-valleys and flood landform.

Elevation of slope areas ranges from 0 to 2351 m (Figure 3.13) with a maximum concentration at 1250-1350 m interval. Slope amount of the slope landform, on the other hand, although change between 0 and 50 degrees, has a mean of 9.89 degrees. Aspect of the slope landform has not a certain concentration at any interval. However, northerly and southerly slopes are slightly higher than other intervals, while the minimum value is obviously for flat aspect values.

A B

C D

Figure 3.12. Examples of slope areas. (Blue: flood; Cyan: valley; Red: Top; and the rest is slope; distance between two grid lines is 1 km).

16 14 12 Min 0 10

% 8 Max 2351 6 4 2 Mean 1202,82 0 Std.Dev. 289.57

0-449 Median 1219 550-649 750-849 950-1049 1150-1249 1350-1449 1550-1649 1750-1849 1950-2049 2150-2249 2350-2449 Mode 1350 Elevation (m eter)

12,00 10,00 8,00 Min 0

% 6,00 Max 50 4,00 Mean 9.89 2,00 Std.Dev. 6.75 0,00

0 Median 9 5-6

11-12 17-18 23-24 29-30 35-36 41-42 47-48 53-54 Mode 0

Slope (degree)

15 Min -1 Max 359 % 10 Mean 171.91 5 Std.Dev. 105.23 0 Median 163 Flat N NE E SE S SW W NW Mode -1 Aspect

Figure 3.13 Topographic attributes of slope landform

36 3.2.4. Top Landform

Top landform class corresponds to high areas and characterized by loop-like contours. They are easily identified on the topographic maps. They display several patterns in the area depending on the nature of the erosion. One common pattern of the top landform is disconnected circular or elliptical areas randomly distributed in the area (Figure 3.14-A). The other pattern is an elongated hill confined between parallel streams (B in the figure). The third pattern is continuous and irregular (with no defined shape) top area observed between several streams flowing in various directions (Map C). The last example is a set of elongated and parallel top areas developed between streams of the same flow direction (Map D).

Elevation of the top areas ranges between 550 and 2400 m with a maximum concentration at 1250 – 1350 m (Figure 3.15). Slope amount of the top landform is low as expected with a mean of 3.26 degrees. Aspect of this landform has a maximum percentage for “flat” class. Southeast to southwest facing slopes form the second class in top landform.

A B

C D

Figure 3.14. Examples of top areas. (Blue: flood; Cyan: valley; Red: Top; and the rest is slope; distance between two grid lines is 1 km).

37 16 14 12 Min 550 10

% 8 6 Max 2400 4 2 Mean 1239.49 0 Std.Dev. 320,41 Median 1290 0-449 550-649 750-849 950-1049

1150-1249 1350-1449 1550-1649 1750-1849 1950-2049 2150-2249 2350-2449 Mode 1400

Elevation (m eter)

35 30 25 Min 0 20 Max 44 % 15 10 Mean 3,26 5 Std.Dev. 3,49 0 Median 2 0 5-6

11-12 17-18 23-24 29-30 35-36 41-42 47-48 53-54 Mode 0

Slope (degree)

20 Min -1 15 Max 359 % 10 Mean 140,29

5 Std.Dev. 106,61

0 Median 143 Flat N NE E SE S SW W NW Mode -1

Aspect

Figure 3.15 Topographic attributes of slope landform

38 3.3 Settlement Data

A total of 891 settlements are processed in this study. A database is created as an excel file (Appendix A) that contains following information: • Id no • Name of the settlement • Topographic sheet number • Coordinates (2 columns: Easting and Northing) • Landform class as flood or valley or slope or top • Position within the landform class polygons • Nearest landform class

All settlements are identified using topographic maps of 1984-1997 at 1:25.000 scales. Identified settlements are checked with two external sources: 1) Settlement names listed in the map prepared by the Çankırı Municipality, and 2) Village names published by the State Institute of Statistics for 1950 and 1995 census of population. The former one fits exactly the list obtained in this study. The latter one, however, lists only the administrative units (village and larger ones), therefore it is not used in this study. During the creation of the settlement database following criteria are applied: - No distinction is made between the settlements considering their size, population or administrative classification. They are all counted in the database and considered as a single settlement. - Each settlement is considered to be represented by a definite point on the map which is, most probably, the initial location of the settlement. Therefore, the later growth of the settlement is not important in this study. An example of initial site selection is illustrated in Figure 3.16 for Çankırı city where a clear distinction is possible between the oldest and later parts of the city. The exact location of the settlement is problematic only for a couple of large settlements. For such settlements, if topographic attributes are similar for the whole area of the settlement, then any point in the polygon can be selected. Otherwise, either the mosque or center of the settlement is marked for the location. - Topographic attributes of the settlements are read from topographic maps. To avoid misreading due to variations in topographic attributes, a buffer area of 100 m, in radius, is defined for each settlement that corresponds to approximately 9 pixels, and the mean of this area is calculated. - A group of houses appeared in the topographic map particularly around recent activities such as modern farms or petrol stations are not considered as settlement, and therefore, not included in this study. - High-land settlements (plateau) are not taken into consideration because they are not permanent settlements.

Figure 3.16. A general view of Çankırı city showing the difference in the pattern of the old and new parts.

First the coordinates of the settlements are read from topographic map and transferred to database (Figure 3.17). Using these coordinates the topographic attributes (elevation, slope and aspect) are extracted from DEM of the area. Lastly, the landform class, the nearest landform class and the position of the settlement within the class are read from the landform map.

Figure 3.17. Distribution of 891 settlements (red points) in the study area.

40 3.3.1. Settlement and Topography

Topographic characteristics of settlements for elevation, slope and aspect are illustrated in Figure 3.18. According to elevation data most of the settlements are located between 1150 and 1250 with a mean at 1066.74 m. A sudden decrease in elevation frequency at about 1350 m and the absence of settlements above 1760 m are interesting results of this histogram.

Settlements have a slope variation between 0 to 24 degrees with a mean at about 7.17 degrees. Although, the study area has a slope amount of up to 57 degrees (see Figure 3.3), settlement locations are seen mostly on more gentle slopes of this area.

Aspect of settlements are shown on 8 major directions with 45 degree intervals and for the flat areas that do not have any slope (-1 score in the table). East, southeast and south facing settlements are relatively more common than other directions. The least preferred direction for the settlements seems to be flat areas.

20 Min 504 15 Max 1760 Mean 1066.74 % 10 Std.Dev. 415.73 5 Median 1087 0 Mode 1200 0-449 550-649 750-849 950-1049 1150-1249 1350-1449 1550-1649 1750-1849 1950-2049 2150-2249 2350-2449 Elev ation (meter)

20 Min 0

15 Max 23.80 Mean 7.17

% 10 Std.Dev. 3.34 Median 7 5 Mode 0 0 0 3-4 7-8 11-12 15-16 19-20 23-24 27-28 31-32 35-36 39-40 Slope (degree)

25 Min -1 20 Max 354 Mean 168.96 15

% Std.Dev. 141.59 10 Median 163 5 Mode 0 0 Flat N NE E SE S SW W NW

Aspect

Figure 3.18. Histograms and basic statistics of topographic parameters for settlements.

41 3.3.2. Settlement Location and Morphological Landform

Landform characteristics of the settlements are obtained from landform class map using coordinates of the settlements. Number of settlements and their percentage for each class are given in Table 3.3. These are illustrated in the histogram in percentages in Figure 3.19. Accordingly, most of the settlements are located on slopes. The slope landform is followed by valley and then by flood. The least settled landform type is top. An example of settlement for each landform class is given in Figure 3.20 and Figure 3.21.

Based on these scores alone, although an order of preference for the landforms can be suggested, this interpretation may not be valid if the percentages and availability of suitable landforms in the area are not checked. A correct interpretation, therefore, will be made after necessary analyses are made in the next chapter.

Table 3.3.Frequency and percentages of settlements for each landform class

Landform Frequency Percentage

Flood 79 8.87 Valley 244 27.38 Slope 519 58.25 Top 49 5.50

70 60

40 % 30

0 Flood Valley Slope Top

Figure 3.19. Settlement morphological landform class histogram

Flood settlement Photo is taken 24 km SW of Çankırı. The settlement is Konak (Id No: 874 in the database). The settlement is located on the southern margin of the flood along Terme Stream.

Valley settlement Photo is taken 48 km NW of Ilgaz. The settlement is Çomar (Id No: 171 in the database). The settlement is located at the bottom of the valley, on the northern side of Gök River.

Figure 3.20. Examples of flood and valley settlements in relation to landform classes

Slope settlement Photo is taken 28 km W of Çankırı. The settlement is Hisarcık (Id No: 856 in the database). The settlement is located almost at the middle of a long sloping surface facing south.

Top settlement Photo is taken 40 km W of Kızılırmak city. The settlement is Tepe Alagöz (Id No: 833 in the database). The settlement is located on an elongated ridge developed on the northern flank of Çankırı Stream.

Figure 3.21. Examples of slope and top settlements in relation to landform classes.

CHAPTER IV

METHOD AND DATA ANALYSIS

Initial analysis of the data explained in previous chapter can suggest on the preference of certain landforms during the selection of a settlement site. Table 4.1 summarizes the percentages of the settlements and area for each particular landform class. The difference of these percentages is an indicator whether a landform is preferred (plus values) or avoided (minus values). For example, for the flood landform, the area provides a percentage of 6.25; however, the percentage of the settlements is 8.86. Therefore, people attempt to use this landform more extensively than the area provides. Accordingly, the initial analyses suggest that flood and valley landforms are preferred while slope and top are avoided.

Table 4.1. Comparison of landform percentages for settlements and the area.

Landform Settlements (%) Area (%) Difference Flood 8.866 6.25 2.62 Valley 27.384 15.39 11.99 Slope 58.249 67.34 -9.09 Top 5.499 11.03 -5.53

The same data also reveal that some parts of the area are not settled because of unsuitable topographic (elevation, slope and aspect) conditions. For an accurate analysis, therefore, the landforms within these unsuitable areas should be removed and the relationship between the settlements and the landforms should be re-evaluated for the rest of suitable areas.

In this chapter, the method that seeks a relationship between settlement sites and landform classes will be introduced and the analysis within the method will be explained. The flowchart of the method is given in Figure 4.1. The method is composed of three major steps. In the first step, topographically unsuitable areas will be removed. In the second step, relationship between the settlements and landform will be analyzed. In the last step, further analysis of the relative location of settlements within the landform will be carried out for the final investigation of this relationship.

45 Settlement Database Topographic Database Morphological Landform Database

Masking and Weighting Analysis

Subtracting histograms (settlement-topography) to define thresholds/weights

Masking Analysis Weighting Analysis

Define weights for Mask the intervals of negative values elevation, slope, aspect parameters

Producing a new Producing a new Producing a new surface surface unsuitalbe surface unsuitable for all three of according to parameters for at least two of weights the parameters the parameters

Surface for discarded Surface for discarded areas due to all three areas due to at least two Weighted Surface parameters parameters

Select the most appropriate method

Clip out the landform map for unsuitable areas due to the selected method

Analyze preferred and avoided landform

Find the position of a settlement within landform polygon

Find the nearest landform class for each settlement

Interpretation of Results

Figure 4.1. Flowchart of the method to investigate the relationship between settlement locations and landform classes (continuation of Figure 3.1)

46 4.1. Removing Unsuitable Areas

The decision rules to remove unsuitable areas should be extracted from the topographic conditions of the area and the settlements. Histograms of both data sets (given in the previous chapter) can be used, for each topographic parameter, to define the thresholds. Subtracted histograms for elevation, slope and aspect are illustrated in Figure 4.2.

Blue intervals in each histogram indicate positive and red areas indicate negative conditions for the related topographic parameters. The first approach in the definition of the threshold values is to base on positive and negative areas. In this case the negative areas will be removed from the area and only positive areas will be kept for further analysis.

There is, however, a distinct difference in the percentages of some intervals for both positive and negative areas. Therefore, a second approach can be assigning a weight for each interval according to its percentage. These two analyses will be carried out separately below. The first is called “Masking Analysis” and the second one is called “Weighting Analysis”.

4.1 .1. Masking Analysis

In the masking analysis, the thresholds are defined to omit the areas that are out of these thresholds. Setting a threshold is the first requirement for this analysis. These thresholds are defined from the subtraction of settlement and topography histograms for each topographic parameter. Threshold intervals for this study are found using the histograms in Figure 4.2 and the values are given in Table 4.2.

Table 4.2. Topographic thresholds for masking analysis

Topographic parameter Interval to be removed Interval to be kept

Elevation <750 m and >=1350 m 750-1350 m Slope 0 degree and >=11 degrees 1-11 degrees Aspect Flat, N, NE, NW E, SE, S, SW, W

These three topographic parameters are independent from each other. A pixel, for example, on the surface could be within the threshold values for elevation but out of the range for slope and aspect. A total of 8 cases, therefore, are possible for different combinations of these three parameters. An example of these cases is illustrated in Table 4.3. A positive value (+1) is assigned for the pixel if it is within the threshold range, and a negative value (- 1) for others. Values of each topographic parameter are added to find the final score of that point. Accordingly, four different scores can be obtained from these summations. These are (+3), (+1), (-1) and (-3).

47 8

% 0

-2 0-449 450-549 550-649 650-749 750-849 850-949

-4 950-1049 1050-1149 1150-1249 1250-1349 1350-1449 1450-1549 1550-1649 1650-1749 1750-1849 1850-1949 1950-2049 2050-2149 2150-2249 2250-2349 2350-2449

-6

-8 Elevation (m eter)

% 0 0 3-4 7-8

-5 11-12 15-16 19-20 23-24 27-28 31-32 35-36 39-40 43-44 47-48 51-52 55-56

-10 Slope (degree)

% 0

-2 FlatNNEESESSWWNW

-4

-6

-8 Aspect

Figure 4.2. Histograms obtained by subtracting settlement percentages from the topography percentages for elevation, slope and aspect. Blue intervals indicate positive (preferred) and red intervals indicate negative (avoided) attributes.

Table 4.3. Final score of any pixel with different combinations of three topographic parameters

Case Elevation Slope Aspect Score (Sum)

A +1 +1 +1 +3 B +1 +1 -1 +1 C +1 -1 +1 +1 D +1 -1 -1 -1 E -1 +1 +1 +1 F -1 -1 +1 -1 G -1 +1 -1 -1 H -1 -1 -1 -3

Explanation of these four scores is as follows: (+3) : All topographic parameters are within the threshold range (+1) : Any two topographic parameters are within the range; one is out of the range (-1) : Any one topographic parameter is within the range; two are out of the range (-3) : All three topographic parameters are out of the range

The whole area is processed for the eight classes explained in Table 4.3 and a map is prepared (Figure 4.3) that shows the distribution of these classes. Red color shows the areas that are suitable for all topographic parameters (score: +3). Score +1 areas are indicated by green, yellow and orange colors. A careful analysis of the figure suggest that (+3) and (+1) areas are spatially close to each others. These areas cover three distinct regions in the area. The first one is an elliptical region in the central-southeastern part. Other two areas are elongated regions in the central and northwestern parts. Other four classes are indicated by black (-3), cyan, blue and white colors (-1). Similar to the first observation, this group classes are also spatially associated.

Percentages of each class are given in Table 4.4. Accordingly, the most (+3) and the least (- 3) suitable areas have percentages of 22.74 and 9.81, respectively. Subtotal of suitable and non-suitable areas for any two parameters (+1 and -1) cover 37.15 and 30.30 of the whole area, respectively. Therefore, the total percentage of the area suitable for at least two parameters is about 60 %. The rest 40 % is covered by the area which is not suitable for at least two parameters.

Figure 4.3. Spatial distribution of eight classes based on three topographic parameters.

Table 4.4. Percentages of the eight classes shown in Figure 4.3.

Score Explanation Percentage Subtotal-1 Subtotal-2

+3 All (+) 22.74 22.74 Area suitable at least for two topographic +1 E and S (+), A(-) 10.85 59.89 parameters +1 E and A (+), S (-) 12.40 37.15 +1 E (-), S and A (+) 13.90 -1 E (+), S and A (-) 12.83 Area not suitable at least for two -1 E and S (-), A (+) 9.16 30.30 topographic -1 E and A (-), S (+) 8.31 40.11 parameters -3 All (-) 9.81 9.81

The areas indicated by (+3) and (+1) scores should not be removed because at least two topographic parameters are satisfied in the selection of a suitable area. (-3) area should be removed with no doubt from the area because none of the parameters is suitable for settlement. For (-1) area, on the other hand, it is difficult to decide whether to keep or to remove. In this type, one topographic parameter is satisfied while other two are not. In order to examine the results and compare with (-3) score it is decided to process (-1) score as well. Therefore, the two outputs for the probable masking process will be produced.

The formula to remove the areas with (-3) score is as follows:

IF (Elevation < 750 and Elevation >= 1350) AND (Slope < 1 and Slope >=11) AND (Aspect < 69 and Aspect >= 294) THEN Value = -1 ELSE Value = 1 ENDIF

The output of this process is shown in Figure 4.4. The pattern of the discarded regions does not show randomly distributed pixels but rather it shows certain concentrations in various parts of the area.

The formula to remove the areas with (-1) score is given below. It should be noted that eight classes mentioned above are mutually exclusive and do not overlap. Therefore, the formula should take all three (-1) classes and also (-3) class into consideration. For this reason the formula involves four “if” statements each of which checks one of the scores. Explanation on the right side of the equation clarifies for which score the “if “ statement is used.

IF (E < 750 or E >= 1350) and (S < 1 or S >=11) and (A < 69 or A >= 294) Point H in Table 4.3 OR IF (E < 750 or E >= 1350) and (S < 1 or S >=11) and (A >= 69 and A < 294) Point F in Table 4.3 OR IF (E < 750 or E >= 1350) and (S >= 1 and S < 11) and (A < 69 or A >= 294) Point G in Table 4.3 OR IF (E >= 750 and E < 1350) and (S < 1 or S >=11) and (A < 69 or A >= 294)] Point D in Table 4.3 THEN Value = -1 ELSE Value = 1 ENDIF

The output of this process is given in Figure 4.5. Since this map contains unsuitable areas due to both all-parameter (-3) and two-parameter (-1) conditions, sum of the unsuitable areas covered by this map is more than the previous one (Figure 4.4). A comparison of these two outputs indicate that (-3) score areas are concentrated in some parts of the area while the (-1) score areas are distributed almost over the whole area.

Figure 4.4. Areas discarded due to all three topographic parameters (-3 score).

Figure 4.5. Areas discarded due to at least two topographic parameters (-3 and -1 scores).

52 4.1.2. Weighting Analysis

Weighting Analysis considers topographic parameters with different costs and performs thresholds according to these costs. Any pixel, therefore in the area is assigned a value in which the weights of the parameters are considered. The equation of this weight is as follows:

Weight = (A * Elevation) + (B * Slope) + (C * Aspect)

In this equation, Elevation, Slope and Aspect are the weights for corresponding topographic parameters and are obtained from subtracted histograms. These histograms are shown in Figure 4.2 and the values are listed in Table 4.5 for different intervals of three topographic parameters.

Table 4.5. Weights calculated from the subtracted histograms for the intervals of topographic parameters.

Elevation Slope Aspect

Topo. Settle. Differ. Interval Topo. Settle. Differ. Interval Topo. Settle. Differ. Interval (m) (%) (%) (%) (degree) (%) (%) (%) (degree) (%) (%) (%) 0-449 0.05 0.00 -0.05 0 14,53 6,40 -8,14 -1 7,63 2,13 -5,50 450-549 0.75 0.67 -0.07 1-2 11,53 12,01 0,48 338 - 23 11,90 5,61 -6,29 550-649 5.21 4.60 -0.61 3-4 12,20 14,25 2,05 24 - 68 10,86 8,75 -2,10 650-749 5.22 4.83 -0.39 5-6 11,65 18,52 6,87 69 - 113 10,97 15,15 4,18 750-849 5.92 8.75 2.83 7-8 10,77 16,84 6,07 114 - 158 15,23 20,43 5,19 850-949 9.02 9.76 0.74 9-10 9,67 12,35 2,68 159 - 203 13,14 18,74 5,60 950-1049 9.53 15.60 6.07 11-12 8,58 7,97 -0,62 204 - 248 10,34 11,22 0,88 1050-1149 9.99 15.15 5.16 13-14 6,61 5,72 -0,88 249 - 293 8,56 9,32 0,76 1150-1249 11.12 15.71 4.59 15-16 4,32 3,93 -0,39 294 - 337 11,36 8,64 -2,71 1250-1349 13.24 16.05 2.81 17-18 3,20 1,12 -2,08 1350-1449 11.05 6.06 -4.99 19-20 2,37 0,67 -1,70 1450-1549 8.50 2.02 -6.48 21-22 1,71 0,00 -1,71 1550-1649 5.10 0.34 -4.76 23-24 1,13 0,22 -0,91 1650-1749 3.18 0.22 -2.96 25-26 0,72 0,00 -0,72 1750-1849 1.35 0.22 -1.13 27-28 0,45 0,00 -0,45 1850-1949 0.42 0.00 -0.42 29-30 0,26 0,00 -0,26 1950-2049 0.14 0.00 -0.14 31-32 0,14 0,00 -0,14 2050-2149 0.10 0.00 -0.10 33-34 0,07 0,00 -0,07 2150-2249 0.08 0.00 -0.08 35-36 0,04 0,00 -0,04 2250-2349 0.02 0.00 -0.02 37-38 0,02 0,00 -0,02 2350-2449 0.00 0.00 0.00 39-40 0,01 0,00 -0,01 41-42 0,01 0,00 -0,01 43-44 0,00 0,00 0,00 45-46 0,00 0,00 0,00 47-48 0,00 0,00 0,00 49-50 0,00 0,00 0,00 51-52 0,00 0,00 0,00 53-54 0,00 0,00 0,00 55-56 0,00 0,00 0,00 57-58 0,00 0,00 0,00

53 By only adding these three parameters to find the total score of a pixel might produce wrong result, because in this case, it is assumed that all three parameters have the same weight (contribution) for the selection of the sites. To avoid the equal effect of topographic parameters, each topographic parameter is multiplied by a constant number (A, B and C the equation), which is extracted from settlement database. These numbers, therefore, can be used as a measure of the importance of each parameter individually. To find the values of these constants, the number of settlements which are suitable only for one parameter and not for other two parameters are counted. Frequency and relative weights of this statistics are given in Table 4.6. Accordingly, elevation has a maximum weight (0.37) followed by aspect (0.33) and then by slope (0.29).

Table 4.6. Relative weights of three topographic parameters.

Settlement Count Percentage (%) Weight Elevation 243 37,043 0,37043 Slope 192 29,268 0,29268 Aspect 221 33,689 0,33689

An example of the final score of a pixel for following topographic values is calculated as follows: Elevation: 1155 m Slope: 11 degrees Aspect: 65 degrees (NE) Weight = (0.37043)*(4.59) + (0.29268)*(-0.62) + (0.33689)*(-2.1) = (-0.3901563)

The weights for each parameter interval are processed for the whole area and a new “weighted surface” is created. The surface has values changing between -6 and 6. Histogram showing distribution of points for different weights is given in Figure 4.6. Accordingly, about 73 % of the area falls in the positive region.

Surface Percentage

30 25 20 Percentage 15 Negative 26.76 10 Positive 73.24 5 0 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Figure 4.6. Results of the weighting analysis showing final scores over the whole area.

54 Negative values are considered to be “unsuitable area” and a binary map is prepared showing discarded areas (Figure 4.7). The pattern of this map is very similar to the map produced in masking analysis with (-1) and (-3) score (Figure 4.5). One major difference is that, central western part of the area is more discarded in the weighting analysis compared to the other one.

Figure 4.7. Areas discarded after the weighting analysis.

4.1.3. Evaluation of Discarded Data Three methods are applied to discard unsuitable areas from the region. Outputs of these methods are illustrated in Figures 4.4, 4.5 and 4.7. The decision for the most appropriate method depends on the discarded percentages of the settlements and the surface area for each method. These values are given for each method in Table 4.7. As seen in the table the masking method with (-3) score has the best ratio with only 2.13 % settlements and 9.81 % area being removed. Therefore, this method will be selected to be the most appropriate one.

After the masking method, a total of 19 settlements are removed from the database. Topographic properties and type of landform for these settlements are shown in Table 4.8. Note that all elevation, slope and aspect values are out of the threshold ranges. Slope landform is the type that loses maximum settlement (8), followed by flood (6 settlements), valley (4 settlements) and top (1 settlement). A minor concentration of five settlements is observed in the northwestern part of the area. It is believed that the percentage of the discarded settlements is an optimum number and indicates that the thresholds are accurately selected.

Table 4.7. Discarded settlements and areas due to three different methods.

Method Discarded Settlements Discarded Area Ratio Number Percentage Surface (km2) Percentage (Sett%/Surface%)

Masking (-3) 19 2.13 82.30 9.81 0.22

Masking (-1)+(-3) 139 15.60 336.64 40.11 0.39

Weighting 114 12.79 224.52 26.76 0.48

Table 4.8. Topographic and landform properties of discarded settlements

Id ELEVATION SLOPE ASPECT Settlement Name LANDFORM No (m) (degree) (degree)

5 Bicikler 600 0 -1 top 13 Bostanli 563 0 14 flood 49 Karsi 679 11 304 slope 76 Caciklar 550 0 58 flood 84 Kapakli_H32a1 580 0 -1 slope 139 Sogucoluk 1361 14 31 slope 257 Deresemail_Degirmen_K 700 0 -1 valley 258 Deresemail_Degirmenb 681 13 320 slope 267 Karahasanlar 600 0 53 flood 269 Asagi Hasanlar 627 14 353 slope 520 Dagoren 1400 0 -1 slope 532 Huyuk Koyu 1400 0 -1 valley 584 Taskaracalar 1450 0 52 valley 607 Demircioren 1350 0 46 slope 621 Yenice_G30d3 1350 0 53 valley 702 Kuyupinar 1400 0 -1 slope 796 Süleymanli 700 0 -1 flood 814 Hacilar_H31b3 559 0 55 flood 883 Yukari Caykoy 550 0 -1 flood

Figure 4.8. Location of discarded settlements

Landform map is intersected with unsuitable topographic map to clip out discarded landforms. Total amount of discarded landforms over the area is 9.81 %. Statistical information about discarded landforms is given in Table 4.9. Slope landform has the maximum amount of removed area with a percentage of followed by other three with amounts between 1.1 and 1.5 %.

Examples of removed areas are illustrated in Figures 4.9, 4.10, 4.11and 4.12 for flood, valley, slope and top, respectively. In all figures, red color indicates removed areas and grey color indicate areas remained. As seen in the figures, depending on topographic properties, sometimes a partial area is removed while in some others almost the whole landform is discarded.

Distribution of removed landforms within the area is shown in Figure 4.13. Most of the removed flood areas are located around Kızılırmak River and its tributaries. Slope landforms are mostly removed from central and northern parts of the area. Valley and top landforms, on the other hand, do not indicate any certain concentration but rather randomly distributed throughout the area.

Table 4.9. Percentages of discarded landform due to masking analysis.

Surface of discarded % of discarded % within the area (km2) area whole area Flood 974.95 12.88 1.3 Valley 1.124.5440 14.85 1.5 Slope 4.4.79.569 59.17 6.0 Top 991.169 13.09 1.1

A B

Figure 4.9. Examples of removed flood landforms (red: removed area, grey: remained area; distance between two grid lines is 1 km).

A B

Figure 4.10. Examples of removed valley landforms (red: removed area, grey: remained area; distance between two grid lines is 1 km)

A B

Figure 4.11. Examples of removed slope landforms (red: removed area, grey: remained area; distance between two grid lines is 1 km)

A B

Figure 4.12. Examples of removed top landforms (red: removed area, grey: remained area; distance between two grid lines is 1 km)

59 Distribution of discarded landform within the study area. Figure 4.13.

4.2. Investigation of Relationship Between Settlement Locations and Morphological Landform

In this section, the remained landforms and associated settlements will be analyzed to seek the probable relationship between the two. The section is composed of three parts. In the first part, the relationship between them in terms of preference will be investigated. In the next section, the position (location) of the settlements within each landform will be searched. In the third section, type of the nearest landform for the settlements will be analyzed.

4.2.1. Settlement Location versus Morphological Landform Class

Frequency and percentages of the settlements and landforms are given in Table 4.10. The histograms of these percentages are extracted to find the final score for the preference (Figure 4.14). The positive numbers imply that the people settled in this landform more than the percentage provided by the nature. Therefore, this landform is preferred. The negative number, on the other hand, suggests that although the landform is available, people did not prefer to settle there. Flood and valley landforms, accordingly, are preferred; slope and top are avoided landforms. These results, in general resemble the initial values found before masking the area (compare Table 4.10 with Table 4.1). In both tables positive and negative classes remain the same. The magnitude and the order of the preferred and/or avoided landform change (particularly for slope and valley) after masking the area.

Table 4.10. Final scores of the landforms obtained by subtracting settlement and area histograms

Settlement Settlement Area Percentage Difference

Count percentage Count of area (settle-land) Flood 73 8,37 715793 5,82 2,55 Valley 240 27,52 1694471 13,79 13,74 Slope 511 58,60 7395530 60,17 -1,57 Top 48 5,50 1274718 10,37 -4,87

The area remained during the masking process may stay due to one (-1), two (+1) or three (+3) suitable topographic property. Relative ratios of these scores for each landform are given in Table 4.11. The maximum percentage for (+3) score is obtained by valley landform (about 60 %) which is a consistent value with other results.

Table 4.11. Frequency and percentages of the settlements within the landforms for three scores.

Frequency Percentage (-1) score (+1) score (+3) score (-1) score (+1) score (+3) score Flood 18 25 30 24.7 34.2 41.1 valley 24 71 145 10.0 29.6 60.4 Slope 72 218 221 14.1 42.7 43.2

Remaining Settlements 70 60 50 40 % 30 20 10 0 Flood Valley Slope Top Landform Classes

Remaining Landform Area

70 60 50 40 % 30 20 10 0 Flood Valley Slope Top Morphological Landform Classes

Landform Preferences for Settlement Locations

5 % 0 Flood Valley Slope Top -5

-10 Morphological Landform Classes

Figure 4.14. Resultant histogram (settlement-landform) showing preferred (positive) and avoided (positive) landform classes.

62 4.2.2. Distance Ratio Analysis

Position of the settlement within a landform class may imply valuable information on the selection of this landform. For this reason an analysis, called “distance ratio analysis” is performed that tests the relative position of the settlement within the landform polygon. The procedure for measuring necessary distances is shown in Figure 4.15 for each landform. Two distances (a and b) are measured for each settlement. The distance “a” is measured from the location of settlement to: - the nearest margin for flood type landform - the stream (downward) for the valley type landform - the upper boundary of valley (downward) for slope type landform, and - the nearest boundary for the top type landform The distance “b”, on the other hand is the distance between: - the two margins of the flood plain for flood type landform, - the stream and the boundary of slope for valley landform, - the valley (or flood) boundary to top boundary for slope landform, - the slope boundary and topographic divide for top landform. The distance ratio is then calculated as a/b for each settlement. The range and the meaning of distance ratio for each landform class are explained below: - For the flood landform the range is between 0 and 0.5. Minimum value (0) indicates that the settlement is located on either margin and maximum value (0.5) indicates that the settlement is located at the center of the flood polygon. - For the valley landform the range is between 0 and 1. Minimum value indicates that the settlement is located over the stream and the maximum value indicates that the settlement is on the slope boundary. - For the slope landform the range is between 0 and 1. The minimum value indicates that the settlement is on the valley (or flood) boundary and the maximum value indicates that the settlement is on the top boundary. - For the top landform the range is between 0 and 1. The minimum value indicates that the settlement is located on the slope boundary and the maximum value indicates that the settlement is located over the topographic divide. Histograms of the distance ratio for each landform are illustrated in Figure 4.16. In all histograms certain trends with gradual increase (or decrease) can be observed. Following information can be extracted by visual interpretation of these histograms: - Flood type settlements are located towards the margin of the flood plain. About 40 % of the settlements have a ratio of less than 0.1, which suggests that they are located within the outer 20 % zone (close to the margin).

63 - Valley type settlements are mostly located towards the upper boundary of the valley polygon close to the slope landform. Low percentage at smaller ratio suggests that people avoid settling in the close vicinity of stream channel. - Slope type settlement is the most consistent example showing a maximum concentration at lower ratios. Low ratio for the slope landform suggests that the settlements are very close either to valley or flood landform. - Top type settlements show a gradual decrease at distance ratio towards the topographic divide. Most of the settlements are, therefore, located around the hill where the slope tends to increase.

Figure 4.15. Measuring required distances

64 Flood 25

0 0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,40 0,45 0,5

Distance Ratio Valley 50 45 40 35 30 25 20 15 10 5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Distance Ratio

Slope 18 16 14 12 10 8 6 4 2 0 00.10.20.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Distance Ratio Top 25

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Distance Ratio

Figure 4.16. Histograms for the distance ratio for four landform settlements.

65 4.2.3. Nearest Landform Analysis

Histograms prepared in previous section (Distance Ratio Analysis) indicate that concentration of settlements towards the both margins of the histograms is a common feature. That means that the settlements are mostly close to another landform class. For example, in the histogram for slope (Figure 4. 16) more than half of the settlements are very close to another landform class. The histograms, however, do not indicate the type of the nearest landform class. In most cases the nearest landform class can be important in the selection of settlement site. For this reason, an analysis of this class should be made.

Although, one settlement can be close to the boundary of more than one class, arithmetically the shorter distance is considered to determine the nearest landform. The nearest landform analysis, therefore, is simply the shortest distance from the settlement to the neighbor class. These distances are measured for all settlements and the nearest landform class is assigned for each settlement. (Nearest classes for each settlement are included in Appendix A).

Summary of the “nearest landform class analysis” is given in Table 4.12. The results indicate that three of the landform settlements have consistently only one neighbor landform class. These neighbor classes are: - slope for the flood settlements (90 %) - slope for the valley settlements (97 %) - slope for the top settlements (98 %)

Table 4.12. Results of the Nearest Landform Analysis Nearest Landform Class Count Flood Valley Slope Top

Flood 79 8 71 0 Settlements

Valley 244 6 237 1 Settlements

Slope 519 60 329 130 Settlements

Top 49 0 1 48 Settlements

High percentage of slope landform as the nearest class for other three landform settlements is natural because of the spatial pattern of the landforms. All these landforms should normally be bounded by “slope” area. Therefore the nearest landform indicated in three histograms for the flood, valley and top landforms (in Figure 4.16) should refer to slope landform.

66 The nearest landform for the slope settlements, on the other hand, shows variations compared to other three. The percentages of the nearest landforms are 63.4, 25.0 and 11.6 for valley, top and flood, respectively.

4.3. Interpretation of Results

Final interpretation of the settlement location in relation to the landform classes is shown in Figure 4.17. Three major sites are detected in Çankırı area preferred by people to settle. These are illustrated by ellipse in the figure and called as “settlement zones”. During determination of these zones following criteria are used: - percentages of settlements in each landform (Table 4.10) - distances ratio (Figure 4.16) - nearest landform class (Table 4.12)

Figure 4.17. Final interpretation of settlement positions

Two main conclusions derived from this diagram are:

1. The most preferred location is the transitional area between valley and slope (85.63 %). This is followed by flood-slope transition with 8.87 % and top-slope transition with 5.5 %. 2. Morphologic boundary of flood and top landform classes are consistent with the perception of people during the selection of the settlement site. The boundary between valley and slope landforms, on the other hand, cross-cut the settlement zone defined by the locations of the settlements. Although valley-slope association seems to be the most important factor in this selection, the morphologic boundary between these two landforms is artificial.

CHAPTER V

DISCUSSION

This chapter contains three sections. In the first section, the algorithm of the method is discussed regarding general flow of the method. In the second section, the data used in this study and their effect on the accuracy of the results will be discussed. In the last section, the results obtained in this thesis will be discussed in relation to human perception of morphological landform types.

5.1. Algorithm and Structure of Method

The method proposed in this study investigates if people take the morphological landform classes into consideration during the selection of a site for their settlements or not. The method is simple, straightforward and easily applicable considering capability of existing software. There is not any major problem faced during the processes and analysis.

The method is composed of two main successive steps and uses data provided from topographic maps. In the first step, unsuitable areas are removed from the database. Certain landform classes and settlements are also deleted from database in accordance with this removed area. The only criterion in the removal of unsuitable areas is the topographic thresholds. In the second step of the method, the location of the settlements within the remained landform is investigated to reach a conclusion on the selection of settlement sites. General comments on the overall structure of the method are given below.

Other factors influencing selection of settlements: The method considers only topographic conditions in searching for a relationship between settlement and landform classes. All other possible factors that could be a criterion for the site selection are ignored in this study because of two main reasons: 1)The scope of this study is limited with the question “is there a relationship between landform types and settlement locations?”. The question “why people select this particular place” therefore is beyond the scope of the thesis, 2) Availability of data for other factors is still a problem in Turkey. For example, amount and location of water bodies, local natural economic resources, age of the settlements, forest and agricultural inventories, natural hazard maps (landslide, flood etc) and similar data are either not available or not accessible.

Application to different terrains: This study is applied to Çankırı Province which is characterized by certain morphological properties. The most prominent feature of the area is to have a rough topography with deeply dissected valleys and high mountains. The difference between the lowest and the highest elevations is about 2000 m. This topography, therefore, produces a landform classification that may differ from another terrain. In central Anatolia, for example, the classification used in this study can not be adopted. This is, however, not an important factor that can change the structure of the method. The classification made for another region with different types and names can be used in this method as well.

Selection of thresholds: Topographic thresholds are used in the method to remove unsuitable areas for settlement. Two different methods (masking and weighting) are suggested for this removal. Since the masking method considers two sub-analysis, the method proposes a total of three final products. The best output is selected among these three products and their values are assigned as thresholds. In this study, simply the ratio of remained settlements and remained topography is used to select the masking method. This selection, however, is user dependent and can be differentiate in some other studies. Various threshold values can be obtained by application of different masking methods and/or statistical analyses.

Further analysis: The method is normally completed after a certain relationship is determined between the landform type and the location of settlements. Further analysis, however, can be carried out for a detailed investigation of this relationship. Such analyses are not performed here because it is believed that a good conclusion is reached in the present study. The method, if necessary, can handle other analysis simply adding to the last step of the algorithm. Some examples of these analyses will be explained in the “Recommendations” section.

69 5.2 Data and Process

Accuracy of the results obtained in the method depends on the nature of the data used. In this section, some aspects of these data will be discussed.

Scale: All the data in this study area are derived from 1:25.000 scale topographic maps. It is believed that 1:25.000 scale topographic map is the most appropriate map as far as the size of the area is concerned. A larger scale map would produce unnecessary information and would artificially increase volume of data. A smaller scale map, on the other hand, would disable recognition of some information that would negatively affect accuracy of all datasets (DEM, settlement database and landform polygons).

Production of DEM and its derivatives: Digital Elevation Model (DEM) of the area is one of the most important input data from which various derivatives are prepared and used to define the thresholds for the removed areas. Three aspects of the DEM that may affect accuracy of DEM are digitization process, contour interval and grid size.

All the contours in the area are digitized manually from original topographic maps. An automated digitization process could not be applied because of the problems in the software. The manual digitization is, on one hand, a time consuming process, on the other hand, can produce erratic maps at various stages since it is a user dependent process.

Contour interval used in this study is 50 m for most part of the area. In some places where slope amount is low, extra contours (10 m or 5 m interval) are added to avoid wide spacing between the contours. Elevation, slope and aspect values of settlements are also read from the same DEM to provide consistency. Landform classes are digitized from hardcopy maps; therefore, the accuracy of the DEM does not affect the landform polygons.

Grid spacing of 100 m is used in this study. Although, as mentioned earlier, several products with different grid sizes are prepared; finally 100 m resolution is believed to be the best selection. A finer grid size is not necessary if the size of the area is taken into consideration. A coarser grid size would affect particularly the settlement database in a negative way.

Morphological landform classes: Although the purpose of this study is not to introduce a landform classification for Çankırı area, a correctly classified landform has vital importance to test the model proposed in the thesis. As mentioned in the literature survey section, various disciplines perceive morphological landform classes in different ways; therefore there is a wide variety of classifications. A four-fold classification of the area as “flood”, “valley”, “slope”, and “top” suggested in previous studies is adopted in this study.

70 Manual digitization of landform classes: Digitization of landform vector data is performed manually and was the most time consuming process during the preparation of this thesis. This problem is the most important negative factor, if not solved, in the application of this method to other regions. Solution to this problem is to develop algorithms on automated digitization of landforms from topographic maps. As mentioned before, there are several attempts in the literature to overcome this problem, but the present level of the algorithms is not adequate to eliminate this problem.

Another problem of the manual digitization is that it is user dependent, and therefore, different people can digitize the same area in various patterns. This is partly due to the lack of definite numerical description of landform classes. For example, the boundary between a valley landform and a slope landform can be drawn slightly different in different applications. The lower boundary of top landform might be another confusing example.

Vector-raster conversion: Topographic data used in this study are in raster and landform data in vector format. During the intersection of these two data sets, the vector data are converted to raster format. Since the grid size of the raster data is 100 m, a certain part of the data is lost during this conversion. To overcome this problem in the thesis, the data are re-sampled to 25 m, preserving the attributes of each cell.

Settlement data: Settlements in the database are considered to be represented by a single point. This point is most probably the initial location of the settlement. Topographic properties of the settlements (values for elevation, slope and aspect) are read within a buffer zone with 100 m radius. To test the accuracy of these readings, in the first pass, two sets of measurements are read, one for single point, other for buffer zone. Comparison of these two sets indicates that although similar results are obtained for most of the settlements, there are still certain differences between these two sets. Field tests made on topographic maps show that the differences are due to the minor variations of topographic properties in the close vicinity of the settlement. It is then decided that the readings obtained from buffer zones are more reliable. Therefore the mean of each topographic parameter obtained from the buffer zone is assigned to the settlements. In this way, a maximum of 9 pixels are considered in the calculations. The results produce no erratic values for elevation and slope parameters. For the aspect value, however, the (-1) values assigned for flat areas can cause problems because there is no arithmetic meaning of this value. In such cases (-1) values are not included in the calculations if number of such pixels is less then four; otherwise (-1) is assigned for this settlement.

71 5.3. Results of the Analyses

This thesis is one of the first studies that quantifies morphological landform classes and links this to the location of settlement location. Although the main emphasis of the thesis is to develop a method that seeks this relationship, the results obtained after it is tested for an area is an important criterion for the applicability of the method. For this reason, validity of the results obtained in this thesis will be briefly discussed here.

The results obtained in the thesis clearly indicate that, people preferred to settle at valley- slope transition. The concentration of the settlements, referred to as “settlement zone” in this thesis, include the boundary of valley and slope. Therefore, a scientific classification of landform for valley-slope transition is not consistent with the landform recognition of people.

Other two concentrations, on the other hand, for flood and top landform are almost parallel to the concentration of “settlement zones”. Accordingly, the only problematic boundary to classify morphological classes with respect to the human perception is valley-slope boundary.

Numerical analyses indicate that people relatively prefer to settle in valley and flood areas and avoid slope and top areas. Determination of the main reasons for this decision is almost impossible with the existing information. To answer the question “why they prefer that landform” requires further information. It is believed that so many factors that can affect selection of a site. Some of these factors are mentioned earlier such as natural resources, social impacts etc. It is believed that a survey in the area that will focus on the selection of settlements and recognition of landform by local people would contribute a lot to the understanding of settlement-landform relations.

CHAPTER VI

CONCLUSIONS AND RECOMMENDATIONS

6.1. Conclusions

This study is carried out in Çankırı region to investigate the relationship between settlement location and morphological landform classes. A total 891 settlements are evaluated in the analysis. Topographic data, settlement data and landform data are three main input sets.

The most important outcome of this thesis is the method developed to seek that relationship. The method is composed of two main steps. In the first step, unsuitable areas are determined from area using topographic thresholds and related settlements and landforms are discarded from database. In the second step, percentages of the remaining areas and settlements are used to evaluate settlement-landform relationship. “Distance ratio analysis” and “nearest landform class analysis” are performed for final interpretation of the results. The method is one of the first proposals investigating this relationship. It is believed that it can be applied to other terrains with their own landform classification.

Two main conclusions are derived after the analyses are completed. The first conclusion is on the quantitative distribution of the settlements among existing landform classes (flood, valley, slope and top). Percentages of settlements flood, valley, slope and top are found as 8.37, 27.52, 58.60 and 5.50, respectively. These percentages and the position of settlements in the landform polygons suggest that valley is the most preferred landform followed by flood type. Slope and top landforms are relatively less preferred. About 86 % of the settlements are concentrated along valley-slope boundary.

The second conclusion is on the morphologic landform classification versus human recognition of landform classes. Spatial distribution of settlement concentrations, “settlement zones”, is used to evaluate this recognition. Accordingly, morphologic top and flood landforms are conformable with human “settlement zones”. Concentration of settlement at valleys and slopes, on the other hand, indicate that the boundary of these two landforms is the most attractive for settlements and, therefore, shows an unconformity between morphologic and human classification.

6.2 Recommendations

Recommendations made here aim to contribute to further studies carried out in similar subjects to reduce process time and to increase reliability of results.

- Definition of landform classes is still a problematic matter. Further studies should be carried out for the most optimum classification (types and names of the classes) as well as parametric description of these classes.

- Manual digitization of landforms is a time consuming and user-dependent process. Automated classification algorithms should be developed that can be adapted to different terrains.

- Further statistical analyses on the spatial distribution of settlements should be carried out that can produce spatial weights for different parts of the area. These weights might be inserted into analysis proposed in this thesis.

- Only topographic properties of settlements are considered in this study. Other parameters, if available, such as initial age, population variation through different ages, natural resources in the vicinity etc should be included into the method.

- Modifications in various steps such as method of reading topographic parameters of settlements, determination of threshold values for masking unsuitable areas, decision on the masking method etc will increase reliability of the results obtained.

- Settlement selection is based on human perception, which is not included in the method developed here. The way people think on this subject can contribute too much to build a scientific frame in such studies. Such surveys can be, at least, used as assessment of the accuracy for the study.

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APPENDIX

SETTLEMENT DATABASE

Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 1 Doganlar_F29c F29-c3 494306 4543511 slope 892 4 165 0,33 valley 2 Sakarca H32-a1 588203 4471546 flood 551 2 316 0,04 slope 3 Cukurkoy F29-c1 488499 4552879 slope 650 2 271 0,12 valley 4 Guneykisla H32-a4 590714 4469057 slope 615 6 278 0,69 top 5 Bicikler F29-c1 487351 4553278 top 600 0 -1 0,81 slope 6 Abdullar_F29c2F29-c2 494240 4553805 slope 666 9 300 0,45 valley 7 Gulefler F29-c2 495032 4553659 valley 653 8 94 0,70 slope 8 Akcapinar_F29 F29-c2 495340 4554389 slope 722 12 127 0,73 top 9 Tepe_F29c2 F29-c2 494150 4555100 valley 762 10 277 0,27 top 10 Bayanpinar H32-a1 585069 4478057 flood 566 5 353 0,04 slope 11 Purahmetler F29-c2 493650 4553350 slope 653 5 300 0,12 valley 12 Kavlakli H32-a4 587293 4469754 flood 575 5 93 0,01 slope 13 Bostanli H31-b4 569388 4464980 flood 563 0 14 0,24 slope 14 Sarilar F29-c2 498882 4553922 slope 795 7 320 0,42 valley 15 Yunuslar_F29c F29-c2 498100 4553950 top 734 8 304 0,29 slope 16 Toklar F29-c2 497702 4553776 slope 718 10 84 0,17 valley 17 Bolukoren_F29 F29-c3 493415 4539491 top 1274 11 262 0,14 slope 18 Ortaca F29-c3 494050 4540950 slope 1196 17 294 0,55 top 19 Akbiyik F29-c3 489950 4541900 slope 1148 16 195 0,73 top 20 Hatipoglu F29-c3 494576 4542682 top 884 9 340 0,84 slope 21 Pelitcik F29-c3 490522 4540343 valley 1012 10 272 0,65 slope 22 Kizik F29-c3 490787 4539191 slope 1094 17 87 0,53 valley 23 Tasoglu F29-c3 497700 4539350 valley 930 8 236 0,85 slope 24 Yayaoglu F29-c3 497600 4540050 slope 939 14 87 0,20 valley 25 Dokuk F29-c3 499400 4539050 slope 1154 18 52 0,18 valley 26 Yakakoy F29-c3 495650 4539150 slope 1118 9 73 0,37 valley 27 Terzi_F29c3 F29-c3 495550 4539500 valley 1134 11 141 0,57 slope 28 Muratoglu F29-c3 496100 4539550 slope 1070 13 151 0,22 valley 29 Komesler F29-c3 496550 4539900 slope 1093 12 183 0,19 valley 30 Zayim F29-c3 490750 4541300 slope 1051 4 219 0,24 valley 31 Ovacik_F29c3 F29-c3 493192 4547347 slope 1141 4 15 0,67 top 32 Gümüsler F29-c3 492227 4547674 top 1181 7 275 0,35 slope 33 Sabanlar F29-c3 493700 4547250 slope 1145 5 348 0,74 top 34 Esenler_F29c3 F29-c3 495200 4547100 slope 1102 10 37 0,20 valley 35 Ahmetler F29-c3 498970 4550201 slope 1064 10 188 0,19 valley 36 Colak F29-c3 499650 4550100 slope 1082 10 194 0,06 valley 37 Sofular_F29c3 F29-c3 499750 4549650 slope 1089 8 335 0,20 valley 38 Aydinlar F29-c3 498550 4549100 slope 1047 8 297 0,30 valley 39 Bakirci F29-c3 497950 4548950 slope 1012 9 279 0,17 valley 40 Alinca F29-c3 490150 4545800 slope 1123 11 191 0,19 valley 41 Asagi_Alinca F29-c3 499776 4544383 slope 1007 8 180 0,34 valley

79 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 42 Ekincik_F29c3 F29-c3 495019 4548725 slope 996 8 70 0,84 top 43 Inceoglu F29-c3 495900 4548550 top 950 0 162 0,69 slope 44 Kadi F29-c3 495597 4548297 top 954 4 50 0,91 slope 45 Yayalar F29-c3 496050 4547950 valley 992 7 124 0,19 slope 46 Musatlar F29-c3 496850 4548750 valley 918 8 110 0,21 slope 47 Ganibeyler F29-c3 491329 4552070 slope 623 10 68 0,12 valley 48 Karagol F29-c3 490528 4551539 slope 776 9 62 0,24 valley 49 Karsi F29-c3 491831 4551587 slope 679 11 304 0,16 valley 50 Gumelik F29-c3 498184 4552600 slope 905 7 136 0,67 top 51 Sutcu F29-c3 497052 4552282 slope 862 14 323 0,62 top 52 Sindire F29-c3 496850 4551750 slope 826 11 248 0,47 valley 53 Inandik H31-a1 547741 4473441 flood 800 3 122 0,30 valley 54 Bedirler F29-c3 491427 4543453 valley 971 8 41 0,33 slope 55 Sogutcu_Kuzey F29-c3 490326 4544241 slope 983 10 227 0,15 valley 56 Sogutcu_Guney F29-c3 490650 4544050 slope 1004 4 264 0,16 valley 57 Demirciler_F29c F29-c3 491852 4544260 slope 1048 4 148 0,08 top 58 Kavaklar F29-c3 495824 4550625 slope 757 6 66 0,06 valley 59 Kargali F29-c3 495070 4550329 slope 974 14 90 0,44 valley 60 Kislakoy F29-c3 499250 4542750 valley 781 6 160 0,15 slope 61 Kislapazari F29-c3 498800 4542150 flood 798 2 53 0,41 slope 62 Cingiller F29-c3 497950 4542050 flood 800 0 -1 0,42 slope 63 Koltuk F29-c3 496850 4542750 slope 838 13 192 0,16 flood 64 Ote F29-c3 497050 4542150 flood 803 4 16 0,03 slope 65 Yenioren F29-c3 494996 4552591 slope 728 9 99 0,60 top 66 Osmankoy F29-c3 496043 4552596 valley 614 11 288 0,11 slope 67 Ilyaslar F29-c3 494151 4552655 slope 829 9 301 0,83 top 68 Bakircilar F29-c3 495169 4551929 slope 775 11 135 0,09 valley 69 Yiginot F29-c3 499850 4546650 slope 1056 14 164 0,27 valley 70 Alkisrak F29-c3 498400 4547450 slope 1125 14 153 0,19 valley 71 Eskikoy F29-c3 497050 4545500 slope 1086 16 168 0,66 valley 72 Buyuk Bahceli H31-b2 584117 4473943 valley 587 3 137 0,18 slope 73 Yigitler F29-c3 494500 4544950 slope 1177 11 176 0,68 top 74 Omerler_F29c3 F29-c3 493072 4543514 valley 938 13 155 0,87 slope 75 Imanlar_F29c3 F29-c3 491795 4543349 slope 978 9 19 0,16 valley 76 Caciklar H32-a2 595982 4476282 flood 550 0 58 0,50 slope 77 Basboyunduruk F29-c4 488803 4539966 valley 1100 2 123 0,88 slope 78 Dudas F29-c4 486860 4539902 slope 1046 17 47 0,44 valley 79 Musallar_F29c4 F29-c4 487300 4540400 slope 1088 19 220 0,35 valley 80 Kizilelma F29-c4 486200 4538950 valley 1088 15 30 0,41 slope 81 Saraycik_H31b3H31-b3 579559 4461007 slope 645 3 19 0,80 top 82 Karaomer H32-a1 591072 4481579 valley 600 0 106 0,31 slope 83 Beytarla Y. G28-b2 457334 4527590 slope 1331 11 345 0,61 top 84 Kapakli_H32a1 H32-a1 587875 4478750 slope 580 0 -1 0,19 flood 85 Beydini F29-c4 485885 4546690 slope 863 23 95 0,44 valley 86 Boyali F29-c4 485138 4551844 valley 634 5 220 0,44 slope 87 Hatlar F29-c4 484974 4551115 slope 663 10 313 0,45 valley 88 Koseler F29-c4 484950 4551900 slope 628 6 182 0,10 valley 89 Mustafaaga F29-c4 489127 4552428 slope 697 5 23 0,10 valley 90 Kucuksu F29-c4 488117 4552022 slope 709 7 329 0,29 valley

80 Coordinates Topographic Properties Nearest Id Settlement Topo Landform Distance Easting Northing Landform No Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 91 Surler F29-c4 488450 4551077 slope 864 12 352 0,48 top 92 Sazkoy F29-c4 486676 4548174 top 695 7 222 0,96 slope 93 Guney_F29c4 F29-c4 487731 4547531 slope 834 20 217 0,24 valley 94 Suluk F29-c4 487950 4542700 slope 1111 16 341 0,58 top 95 Gocek F29-c4 489134 4544163 slope 961 8 279 0,22 valley 96 Derekoy_F29c4 F29-c4 487597 4543702 slope 978 8 304 0,57 valley 97 Catak_F29c4 F29-c4 486712 4543682 slope 819 9 242 0,23 valley 98 Yukarikayalar F29-c4 487603 4542095 slope 1081 15 259 0,57 top 99 Asagikayalar F29-c4 487050 4541800 slope 936 11 246 0,07 valley 100 Cay_F29c4 F29-c4 486450 4541500 slope 893 12 63 0,10 valley 101 Otegece_F29c4 F29-c4 485900 4541650 slope 1006 18 151 0,37 valley 102 Govez F29-c4 485500 4541850 slope 983 13 73 0,18 valley 103 Samlar F29-c4 487088 4550527 slope 814 11 331 0,25 valley 104 Saylar F29-c4 486737 4549564 slope 849 11 290 0,83 top 105 Dogancilar F29-d3 473675 4540964 valley 757 9 210 0,23 slope 106 Karaoren_F29d3F29-d3 472909 4541218 slope 728 12 186 0,01 valley 107 Acemler F29-d3 471682 4540659 slope 680 12 127 0,01 flood 108 Kuzyaka F29-d3 472100 4539920 slope 900 13 145 0,33 flood 109 Ozlu Y._Kuzey H30-a1 505473 4480712 valley 1663 7 307 1,00 slope 110 Babalar F29-d4 461750 4540700 valley 771 9 186 0,20 slope 111 Kartak F29-d4 460750 4540700 slope 813 11 76 0,04 valley 112 Yaylar F29-d4 462930 4539125 slope 650 7 204 0,11 flood 113 Kulatkoy F29-d4 461329 4542695 slope 1238 14 193 0,23 valley 114 Asagi Alagoz H31-b3 580064 4468269 flood 559 2 165 0,03 valley 115 Terzi_F29d4 F29-d4 460884 4543073 slope 1273 9 195 0,43 valley 116 Catak_Bati F30-c3 537404 4541005 valley 1237 9 227 0,80 slope 117 Catak_Dogu F30-c3 536842 4540748 valley 1209 9 231 0,78 slope 118 Koclu F30-c4 524657 4540475 slope 1008 11 14 0,54 valley 119 Feriz F30-c4 522195 4542878 slope 945 16 273 0,46 valley 120 Ambarozu F30-d1 500192 4552874 slope 815 10 37 0,22 valley 121 Yahya F30-d1 502242 4553018 slope 604 15 75 0,12 valley 122 Yuvacik F30-d1 500563 4553965 slope 790 10 18 0,61 valley 123 Derekoy_F30d3 F30-d3 519961 4542027 slope 1064 16 308 0,22 valley 124 Ortakoy F30-d3 519420 4541357 slope 1106 13 101 0,81 top 125 Yaylatepe F30-d3 515457 4545617 slope 959 14 23 0,61 top 126 Karakuzu F30-d3 515284 4542276 slope 923 9 253 0,10 valley 127 Hacilar_F30d3 F30-d3 515696 4543014 slope 885 13 346 0,05 valley 128 Yukari KarakuzuF30-d3 515850 4541800 slope 1026 12 304 0,44 valley 129 Dahanlar F30-d3 515200 4541300 slope 1046 11 327 0,10 valley 130 Dere_Karakuzu F30-d3 515112 4541922 valley 940 8 14 0,43 slope 131 Cayircik F30-d3 513060 4542578 slope 946 12 244 0,28 valley 132 Evkadi F30-d3 513115 4543588 slope 958 16 277 0,45 valley 133 Hakalmaz F30-d3 511291 4545101 slope 823 24 80 0,23 valley 134 Goynukoren F30-d3 512268 4540959 slope 996 12 320 0,11 valley 135 Hasanlar_F30d3F30-d3 511976 4541184 slope 966 8 151 0,06 valley 136 Camdibi F30-d3 511780 4540344 slope 1091 17 58 0,07 valley 137 Dere_Goynukor F30-d3 512250 4540150 slope 1100 10 315 0,04 valley 138 Imatlar F30-d3 512354 4540406 slope 1097 11 319 0,16 valley 139 Sogucoluk F30-d3 511203 4539363 slope 1361 14 31 0,61 top

81 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 140 Harmancik F30-d3 518445 4543652 slope 904 5 79 0,73 valley 141 Belen_Guney F30-d4 502800 4539850 slope 1130 13 78 0,26 top 142 Belen_Kuzey F30-d4 502600 4540150 slope 1062 11 332 0,17 valley 143 Samli F30-d4 502050 4540400 slope 1028 13 44 0,28 valley 144 Sonya F30-d4 501721 4542133 slope 721 9 331 0,13 valley 145 Kahvecikoy F30-d4 502203 4542492 valley 703 3 186 0,39 flood 146 Dabazali F30-d4 503600 4542200 slope 701 3 96 0,14 valley 147 Ercek_F30d4 F30-d4 500573 4538922 slope 1140 10 151 0,11 valley 148 Egbeller F30-d4 500550 4540500 top 991 6 71 0,14 slope 149 Avlagikaya F30-d4 501420 4545176 slope 1110 11 273 0,14 valley 150 Emirler F30-d4 503700 4543700 slope 847 13 204 0,28 valley 151 Soganli F30-d4 502560 4549747 slope 1031 16 79 0,77 top 152 Cevre F30-d4 503773 4551632 slope 504 8 65 0,08 flood 161 Istiyetopcu F30-d4 506197 4539845 slope 951 15 146 0,34 valley 162 Ova_Istiyetopc F30-d4 506186 4541698 slope 702 10 51 0,04 valley 163 Kavak F30-d4 510320 4541266 slope 1150 3 89 0,67 top 164 Incekaya_Dogu F30-d4 507738 4540384 slope 1075 12 228 0,47 valley 165 Incekaya_Bati F30-d4 507351 4540349 slope 974 17 259 0,26 valley 166 Ekincik_F30d4 F30-d4 508335 4541937 slope 964 9 325 0,74 top 167 Burumcek F30-d4 507852 4539659 slope 1057 19 275 0,20 valley 168 Orta_Saraycik F31-c4 564600 4539162 slope 1306 7 165 0,18 valley 169 Kumet_Sarayc F31-c4 564794 4539265 slope 1314 9 171 0,16 valley 170 Tondur_Sarayc F31-c4 565283 4539312 valley 1332 10 216 0,79 slope 171 Comar_Dogu F31-d3 561644 4542779 valley 1311 7 148 0,24 slope 172 Comar_Bati F31-d3 562403 4542849 valley 1327 15 254 0,89 slope 173 Eksik F31-d3 556932 4541291 slope 1394 11 150 0,10 valley 174 Kiymik F31-d3 557058 4540226 valley 1284 11 59 0,67 slope 175 Mulayim F31-d3 559173 4541454 slope 1283 14 140 0,33 valley 176 Duz F31-d3 559600 4541650 slope 1242 15 148 0,23 valley 177 Murathaci F31-d3 558785 4541560 slope 1373 20 159 0,65 top 178 Donayse F31-d3 558508 4541099 slope 1349 10 137 0,56 valley 179 Yenice_F31d3 F31-d3 560172 4542248 slope 1290 11 127 0,15 valley 180 Yuvademirciler_F31-d3 560620 4540053 slope 1514 11 259 0,61 top 181 Kissenir F31-d3 559789 4540222 slope 1248 15 272 0,34 valley 182 Bolme G28-b1 446600 4526974 slope 1424 7 126 0,33 valley 183 Hasanlar_G28bG28-b1 444136 4535293 slope 989 8 135 0,42 flood 184 Salmanlar G28-b1 445806 4536188 flood 967 6 171 0,27 valley 185 Imamlar_G28b G28-b1 445235 4536655 slope 1082 12 120 0,20 valley 186 Kozdere G28-b1 445539 4536882 valley 1084 13 127 0,93 slope 187 Kayalar G28-b1 446632 4537224 valley 1002 9 189 0,60 slope 188 Derekoy_G28b G28-b1 446733 4537785 valley 1046 14 179 0,59 slope 189 Adiller G28-b2 448112 4527637 slope 1351 12 143 0,42 valley 190 Belen G28-b2 456379 4534825 slope 1165 8 106 0,59 top 191 Eskioglu G28-b2 456555 4535320 slope 1151 9 100 0,67 top 192 Orta_Belen G28-b2 455833 4534146 slope 1157 10 135 0,12 valley 193 Dagci G28-b2 455380 4534093 slope 1204 11 132 0,48 top 194 Budaklar G28-b2 457424 4532444 slope 910 8 134 0,82 top 195 Baldanlar G28-b2 457839 4532465 slope 868 8 128 0,63 top 196 Buyukyayalar G28-b2 455767 4531311 slope 907 8 215 0,30 flood 197 Haciahmetler G28-b2 456830 4530511 flood 825 7 167 0,11 slope

82 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 198 Eleler G28-b2 456410 4530728 slope 849 8 201 0,06 flood 199 Durmuslar G28-b2 455055 4530555 slope 947 5 52 0,84 top 200 Cotler G28-b2 454842 4531522 slope 973 14 152 0,15 valley 201 Hamzalar G28-b2 452936 4529272 flood 914 3 81 0,36 slope 202 Derekoy_Hamz G28-b2 453764 4529566 flood 892 3 144 0,30 slope 203 Seviller_Guney G28-b2 453700 4530350 slope 1000 6 112 0,26 valley 204 Burnuk G28-b2 454588 4528808 slope 1023 10 23 0,32 valley 205 Seviller_Kuzey G28-b2 453475 4530800 slope 1071 11 155 0,84 top 206 Kagizlar G28-b2 457716 4537313 valley 892 14 118 0,86 slope 207 Akgozoglu G28-b2 457549 4536526 valley 807 9 90 1,00 slope 208 Dereagil G28-b2 456890 4537835 valley 1032 13 173 0,58 slope 209 Haliccik G28-b2 457184 4536034 slope 1021 14 66 0,30 valley 210 Yaplan G28-b2 455910 4537094 slope 1171 16 101 0,55 top 211 Akpinar G28-b2 454302 4536952 slope 1253 10 148 0,17 valley 212 Kazlarkoy G28-b2 453702 4537073 slope 1329 10 150 0,47 top 213 Kabaarmut G28-b2 451183 4527822 slope 1202 10 93 0,47 valley 214 Sofular_G28b2 G28-b2 448601 4537719 valley 1068 8 277 0,97 slope 215 Karakoy G28-b2 448004 4538371 slope 1276 15 169 0,49 valley 216 Oren_Sofular G28-b2 449651 4537982 valley 1099 6 238 0,86 slope 217 Kirazlar G28-b2 450654 4538101 valley 1150 2 263 0,56 slope 218 Cayli_G28b2 G28-b2 457108 4530155 flood 823 5 123 0,10 slope 219 Cokusler G28-b2 457644 4529191 valley 942 5 8 0,54 slope 220 Asagikoy Cayli G28-b2 458000 4529386 slope 932 4 331 0,59 top 221 Guvez G28-b2 456631 4529169 top 966 7 326 0,57 slope 222 Kadirgil G28-b2 456329 4529407 valley 948 6 169 0,72 slope 223 Sevkiler G28-b2 451487 4531982 slope 1271 6 127 0,40 valley 224 Oruclar G28-b2 451518 4531808 slope 1258 4 146 0,09 valley 225 Turkmenler G28-b2 451048 4531718 slope 1293 6 129 0,57 valley 226 Imciler G28-b2 450728 4530741 valley 1250 0 44 0,49 slope 227 Demirciler_Sof G28-b2 449262 4530357 slope 1302 4 134 0,19 valley 228 Yaziboyu G28-b2 453953 4532370 slope 1042 8 196 0,37 valley 229 Seyhler_G28b2G28-b2 453107 4531856 slope 1077 9 74 0,43 top 230 Tasmanlar_G2 G28-b2 453731 4533500 slope 1268 6 125 0,59 top 231 Yurecik G28-b2 452529 4534877 slope 1212 8 106 0,47 valley 232 Mesecik G28-b2 453098 4535249 slope 1144 19 194 0,26 valley 233 Esenler_G28b2G28-b2 453532 4534855 slope 1105 8 179 0,09 valley 234 Bekirkoy G28-b2 453382 4535315 slope 1214 17 185 0,69 flood 235 Musalar_G28b G28-b2 452970 4535715 slope 1274 14 168 0,60 flood 236 Catacik G28-b2 454655 4535456 valley 1016 11 111 0,98 slope 237 Eskipazar G29-a1 460567 4532864 slope 750 0 -1 0,22 valley 238 Yorgular G29-a1 460519 4531168 slope 853 8 328 0,29 valley 239 Kincilar G29-a1 460122 4531266 slope 805 6 315 0,11 flood 240 Kurban G29-a1 459428 4532341 slope 760 4 86 0,05 flood 241 Istasyon G29-a1 460607 4534060 slope 731 7 91 0,10 flood 242 Arslanlar G29-a1 462899 4532933 valley 766 9 190 0,87 slope 243 Gevrekler G29-a1 463526 4531549 slope 908 9 12 0,51 valley 244 Ahirtas G29-a1 464341 4531546 slope 879 7 24 0,37 valley 245 Dibek G29-a1 464540 4531943 valley 844 5 324 0,75 slope 246 Bayindir_G29a G29-a1 466646 4525231 slope 1004 1 161 0,22 flood

83 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 247 Boncuklar G29-a1 468432 4529175 top 1096 5 185 0,82 slope 248 Karkin G29-a1 467800 4529900 top 954 6 254 0,44 slope 249 Gozlu G29-a1 463096 4529308 top 1015 4 79 0,35 slope 250 Tasmanlar_G2 G29-a1 462608 4529804 valley 1002 3 78 0,82 slope 251 Tefen G29-a1 462153 4529583 top 1032 4 28 0,23 slope 252 Tepekoy_G29a G29-a1 461950 4529300 top 1051 1 207 0,62 slope 253 Durallar G29-a1 463835 4528887 slope 963 6 16 0,06 valley 254 Oren_G29a1 G29-a1 463528 4527945 slope 1042 6 51 0,33 valley 255 Kadilar G29-a1 463430 4526664 slope 1155 11 64 0,65 top 256 Deresemail_De G29-a1 468160 4537084 slope 704 8 330 0,06 valley 257 Deresemail_De G29-a1 468174 4537392 valley 700 0 -1 0,35 slope 258 Deresemail_De G29-a1 467250 4536750 slope 681 13 320 0,26 valley 259 Deresemail_GoG29-a1 466700 4536400 valley 662 9 59 0,36 slope 260 Topcali G29-a1 468421 4532924 slope 1066 12 276 0,17 valley 261 Y.Topcali G29-a1 468302 4533661 slope 1118 9 162 0,35 valley 262 Hasli G29-a1 458681 4536468 valley 786 8 84 0,88 slope 263 Alagoz G29-a1 458299 4536910 valley 820 13 143 0,67 slope 264 Pasakoy_G29a G29-a1 458065 4537333 slope 875 12 177 0,07 valley 265 Imanlar_G29 G29-a1 466420 4528399 valley 962 5 209 0,54 slope 266 Kapicilar G29-a1 459314 4534003 slope 875 6 120 0,61 top 267 Karahasanlar G29-a1 464655 4538120 flood 600 0 53 0,36 slope 268 Yukari Hasanla G29-a1 464680 4537617 slope 637 10 239 0,47 flood 269 Asagi Hasanlar G29-a1 465521 4537878 slope 627 14 353 0,42 flood 270 Yukari Saray G29-a1 464297 4538658 flood 611 3 167 0,06 slope 271 Asagi Saray G29-a1 464826 4538721 slope 635 7 176 0,56 flood 272 Ucevler G29-a1 466404 4538246 slope 593 4 185 0,05 flood 273 Cami Kirankoy G29-a1 461487 4535057 flood 686 3 306 0,21 slope 274 Turpcular G29-a1 460918 4535288 valley 698 5 106 0,34 slope 275 Yeni_Kirankoy G29-a1 461225 4534952 flood 687 1 38 0,44 slope 276 Ces G29-a1 461618 4534362 slope 708 6 309 0,34 flood 277 Koycegiz_G29aG29-a1 462750 4538100 flood 667 11 253 0,45 slope 278 Taslikoy G29-a1 462050 4537950 slope 663 12 135 0,06 flood 279 Cavuslar KoyceG29-a1 462250 4538900 slope 645 2 137 0,04 flood 280 Ortakoy_G29a G29-a1 464292 4529960 slope 907 4 204 0,98 top 281 Yenikoy_G29a G29-a1 463407 4530186 slope 961 3 71 0,36 top 282 Yukarikoy_G29 G29-a1 463681 4529776 slope 960 7 89 0,42 top 283 Sariahmetler G29-a1 462350 4530500 slope 964 4 61 0,47 top 284 Ovakoy G29-a1 460100 4536900 valley 730 16 181 0,26 slope 285 Dereozu G29-a1 459456 4537715 valley 800 4 177 0,95 slope 286 Kuplu G29-a1 458857 4538809 slope 886 15 59 0,10 valley 287 Ozankoy G29-a1 459832 4527989 slope 1040 13 285 0,37 valley 288 Taslik G29-a1 460323 4525537 valley 1225 6 273 0,62 slope 289 Beytarla G29-a1 458135 4528860 slope 990 9 294 0,53 valley 290 Otedag F30-d4 506995 4539361 slope 865 13 74 0,04 valley 291 Yazikavak G29-a1 466133 4533995 slope 1023 8 246 0,44 valley 292 Asagi Keceler G29-a1 465782 4531748 valley 850 4 118 0,33 slope 293 Yukari Keceler G29-a1 466853 4531509 slope 900 7 308 0,23 valley 294 Kirankoy G29-a1 461573 4535315 slope 682 3 316 0,10 flood 295 Baspinar G29-a2 473088 4537645 valley 953 7 111 0,76 slope 296 Ercek_G29a2 G29-a2 475490 4538642 slope 1225 9 106 0,54 valley

84 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 297 Cayir_G29a2 G29-a2 470862 4537939 valley 817 8 290 0,88 slope 298 Hocalar G29-a2 470600 4537800 slope 842 11 218 0,08 valley 299 Softalar G29-a2 470163 4538016 slope 797 4 239 0,17 valley 300 Kurukavaklar G29-a2 469956 4538084 valley 790 8 202 0,78 slope 301 Mahmutlar G29-a2 468650 4530550 valley 1027 9 203 0,63 slope 302 Yahyalar G29-a2 469392 4529674 slope 1093 5 192 0,05 top 303 Bolukoren_G29 G29-a2 476619 4529159 slope 1214 8 303 0,44 valley 304 Kabaca G29-a2 478519 4528126 slope 1134 7 117 0,62 valley 305 Mutaflar G29-a2 478100 4529550 top 1212 5 188 0,48 slope 306 Karasu G29-a2 478150 4531050 top 1220 1 213 0,13 slope 307 Cumaderesi G29-a2 478070 4532307 valley 1200 1 200 0,86 slope 308 Candirlar G29-a2 473821 4532768 valley 1134 8 211 0,46 slope 309 Yemisler G29-a2 471893 4532183 slope 1153 7 255 0,76 top 310 Kizilcapinar G29-a2 471747 4531075 slope 1150 10 303 0,63 valley 311 Pelitcik_CandirlaG29-a2 471250 4529950 valley 1164 4 148 0,96 slope 312 Karsi_Candirlar G29-a2 471849 4530065 valley 1166 8 215 0,20 slope 313 Doglacik G29-a2 474100 4528400 valley 1145 5 200 0,74 slope 314 Saraycik_G29a2G29-a2 473757 4526440 slope 1070 5 164 0,22 valley 315 Yunuslar_G29a G29-a2 474559 4526214 top 1090 10 166 0,21 slope 316 Hatipler G29-a2 474896 4526695 slope 1140 6 291 0,26 top 317 Doganlar_G29a G29-a2 475900 4527150 slope 1150 1 24 0,94 top 318 Sadeyaka_GuneG29-a2 470936 4526633 slope 1031 4 170 0,66 valley 319 Sadeyaka_Kuze G29-a2 471200 4526834 valley 1039 4 190 0,38 slope 320 Seyhler_G29a2 G29-a2 472195 4525373 top 1025 4 168 0,93 slope 321 Sobucimen G29-a2 478765 4535726 slope 1326 10 170 0,80 top 322 Sarimehmet H32-a1 589995 4483621 top 650 0 103 0,82 slope 323 Tamislar G29-a2 469842 4532133 slope 1050 1 8 0,74 top 324 Emiroglu G29-a2 469779 4534242 slope 955 6 228 0,03 valley 325 Asagikoy Tamis G29-a2 470475 4533926 valley 968 10 280 0,27 slope 326 Yaka G29-a2 470907 4534635 slope 1213 13 212 0,70 top 327 Doruklar G29-a2 470050 4535350 slope 1128 11 249 0,56 top 328 Yesiller G29-a2 476918 4534500 slope 1310 7 137 0,95 top 329 Koseoglu G29-a2 476008 4534374 slope 1303 6 275 0,61 top 330 Yenikoy_Yesiller G29-a2 477436 4535488 slope 1261 5 216 0,18 valley 331 Demirciler_Yesi G29-a2 478132 4537967 top 1400 1 225 0,36 valley 332 Dag Cukuroren_G29-a3 471900 4517750 slope 1356 9 336 0,77 valley 333 Orta_Kuzdere G29-a3 475150 4518550 slope 1226 12 318 0,12 valley 334 Asagi_Kuzdere G29-a3 474979 4518912 valley 1157 7 246 0,89 slope 335 Yukari Kuzdere G29-a3 475500 4518450 slope 1252 8 343 0,61 valley 336 Goynukcukuru G29-a3 471442 4520273 slope 1131 11 301 0,19 valley 337 Bolukoren Goyn G29-a3 472479 4519462 slope 1326 14 180 0,18 valley 338 Yenikoy_Yukari G29-a3 478350 4522600 slope 1231 7 154 0,55 top 339 Yenikoy_Asagi G29-a3 478800 4522250 valley 1186 7 222 0,85 slope 340 Yenikoy_Kuruz G29-a3 478800 4520050 slope 1197 8 309 0,42 valley 341 Corduk G29-a3 476850 4522200 slope 1237 10 130 0,21 valley 342 Hamamli G29-a3 470450 4524600 slope 1000 0 220 0,45 flood 343 Kisac_G29a3 G29-a3 472350 4523750 slope 1290 13 320 0,76 top 344 Yesiloren G29-a4 467450 4518200 slope 1402 7 118 0,77 top 345 Deresoplan G29-a4 462100 4522750 slope 1159 12 55 0,51 valley 346 Dere_Deresopla G29-a4 462157 4524597 valley 1136 7 29 0,45 slope 347 Gokyeri G29-a4 461400 4524350 slope 1200 5 97 0,38 valley

85 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 348 Orencik_G29a4 G29-a4 460300 4524150 slope 1258 7 31 0,22 top 349 Bozkus_G29a4 G29-a4 458900 4524850 slope 1299 4 154 0,83 top 350 Kuzoren_G29a4 G29-a4 466550 4522150 slope 1214 13 325 0,86 valley 351 Akbas G29-b1 485841 4527525 slope 1078 12 39 0,10 valley 352 Beydili G29-b1 487105 4535108 valley 1304 3 126 0,48 slope 353 Beymelik G29-b1 483354 4531843 slope 1253 7 261 0,61 top 354 Soguksu G29-b1 481157 4531999 slope 1257 6 148 0,14 valley 355 Gocuk G29-b1 482975 4530631 slope 1200 7 249 0,64 top 356 Boduroglu G29-b1 488796 4536643 slope 1306 17 156 0,45 valley 357 Besiraga G29-b1 489341 4536692 slope 1236 15 141 0,41 valley 358 Yayaoglu G29-b1 488878 4535654 top 1250 2 178 0,02 slope 359 Dagdibi G29-b1 485332 4538643 slope 1279 19 321 0,60 top 360 Kuzoren_G29b1 G29-b1 488431 4528346 slope 995 8 338 0,14 flood 361 Meydan G29-b1 485835 4530065 top 1213 5 145 0,18 slope 362 Karakoca G29-b1 487576 4529618 slope 1055 12 199 0,47 top 363 Orenli G29-b1 479597 4525119 slope 1369 6 118 0,35 top 364 Ahilar G29-b1 480818 4526415 slope 1249 3 97 0,66 valley 365 Tashanlar G29-b1 483809 4533767 slope 1308 3 240 0,40 valley 366 Kizilcaoren G29-b1 483400 4533900 slope 1306 3 184 0,83 top 367 Kocekler G29-b1 485690 4533621 slope 1308 4 144 0,35 top 368 Yiprak G29-b1 484605 4530558 slope 1168 9 197 0,27 valley 369 Tohumlar G29-b1 484078 4529026 valley 1031 8 211 0,27 slope 370 Kisla_G29b1 G29-b1 482950 4529250 valley 1000 0 -1 0,08 slope 371 Kirenozu G29-b1 481905 4528872 valley 1000 3 158 0,91 slope 372 Haydarlar G29-b1 483050 4534950 valley 1344 3 242 0,82 slope 373 Gokceler G29-b1 487600 4531250 slope 1308 7 141 0,48 top 374 Gomlekciler G29-b1 482500 4535150 slope 1348 3 203 0,23 valley 375 Yenikoy_G29b1 G29-b1 479976 4535656 slope 1314 9 178 0,56 top 376 Dogancilar_G29 G29-b1 481332 4535459 slope 1366 7 203 0,57 valley 377 Kapakli_G29b1 G29-b1 479837 4530635 top 1268 3 204 0,78 slope 378 Tokmakoglu G29-b1 480858 4530705 top 1256 4 115 0,32 slope 379 Semerciler G29-b1 479300 4530100 slope 1259 5 96 0,30 valley 380 Sallar G29-b1 479300 4534000 top 1307 3 338 0,76 slope 381 Yurekoren G29-b2 489637 4535740 slope 1250 7 339 0,55 top 382 Cedime G29-b2 496255 4525145 slope 1513 10 189 0,35 valley 383 Catak_G29b2 G29-b2 496418 4537570 valley 1099 3 295 0,53 slope 384 Karaagac_G29b G29-b2 495850 4537600 valley 1100 2 46 0,56 slope 385 Hankoy F29-d3 468538 4539225 flood 591 6 306 0,14 slope 386 Demirci_G29b2 G29-b2 495596 4538032 valley 1078 9 127 0,80 slope 387 Cayli_G29b2 G29-b2 492094 4529750 flood 932 12 236 0,07 slope 388 Yuruk G29-b2 491350 4530950 valley 1051 8 166 0,84 slope 389 Beykoy_G29b2 G29-b2 490073 4531010 slope 1236 14 110 0,68 valley 390 Yusufoglu_G29bG29-b2 490350 4528878 slope 1080 10 272 0,28 flood 391 Govem G29-b2 493377 4529621 slope 1101 10 151 0,29 flood 392 Dokecek G29-b2 491120 4537236 slope 1226 14 308 0,28 valley 393 Sagiroglu G29-b2 491005 4536591 slope 1225 12 295 0,34 valley 394 Deveci G29-b2 489711 4537514 slope 1269 17 99 0,42 valley 395 Findicak G29-b2 499020 4533050 slope 1263 14 171 0,58 valley 396 Yukari Findicak G29-b2 499100 4533450 slope 1340 11 179 0,57 valley 397 Kabak G29-b2 496148 4529264 valley 1081 2 120 0,84 slope 398 Incigez G29-b2 498465 4529773 top 1108 6 153 0,13 slope

86 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 399 Sofuoglu_G29bG29-b2 492919 4535899 slope 1422 9 277 0,67 top 400 Sarioglu G29-b2 492400 4536400 slope 1401 10 181 0,20 valley 401 Kuzgun G29-b2 498900 4538250 slope 1178 17 281 0,29 valley 402 Ulukoy G29-b2 496145 4532604 slope 1297 10 165 0,42 valley 403 Asagi_Ulukoy G29-b2 496100 4532400 slope 1252 16 153 0,36 valley 404 Incebogaz G29-a2 475898 4532377 slope 1153 5 188 0,05 valley 405 Karasar G29-b2 493573 4532690 slope 1285 9 152 0,53 valley 406 Seyhler_G29b2G29-b2 496043 4538022 valley 1056 7 210 0,85 slope 407 Asagi Kasar_B G29-b2 493289 4532310 slope 1242 13 155 0,34 valley 408 Cerkes G29-b3 490929 4518082 slope 1132 1 239 0,05 flood 409 Ahirkoy G29-b3 495027 4513459 valley 1198 1 21 0,54 slope 410 Aliozu G29-b3 495961 4520302 valley 1250 2 203 0,97 slope 411 Bozoglu G29-b3 493283 4515002 valley 1165 6 76 0,17 slope 412 Calcioren G29-b3 496413 4523928 slope 1465 5 197 0,52 valley 413 Coroglu G29-b3 495705 4523501 slope 1420 4 78 0,56 top 414 Kadiozu G29-b3 497901 4518372 valley 1265 3 114 0,75 slope 415 Karamustafa G29-b3 498932 4515925 flood 1172 2 232 0,31 valley 416 Gelik G29-b3 493595 4521480 top 1315 6 217 0,20 slope 417 Ovacik_Gelik G29-b3 494410 4521920 slope 1358 5 186 0,33 top 418 Orenkoy G29-b3 490041 4514669 valley 1164 1 125 0,78 slope 419 Seyhdogan G29-b3 491816 4522212 slope 1325 6 208 0,27 top 420 Eymir G29-b3 490765 4522732 slope 1353 8 168 0,19 top 421 Yalakozu G29-b3 498659 4513160 slope 1192 8 82 0,04 flood 422 Akhasan G29-b4 483603 4513489 slope 1214 8 101 0,69 top 423 Bayindir_G29b G29-b4 481204 4519260 slope 1196 5 128 0,07 valley 424 Ilica_G29b4 G29-b4 483400 4519150 flood 1101 2 165 0,11 slope 425 Bedil G29-b4 486281 4520921 slope 1208 11 223 0,43 valley 426 Balkavak G29-b4 479159 4523712 slope 1288 6 151 0,62 top 427 Karaagac_G29 G29-b4 479847 4524184 slope 1286 7 150 0,30 top 428 Nahilar G29-b4 482149 4524023 slope 1324 9 198 0,79 top 429 Kurtcimeni G29-b4 479800 4521500 flood 1069 15 138 0,20 slope 430 Dikenli_G29b4 G29-b4 482157 4516376 valley 1199 3 335 0,62 slope 431 Halkoglu G29-b4 482464 4511387 slope 1251 3 140 0,13 flood 432 Boyuncak G29-b4 480485 4512011 slope 1352 3 134 0,87 top 433 Kadikoy G29-b4 484465 4517482 top 1175 2 35 0,44 slope 434 Yalnizca G29-b4 483660 4515681 slope 1205 4 175 0,11 valley 435 Comlekci G29-b4 485301 4516882 slope 1159 4 117 0,27 valley 436 Kizillar G29-b4 487631 4522333 slope 1306 12 175 0,54 valley 437 Kinik G29-b4 489150 4520250 slope 1199 3 184 0,55 valley 438 Kiremitci G29-b4 488311 4516951 slope 1122 2 134 0,07 flood 439 Turbasi G29-b4 487864 4514457 flood 1159 2 91 0,08 slope 440 Yortan G29-b4 486168 4514842 flood 1151 1 336 0,24 slope 441 Karga_G29b4 G29-b4 484750 4511750 slope 1280 5 191 0,73 top 442 Orencik_G29b4G29-b4 485293 4512412 slope 1274 2 211 0,61 top 443 Abdullar_G29b G29-b4 485950 4511900 valley 1253 5 96 0,90 slope 444 Agacakoy G29-c1 482450 4509250 flood 1250 2 173 0,35 slope 445 Kisac_G29c1 G29-c1 485193 4507401 valley 1400 3 253 0,89 slope 446 Saraycik_Kuze G29-c1 480366 4510560 valley 1319 5 66 0,60 flood 447 Saraycik_Gune G29-c1 480150 4510750 slope 1333 5 93 0,11 valley 448 Yakuplar G29-c1 488951 4509126 slope 1353 3 48 0,30 valley 449 Yoncali G29-c1 480975 4506067 valley 1301 3 121 0,33 slope

87 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 450 Yumakli G29-c1 479399 4508091 slope 1350 2 111 0,30 valley 451 Yukari Yumakli G29-c1 478984 4507615 slope 1386 6 88 0,44 valley 452 Bozcaarmut_K G29-c1 484253 4504919 slope 1514 8 246 0,46 valley 453 Bozcaarmut_G G29-c1 484200 4505100 slope 1522 9 245 0,52 valley 454 Dagcukuroren_ G29-c1 486532 4509268 slope 1312 9 76 0,58 valley 455 Omerler_G29c G29-c1 486646 4510105 slope 1312 8 262 0,17 valley 456 Asagi_Dagcuk G29-c1 487470 4507131 slope 1400 2 100 0,08 valley 457 Gokce G29-c1 488155 4506680 slope 1504 8 331 0,17 valley 458 Elpirek G29-c1 488206 4507121 slope 1454 8 273 0,27 valley 459 Hacilar_G29c2 G29-c2 497842 4506110 valley 1300 1 215 0,93 slope 460 Buguroren G29-c2 499729 4499561 slope 1389 3 63 0,58 valley 461 Elden G29-c2 496233 4500700 valley 1500 2 236 0,56 slope 462 Dere Bayindir G29-c3 498813 4492196 valley 1420 9 120 0,59 slope 463 Dodurga_G29c G29-c3 499047 4494701 slope 1398 2 81 0,53 valley 464 Orta Bayindir G29-c3 498764 4490665 slope 1408 7 113 0,12 valley 465 Tumtac Bayind G29-c3 497672 4489225 valley 1441 6 111 0,78 slope 466 Karga_G29c3 G29-c3 495825 4491348 valley 1500 1 103 0,96 slope 467 Kayioren G29-c3 494872 4492608 flood 1500 3 135 0,13 slope 468 Incecik G29-c3 492305 4492577 valley 1563 7 86 0,94 slope 469 Pasanin Ciftligi H32-a1 592409 4478006 flood 540 5 337 0,04 slope 470 Karadibek H32-a1 585921 4476181 slope 580 0 101 0,55 valley 471 Karamursel H32-a1 588974 4475211 flood 540 2 353 0,06 slope 472 Afsar G30-a1 500368 4529547 slope 1162 6 322 0,10 valley 473 Erencik G30-a1 500815 4530114 slope 1172 7 288 0,26 top 474 Kiran G30-a1 502806 4530187 top 1229 9 79 0,59 slope 475 Kolavlaga G30-a1 503495 4530524 top 1193 5 119 0,47 slope 476 Cakmak G30-a1 502750 4536250 slope 1444 10 120 0,39 valley 477 Dodurga_G30a G30-a1 501000 4532450 valley 965 11 221 0,99 slope 478 Eyupozu G30-a1 508813 4527587 valley 1233 6 41 0,33 slope 479 Karacahuyuk G30-a1 502556 4532943 slope 1177 10 127 0,38 valley 480 Kizilibrik_G30a G30-a1 503087 4527548 slope 1401 9 148 0,51 valley 481 Orta_Kukurt G30-a1 504500 4529650 valley 1087 7 144 0,48 slope 482 Demirciler_Kuk G30-a1 505877 4529907 valley 1004 5 67 0,81 slope 483 Zevdes G30-a1 505850 4530950 slope 1093 9 136 0,85 top 484 Yazioren_Kuze G30-a1 509272 4532192 slope 958 8 176 0,08 valley 485 Yazioren_Gune G30-a1 509101 4532436 slope 997 9 199 0,36 valley 486 Kiyan G30-a1 509350 4531050 flood 850 2 82 0,10 slope 487 Kisla_G30a2 G30-a2 510559 4530995 valley 850 2 188 0,30 slope 488 Ucgazi G30-a1 507415 4532332 flood 854 6 174 0,06 slope 489 Cakirbag G30-a1 505181 4535658 slope 1474 8 234 0,21 valley 490 Karaoluk G30-a1 505079 4537882 slope 1239 11 119 0,51 valley 491 Sazak_G30a1 G30-a1 507190 4537883 slope 1343 18 175 0,43 valley 492 Gokcukur G30-a1 508210 4537883 slope 1170 16 25 0,08 valley 493 Alic G30-a2 517722 4535893 slope 1302 17 161 0,42 valley 494 Akseki G30-a2 519073 4536397 slope 1287 16 198 0,61 valley 495 Basovacik G30-a2 515200 4527700 slope 1299 6 169 0,35 valley 496 Bayramoren G30-a2 517100 4532650 slope 892 11 89 0,48 valley 497 Beykoy_G30a2 G30-a2 516378 4535022 slope 1043 21 95 0,21 valley 498 Kopurlu_G30a2G30-a2 516700 4534075 slope 810 10 178 0,10 valley 499 Akguney G30-a2 513950 4531000 valley 1000 3 261 0,58 slope 500 Catkese G30-a2 517850 4526700 slope 1250 0 -1 0,10 flood

88 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 501 Dalkoz_Gune G30-a2 519942 4533096 slope 959 12 74 0,54 top 502 Dalkoz_KuzeyG30-a2 519796 4533706 slope 848 9 238 0,26 flood 503 Dolas lar G30-a2 514083 4533652 slope 892 12 141 0,39 valley 504 Sarikaya_G30G30-a2 514410 4535044 slope 1269 17 129 0,54 valley 505 Yilmaz F29-d3 469234 4542747 flood 505 6 69 0,19 slope 506 Kemer_Yurtp G30-a2 512774 4532564 valley 834 10 102 1,00 slope 507 Cayir_G30a2 G30-a2 512168 4532182 slope 893 9 107 0,41 valley 508 Madenli G30-a2 520524 4527108 valley 1319 6 226 0,39 slope 509 Yusufoglu_G G30-a2 512750 4533150 slope 901 13 111 0,17 valley 510 Doganci G30-a2 512251 4533103 slope 1000 7 126 0,24 valley 511 Yukarikoy_G3G30-a2 512424 4533393 slope 982 14 112 0,30 valley 512 Karakisla G30-a2 513300 4533395 slope 897 13 147 0,27 valley 513 Dolap G30-a2 511127 4532674 slope 1049 10 146 0,42 valley 514 Yakali Koyu_OG30-a2 511479 4528686 slope 1159 12 331 0,54 valley 515 Yakali Koyu_KG30-a2 510688 4528557 valley 1127 9 94 0,68 slope 516 Yakali Koyu_DG30-a2 512200 4529150 valley 1066 11 165 0,80 slope 517 Asagi Kasar_G29-b2 493544 4532336 slope 1243 9 183 0,31 valley 518 Akcaoren_F2 F29-d4 459341 4542526 slope 1232 10 160 0,28 top 519 Dagtarla G30-a3 517006 4519253 flood 1244 4 327 0,05 valley 520 Dagoren G30-a3 519606 4512034 slope 1400 0 -1 0,05 top 521 Yesiloz_G30aG30-a3 516418 4523952 valley 1229 3 121 0,71 slope 522 Bozkus_G30aG30-a3 512056 4520081 valley 1240 4 56 0,73 slope 523 Budakpinar G30-a3 512164 4522505 flood 1242 1 105 0,48 slope 524 Cardak G30-a3 510879 4517465 flood 1212 1 329 0,20 slope 525 Cavundur G30-a3 514418 4518752 flood 1244 3 276 0,15 slope 526 Sacak G30-a4 501248 4514658 flood 1174 1 299 0,45 slope 527 Atkaracalar G30-a4 506205 4518244 valley 1249 1 165 0,90 slope 528 Ilker G30-a4 506858 4517124 flood 1205 1 131 0,25 slope 529 Demirli G30-a4 504500 4521000 valley 1326 4 112 0,72 slope 530 Ulupinar G30-a4 509861 4516363 slope 1226 5 326 0,06 flood 531 Susuz G30-a4 502114 4519732 valley 1300 0 11 0,79 slope 532 Huyuk Koyu G30-a4 505402 4524668 valley 1400 0 -1 0,79 slope 533 Cirdak G30-b1 527079 4529897 valley 1525 9 188 0,88 slope 534 Bogazkaya G30-b1 523750 4537750 slope 1003 15 153 0,34 valley 535 Karatas_KuzeG30-b1 521950 4537850 slope 1157 13 172 0,52 top 536 Karatas_Gun G30-b1 521950 4537550 slope 1089 13 185 0,44 flood 537 May is lar G30-b1 521527 4537582 slope 1111 12 156 0,48 top 538 Ketenciler G30-b1 521336 4537984 slope 1198 10 161 0,58 top 539 Oymaagac G30-b1 521150 4535900 slope 952 13 115 0,25 flood 540 Sarialan G30-b1 529944 4535519 top 1344 10 210 0,62 slope 541 Pinarcik G30-b1 527446 4534691 top 1063 8 354 0,12 slope 542 Belenli G30-b1 523200 4534150 slope 1025 7 7 0,37 top 543 Uzunoglu G30-b1 526254 4536387 valley 780 8 207 0,33 slope 544 Cay lıca G30-b1 521718 4529435 valley 1350 1 89 0,34 slope 545 Timarli H31-b3 580240 4466186 flood 556 1 23 0,27 slope 546 Sogutcuk G30-b2 533603 4526301 slope 1336 14 150 0,43 top 547 Aluc Koyu_DoG30-b2 542034 4536983 valley 1461 9 202 0,86 slope 548 Aluc Koyu_BaG30-b2 541247 4536740 slope 1452 8 185 0,21 valley 549 Asiklar G30-b2 538108 4530924 slope 1345 7 316 0,69 valley 550 Es kic e G30-b2 541800 4529200 slope 1000 0 -1 0,03 flood

89 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 551 Yenice_G30db G30-b2 535507 4525076 valley 1073 9 174 0,72 slope 552 Guney G30-b2 539740 4530413 slope 1283 11 177 0,81 top 553 Ikikavak G30-b2 535635 4530708 valley 1315 9 136 0,87 slope 554 Gokceyazi G30-b2 541632 4535026 valley 1177 16 215 0,74 slope 555 Mehmetler G30-b2 540150 4535400 valley 1205 9 93 0,85 slope 556 Kavakli_G30b2 G30-b2 539442 4526407 valley 1067 9 131 0,62 slope 557 Kayi G30-b2 537340 4532123 slope 1325 9 136 0,27 valley 558 Kirislar G30-b2 540668 4532240 slope 1066 9 196 0,04 flood 559 Otegece G30-b2 540687 4531916 flood 1061 8 31 0,20 slope 560 Terzi_G30b2 G30-b2 541338 4533307 slope 1114 10 130 0,39 valley 561 Bahadun G30-b2 541571 4531223 flood 1052 4 200 0,14 slope 562 Kizilibrik_G30b G30-b2 537003 4527081 slope 1205 8 187 0,48 top 563 Yesildumlupina G30-b2 533013 4529996 valley 1361 6 127 0,27 slope 564 Beloren G30-b3 541796 4523809 slope 930 11 345 0,06 flood 565 Corekciler G30-b3 538709 4522747 flood 925 5 328 0,16 valley 566 Agilozu G30-b3 533633 4523708 valley 1051 4 184 0,99 slope 567 Eskiahir G30-b3 535500 4521000 valley 993 3 64 0,56 slope 568 Golluce G30-b3 534342 4518395 slope 1200 3 31 0,28 valley 569 Kizilca G30-b3 532512 4520943 slope 977 4 264 0,38 valley 570 Kursunlu G30-b4 522147 4521052 valley 1126 7 66 0,87 slope 571 Bereket G30-b4 525390 4522285 valley 1175 8 94 0,62 slope 572 Bespinar G30-b4 523368 4522897 slope 1203 4 208 0,53 valley 573 Cukurca G30-b4 526813 4518399 valley 1050 0 -1 0,49 slope 574 Manastir G30-b4 526116 4517279 valley 1085 5 108 0,63 slope 575 Hacimuslu_AsaG30-b4 525538 4524534 valley 1269 8 194 0,97 slope 576 Hacimuslu_Yu G30-b4 525046 4524853 valley 1298 6 100 0,42 slope 577 Hocahasan G30-b4 529087 4515152 slope 1216 6 293 0,25 valley 578 Igdir_G30b4 G30-b4 523983 4518757 valley 1082 4 22 0,79 slope 579 Kapakli_G30b4 G30-b4 523692 4512299 valley 1315 4 272 0,89 slope 580 Kopurlu_G30b4G30-b4 524238 4514491 valley 1066 8 120 0,80 slope 581 Sivricek G30-b4 531422 4523945 valley 1107 6 149 0,62 slope 582 Sumucak G30-b4 529150 4519691 valley 1000 2 139 0,65 slope 583 Yamukoren G30-b4 530270 4518067 slope 1158 6 286 0,31 top 584 Taskaracalar G30-c1 523135 4507356 valley 1450 0 52 0,50 slope 585 Bugay_G30c2 G30-c2 541329 4507159 valley 900 0 26 0,73 slope 586 Cukuroren G30-c2 533844 4501555 slope 1303 16 145 0,28 valley 587 Yolkaya G30-c2 538308 4503719 valley 1026 6 93 0,89 slope 588 Demircevre G30-c2 538997 4508026 valley 1050 0 90 0,80 slope 589 Kayiici G30-c2 539145 4505582 valley 1000 1 76 0,46 slope 590 Ortayaka G30-c2 535189 4500017 slope 1154 3 122 0,06 valley 591 Ciftlikkoy G30-c3 541911 4493523 slope 951 6 151 0,72 valley 592 Eldivan G30-c3 542307 4486890 slope 950 1 14 0,51 valley 593 Cukuroz G30-c3 537427 4495373 slope 1248 2 271 0,61 valley 594 Akcali G30-c3 539463 4496158 valley 1064 5 45 0,87 slope 595 Saraykoy G30-c3 540908 4486883 slope 999 4 75 0,18 valley 596 Seydikoy G30-c3 539708 4492243 slope 940 5 124 0,52 valley 597 Capar G30-c3 532613 4483603 slope 1124 8 275 0,79 flood 598 Caparkayi G30-c4 529615 4484363 valley 1152 4 119 0,51 slope 599 Gurpinar G30-c4 525729 4485264 slope 1148 7 203 0,30 valley 600 Kamis G30-c4 528894 4489131 slope 1306 4 345 0,60 top 601 Yalak Cukurore G30-d1 501628 4508976 flood 1298 2 19 0,30 slope

90 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 602 Orta G30-d1 509081 4497604 flood 1250 0 26 0,44 slope 603 Kalfat G30-d1 508470 4501961 valley 1264 3 76 0,54 slope 604 Kanlica G30-d1 507331 4497733 slope 1263 3 151 0,03 flood 605 Kisac_G30d1 G30-d1 502434 4499486 valley 1330 1 131 0,38 slope 606 Salur G30-d1 505194 4499567 slope 1329 5 287 0,12 valley 607 Demircioren G30-d2 518054 4509958 slope 1350 0 46 0,38 valley 608 Yayla G30-d2 516323 4508869 slope 1485 4 22 0,62 top 609 Dumanli G30-d2 520202 4504661 valley 1350 2 189 0,86 slope 610 Sunurlu G30-d2 516705 4507030 slope 1267 15 148 0,42 top 611 Doganlar G30-d2 516784 4502767 slope 1362 3 28 0,44 valley 612 Karaagac_G30 G30-d2 514401 4498133 valley 1301 2 167 0,56 slope 613 Kirsakal G30-d2 512699 4501052 flood 1250 0 -1 0,14 slope 614 Sakaeli G30-d2 514161 4503318 valley 1250 0 -1 0,81 flood 615 Sancar G30-d2 515327 4500267 valley 1301 4 278 0,79 slope 616 Bulduk G30-d3 517337 4487998 top 1371 9 159 0,91 slope 617 Cerci G30-d3 517966 4485527 valley 1220 13 137 0,43 slope 618 Akcaoren_G30 G30-d3 515489 4485874 valley 1222 8 144 0,39 slope 619 Elmali G30-d3 510978 4488567 valley 1372 7 69 0,35 slope 620 Karaoren_G30 G30-d3 520852 4484065 slope 1146 6 189 0,47 valley 621 Yenice_G30d3 G30-d3 519057 4489896 valley 1350 0 53 0,57 slope 622 Huyuk Koy_G3 G30-d3 515350 4493181 valley 1353 3 74 0,75 slope 623 Eskiyayla G30-d3 516777 4495080 valley 1400 2 229 0,68 slope 624 Sakarcaoren G30-d3 512619 4496652 slope 1300 1 111 0,31 valley 625 Yaylakent G30-d4 508193 4493500 slope 1268 1 341 0,12 valley 626 Inkilap G30-d4 503329 4490591 slope 1365 6 52 0,89 top 627 Yesilyurt_G30d G30-d4 500635 4484230 valley 1537 7 41 0,46 slope 628 Ozlu G30-d4 505249 4485633 valley 1433 7 101 0,73 slope 629 Bugduz G30-d4 504494 4495075 slope 1305 3 145 0,14 valley 630 Gokceoren G30-d4 504689 4489242 valley 1379 4 22 0,88 slope 631 Kucukbahceli H31-b2 583702 4472042 slope 582 2 111 0,26 valley 632 Kayilar G30-d4 507491 4487673 slope 1355 3 274 0,37 valley 633 Kucukkayi G30-d4 507215 4489237 valley 1334 3 266 0,33 slope 634 Yuva G30-d4 503111 4496647 valley 1301 3 151 0,61 slope 635 Akcaoren_G31 G31-a1 542894 4534783 slope 1289 10 188 0,38 valley 636 Alibey G31-a1 543499 4534453 slope 1290 6 134 0,30 top 637 Alibey_Asagi G31-a1 543950 4533950 slope 1209 8 82 0,59 valley 638 Karatas G31-a1 544340 4532516 top 1250 2 145 0,50 slope 639 Alpagut G31-a1 545606 4530091 slope 1154 4 154 0,81 top 640 Asagi Bozan_GG31-a1 549945 4535125 slope 1104 6 188 0,07 valley 641 Belsogut G31-a1 550649 4533194 slope 1034 4 141 0,81 top 642 Yaylaoren G31-a1 542463 4527709 flood 976 7 78 0,09 slope 643 Yenidemirciler G31-a1 543158 4527761 slope 981 8 250 0,16 flood 644 Basdibek G31-a1 548471 4526818 slope 939 8 208 0,28 flood 645 Danisment G31-a1 548102 4536197 slope 1264 10 152 0,05 valley 646 Imamlar_G31a G31-a1 548650 4536214 valley 1203 5 130 0,89 slope 647 Gaziler G31-a1 550837 4527575 slope 902 5 260 0,11 flood 648 Caltipinar G31-a1 549027 4531411 valley 959 9 213 0,55 slope 649 Kese G31-a1 552312 4533453 slope 1026 11 207 0,26 valley 650 Okcular G31-a1 544824 4535205 slope 1256 5 165 0,28 valley 651 Odemis G31-a1 546810 4533436 valley 1047 3 152 0,51 slope

91 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 652 Omerli G31-a1 544808 4527440 valley 948 2 136 0,82 slope 653 Sagirlar G31-a1 545916 4525674 slope 909 7 307 0,21 flood 654 Seki G31-a1 546741 4536075 slope 1308 8 156 0,42 valley 655 Serceler G31-a1 548690 4537307 slope 1297 8 178 0,06 valley 656 Kisla_G31a1 G31-a1 548755 4536548 valley 1221 15 208 0,28 slope 657 SuleymanhacilaG31-a1 542524 4529998 flood 1007 6 212 0,41 slope 658 Yukari Bozan_GG31-a1 549403 4535739 valley 1151 3 206 0,37 slope 659 Hasanhaci G30-d4 504211 4493477 top 1309 4 82 0,22 slope 660 Ilgaz G31-a2 552938 4530688 slope 905 3 143 0,47 valley 661 Arpayeri G31-a2 562219 4534762 valley 1276 14 97 0,93 slope 662 Asagi Dere G31-a2 553050 4533950 valley 1016 8 199 1,00 slope 663 Menser G31-a2 553370 4533903 slope 1046 5 209 0,47 valley 664 Kisla_Asagider G31-a2 553050 4536500 valley 1202 9 184 0,88 slope 665 Asagi Meydan G31-a2 554826 4535425 slope 1203 9 113 0,32 valley 666 Beykoy_G31a2 G31-a2 561700 4538050 slope 1152 14 168 0,20 valley 667 Kisla_Beykoy G31-a2 562472 4538183 slope 1183 13 166 0,07 valley 668 Ecizoglu G31-a2 562232 4538036 valley 1154 6 233 0,16 slope 669 Kuzgece G31-a2 562207 4537802 valley 1179 16 331 0,23 slope 670 Bukcuk G31-a2 555742 4531589 slope 909 5 214 0,68 flood 671 Candere G31-a2 554859 4530645 slope 900 1 171 0,09 flood 672 Yuvasaray G31-a2 562619 4525264 valley 902 6 320 0,81 slope 673 Hacihasan G31-a2 556915 4530125 slope 926 14 284 0,08 flood 674 Inkoy G31-a2 554995 4528323 flood 845 4 38 0,04 slope 675 Kalekoy G31-a2 554974 4534179 slope 1002 5 158 0,04 valley 676 Kazancı G31-a2 559212 4538988 valley 1109 9 269 0,30 slope 677 Kurmalar G31-a2 560941 4537938 valley 1158 13 176 0,59 slope 678 Musakoy G31-a2 557256 4535355 slope 1029 9 133 0,29 top 679 Onac G31-a2 557783 4536416 valley 1094 10 145 0,45 slope 680 Sarmasık G31-a2 559298 4525684 flood 821 2 113 0,10 slope 681 Satilar G31-a2 560373 4537378 valley 1100 6 104 0,62 slope 682 Sazak_G31a2 G31-a2 560267 4533425 valley 1131 16 224 0,69 slope 683 Sihlar G31-a2 555842 4536226 slope 1177 11 165 0,02 valley 684 Yalaycik G31-a2 559311 4537866 valley 1083 6 258 0,84 slope 685 Yazikoy G31-a2 553342 4532362 slope 934 3 175 0,59 valley 686 Yerkuyu G31-a2 560810 4528346 slope 1042 11 136 0,19 valley 687 Yukaridere G31-a2 553150 4534250 valley 1048 7 214 0,84 slope 688 Yukari Meydan G31-a2 554737 4535869 slope 1241 9 122 0,41 valley 689 Yuvademirciler_G31-a2 561200 4538750 slope 1296 15 214 0,74 valley 690 Derecati G31-a3 556842 4511945 valley 1096 2 206 0,27 slope 691 Yukari Bozan_KG31-a1 549203 4536093 valley 1179 9 214 0,49 slope 692 Ilisilik G31-a3 558616 4521024 slope 1200 3 266 0,05 valley 693 Kuscayiri G31-a3 554377 4523577 slope 1334 6 11 0,39 valley 694 Sezgin G31-a3 556156 4520645 valley 1350 1 44 0,91 slope 695 Ahlat G31-a4 551667 4512399 slope 1302 5 179 0,24 valley 696 Dikenli_G31a4 G31-a4 544655 4515695 slope 1207 6 173 0,55 valley 697 Kesecik G31-a4 546250 4517367 slope 1146 6 142 0,04 valley 698 Karatepe G31-a4 546775 4515134 valley 1157 9 254 0,62 slope 699 Aktas G31-a4 548308 4523004 slope 1300 2 108 0,14 flood 700 Ericek G31-a4 546828 4520098 valley 1336 7 165 0,75 slope 701 Kiyisin G31-a4 551080 4520096 valley 1275 8 113 0,33 slope

92 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 702 Kuyupinar G31-a4 550732 4523316 slope 1400 0 -1 0,19 flood 703 Mesutören G31-a4 548490 4519766 slope 1218 9 206 0,27 valley 704 Seyhyunus G31-a4 544315 4521297 slope 1401 2 133 0,50 top 705 Boyacioglu H32-a1 587305 4478011 slope 576 2 136 0,11 flood 706 Saraycik_G30b G31-b1 564416 4539032 slope 1298 5 186 0,14 valley 707 Asagi Oz G31-b3 574970 4518979 slope 1209 8 186 0,63 valley 708 Ayseki G31-b3 575900 4515350 slope 1245 12 143 0,21 valley 709 Pirkayip G31-b3 577127 4516889 valley 1089 11 87 0,33 slope 710 Bademcay G31-b3 582690 4513598 slope 1214 8 240 0,05 valley 711 Cakirlar G31-b3 583158 4514448 valley 1193 4 300 0,99 slope 712 Davutlar G31-b3 582442 4515714 slope 1377 10 172 0,52 valley 713 Saraycik_G31b G31-b3 583154 4516295 slope 1423 12 178 0,86 valley 714 Kivcak G31-b3 574390 4513615 slope 1076 7 172 0,45 flood 715 Sarikaya_G31b G31-b3 580305 4518279 slope 1188 14 163 0,09 valley 716 Gokceyuz G31-b3 579578 4516948 valley 1120 7 163 0,22 slope 717 Yaka Koy G31-b3 579892 4515687 slope 1193 5 203 0,69 top 718 Asagikaya G31-b3 578844 4514609 valley 1080 5 257 0,26 slope 719 Yukariyaka G31-b3 580391 4515770 slope 1236 8 263 0,94 valley 720 Yesilyurt_G31b G31-b3 577428 4514120 flood 1031 2 269 0,27 slope 721 Yaprakli G31-b4 565769 4512238 slope 1195 3 76 0,39 valley 722 Akyazi G31-b4 569892 4511439 valley 1029 5 135 0,16 slope 723 Igdir_G31b4 G31-b4 568790 4514013 valley 1200 3 91 0,81 slope 724 Kavak Koyu G31-b4 570077 4515572 slope 1370 7 156 0,53 top 725 Yukarioz G31-b4 570694 4518333 slope 1258 7 171 0,08 valley 726 Hasakca G31-c1 564928 4501842 valley 856 6 184 0,36 slope 727 Bugay_G31c1 G31-c1 564177 4508154 valley 1045 5 133 0,25 slope 728 Buluca G31-c1 568085 4509374 slope 1050 3 99 0,40 valley 729 Doganbey G31-c1 571670 4507165 slope 975 5 63 0,52 valley 730 Karacaozu G31-c1 565343 4509106 valley 1050 1 80 0,91 slope 731 Cevrecik G31-c1 572187 4501167 top 1074 7 270 0,22 slope 732 Sazcigaz G31-c1 567961 4506220 flood 921 4 147 0,06 valley 733 Yenice_G31c1 G31-c1 571679 4504602 slope 935 8 307 0,12 flood 734 Yuklu_Bati G31-c1 567179 4503781 flood 865 1 206 0,43 slope 735 Yuklu_Dogu G31-c1 567872 4504052 slope 894 5 225 0,20 flood 736 Ayvakoy G31-c2 583181 4509369 valley 1166 6 112 0,40 slope 737 Yukariayva G31-c2 582532 4510621 slope 1250 2 51 0,48 valley 738 Cercicami G31-c2 584293 4511191 slope 1259 7 323 0,41 valley 739 Ikizoren G31-c2 574594 4504691 slope 1197 2 173 0,10 valley 740 Goynukeren Y. G30-a2 514109 4538303 valley 1651 5 336 1,00 slope 741 Yamacbasi G31-c2 580012 4507085 top 1404 2 306 0,41 slope 742 Yabani G31-c2 581492 4506512 slope 1261 9 24 0,70 top 743 Sogutlu G31-c2 583489 4505292 slope 1123 8 222 0,12 valley 744 Buyuk Akseki G31-c2 580071 4500323 top 1341 4 133 0,60 slope 745 Kayacik G31-c2 581182 4503609 top 1362 3 207 0,54 slope 746 Saricay G31-c2 579837 4502755 valley 1287 5 181 0,35 slope 747 Kaymaz G31-c2 576707 4508681 slope 1144 6 137 0,79 top 748 Kirliakca G31-c2 577675 4498291 slope 949 5 206 0,56 valley 749 Subasi G31-c2 578156 4505688 slope 1325 7 156 0,77 top 750 Kullar_Guney G31-c2 579257 4510197 slope 1100 1 169 0,47 valley 751 Sofuoglu_G31c G31-c2 580455 4504653 valley 1349 3 165 0,34 slope 752 Tatlipinar G31-c2 573994 4508334 slope 963 12 296 0,02 flood

93 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 752 Tatlipinar G31-c2 573994 4508334 slope 963 12 296 0,02 flood 753 Topuzsaray G31-c2 575552 4499318 slope 1119 10 186 0,65 top 754 Zekeriyakoy G31-c2 576998 4502188 valley 1205 5 285 0,88 slope 755 Kuzukoy G31-c3 580497 4485855 valley 650 3 147 0,97 slope 756 Altinli G31-c3 581708 4488470 slope 800 2 128 0,44 top 757 Alacat G31-c3 578279 4491522 slope 880 1 78 0,81 top 758 Haydar G31-c3 579962 4491118 slope 875 6 38 0,05 valley 759 Balibagi G31-c4 566045 4490459 slope 1031 8 218 0,64 top 760 Bayindir_G31c G31-c4 568940 4497042 slope 1083 7 191 0,51 valley 761 Cayirpinar G31-c4 567328 4493177 valley 1100 0 67 1,00 slope 762 Civikoy G31-c4 564563 4493873 slope 1008 3 333 0,19 valley 763 Kucuklu G31-c4 568826 4493461 valley 1124 7 158 0,08 slope 764 Ovacik_G31c4 G31-c4 572137 4489100 valley 920 4 160 0,48 slope 765 Kaput G31-c4 573129 4492787 valley 950 0 -1 0,48 flood 766 Akcavakif G31-d1 548440 4504939 valley 824 5 205 0,28 slope 767 Tepekoy_G31d G31-d1 548758 4503265 flood 790 2 148 0,10 slope 768 Gumusduven G31-d1 544916 4504023 valley 894 7 299 0,14 slope 769 Asagi Cavus G31-d1 552070 4504409 flood 839 2 211 0,07 slope 770 Ayan G31-d1 550493 4502656 flood 813 5 288 0,09 slope 771 Ikicam G31-d1 547309 4509671 valley 1140 9 180 0,10 slope 772 Karatekin G31-d1 543250 4501971 flood 900 0 -1 0,04 slope 773 Korgun G31-d1 543475 4509743 flood 919 5 107 0,15 slope 774 Alanpinar G31-d1 551348 4508749 slope 976 10 131 0,09 valley 775 Icyenice G31-d1 549700 4500700 flood 788 3 31 0,27 slope 776 Kembaglari G31-d1 551375 4499677 flood 760 0 217 0,05 slope 777 Basegmez G31-d2 554412 4510701 slope 1102 6 184 0,10 valley 778 Ballibidik G31-d2 561871 4505042 valley 954 5 157 0,64 slope 779 Degim G31-d2 559547 4506219 valley 1011 7 229 0,67 slope 780 Dutagac G31-d2 557399 4505618 valley 1054 7 146 0,55 flood 781 Inac G31-d2 558804 4498205 slope 799 7 344 0,26 flood 782 Pasakoy_G31d G31-d2 556438 4508616 flood 985 8 264 0,07 slope 783 Yakadere G31-d2 560463 4508317 flood 1100 0 12 0,33 slope 784 Yukaricavus G31-d2 553326 4504896 flood 871 4 158 0,04 slope 785 Esentepe G31-d3 555379 4492795 slope 897 3 217 0,42 top 786 Dedekoy_G31d G31-d3 561814 4494056 valley 931 8 254 0,27 slope 787 Dogantepe G31-d3 554010 4491112 valley 850 2 317 0,37 slope 788 Süleymanlı_G3 G31-d3 553158 4486472 slope 819 6 268 0,33 top 789 Tuzlu G31-d3 557107 4497371 valley 755 5 249 0,63 slope 790 Cankiri G31-d4 551145 4495623 flood 739 4 58 0,10 slope 791 Oglakli G31-d4 546847 4487140 slope 1025 10 96 0,38 valley 792 Asagi Yanlar G31-d4 547939 4489945 slope 772 7 60 0,11 flood 793 Golezkayi G31-d4 545950 4485200 slope 1007 5 142 0,50 valley 794 Hidirlik G31-d4 548830 4494307 valley 1005 7 104 0,88 slope 795 Saritarla G31-d4 543250 4495064 slope 1011 7 106 0,53 valley 796 Süleymanli G31-d4 552421 4485521 flood 700 0 -1 0,15 slope 797 Saritepe G31-d4 544808 4491849 valley 814 6 154 0,31 slope 798 Cicek G32-a4 584900 4513050 slope 1300 1 57 0,31 valley 799 Mansurlu G32-a4 585940 4513406 slope 1317 6 165 0,17 valley 800 Musellim G32-a4 585714 4512195 slope 1304 4 213 0,22 valley 801 Kilicli G32-a4 585350 4512500 top 1300 0 -1 0,12 slope

94 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 802 Kayapa G32-a4 584651 4512167 slope 1300 1 129 0,83 top 803 Huseyinfaki G32-a4 585255 4511743 valley 1300 1 294 0,47 slope 804 Kerimler G32-a4 585911 4512037 slope 1309 7 206 0,24 valley 805 Yesilyayla G32-a4 587008 4515050 slope 1447 17 143 0,33 valley 806 Belibedir Kislac G32-d1 585445 4511248 slope 1390 11 292 0,87 top 807 Belibedir Cerikl G32-d1 584700 4510950 top 1302 4 156 0,40 slope 808 Kiyi G32-d1 589809 4499263 valley 819 15 74 0,40 slope 809 Hacihasanoglu G32-d1 590100 4499200 valley 814 9 203 0,19 slope 810 Kulla G32-d1 590336 4499020 valley 818 12 247 0,89 slope 811 Imamusagi G32-d1 590074 4498367 valley 800 3 48 0,28 slope 812 Igdecik G32-d1 590570 4498344 valley 805 7 255 0,38 slope 813 Coca G32-d1 590402 4497846 valley 792 7 213 0,75 slope 814 Hacilar_H31b3 H31-b3 574434 4466241 flood 559 0 55 0,34 slope 815 Gurmec G32-d1 585408 4501497 slope 1059 16 225 0,47 valley 816 Asagikayaharm G32-d1 587820 4501813 top 1156 6 240 0,41 slope 817 Ozlu Y._Guney H30-a1 505888 4480014 slope 1752 6 177 0,18 valley 818 Agzibuyuk G32-d4 586283 4488742 slope 774 5 104 0,63 valley 819 Mollamehmet G32-d4 585565 4488447 top 810 8 161 0,44 slope 820 Kazbekir G32-d4 588259 4489283 top 708 3 197 0,30 slope 821 Haciomer G32-d4 587542 4489943 slope 750 1 100 0,01 valley 822 Danabasi G32-d4 588480 4486346 top 751 1 186 0,19 slope 823 Yeniyapan_G32G32-d4 587171 4485451 slope 783 10 143 0,49 valley 824 Bascoban G32-d4 590822 4487707 slope 661 7 22 0,17 valley 825 Kizara Y. H30-a2 510750 4537578 slope 1576 8 283 0,61 top 826 Karadayi H31-b4 567033 4467242 slope 566 1 169 0,15 flood 827 Kizilirmak H31-b3 583590 4466986 flood 556 1 323 0,42 slope 828 Besdut_Guney G32-d4 590172 4496480 flood 753 6 177 0,07 slope 829 Besdut_Kuzey G32-d4 590400 4497464 valley 769 9 239 0,37 slope 830 Cagabey G32-d4 587759 4494083 slope 999 5 146 0,92 top 831 Unur Koyu_KuzG32-d4 584967 4493630 slope 1007 4 155 0,02 top 832 Unur Koyu_Gu G32-d4 584944 4492537 slope 976 4 113 0,40 valley 833 Tepealagoz H31-b3 582310 4469719 top 580 0 81 0,51 slope 834 Buyuk Yakali H30-a2 517806 4481699 slope 1217 5 80 0,27 top 835 Kosrelik H30-a2 512339 4477424 valley 1200 1 79 0,72 slope 836 Kutlusar H30-a2 519612 4472599 valley 951 3 113 0,95 slope 837 Kurtsivrisi H30-a2 518562 4469652 slope 1044 4 68 0,65 top 838 Kucuk Yakali H30-a2 517597 4480430 valley 1175 8 176 0,16 slope 839 Yesiloz_H30a2 H30-a2 517900 4477000 valley 1104 6 106 0,41 slope 840 Sarisu H30-a2 515750 4472700 valley 1020 10 216 0,61 slope 841 Tepekoy_H30a H30-a2 516750 4473150 slope 1195 6 217 0,24 valley 842 Mese Y.-H30a3 H30-a3 513455 4467797 slope 1241 8 55 0,33 valley 843 Dalyasan H30-a3 513200 4469300 valley 1205 6 178 0,49 slope 844 Demirci_H30a2 H30-a3 518590 4464914 valley 961 6 76 0,81 slope 845 Meseli H30-a3 517634 4468013 valley 950 3 39 0,93 slope 846 Oyumigde H30-a3 519259 4463796 valley 904 5 174 0,96 slope 847 Ozbek H30-a3 520450 4468750 flood 901 2 152 0,21 slope 848 Sabanozu H30-b1 524011 4481555 flood 1050 0 37 0,21 slope 849 Bulgurcu H30-b1 522095 4474068 slope 968 11 101 0,04 valley 850 Goldagi H30-b1 522079 4472556 slope 1047 14 273 0,40 top 851 Gumerdigin H30-b1 521677 4477158 slope 1076 9 118 0,46 top

95 Coordinates Topographic Properties Nearest Settlement Topo Landform Distance Id No Easting Northing Landform Name Sheet Class Elevation Slope Aspect Ratio (X) (Y) Class 851 Gumerdigin H30-b1 521677 4477158 slope 1076 9 118 0,46 top 852 Demirhasan H30-b1 526298 4474658 slope 922 6 79 0,03 valley 853 Gundogmus H30-b1 524866 4470647 valley 1000 4 142 0,79 slope 854 Karakocas H30-b1 531022 4477772 slope 986 5 239 0,12 valley 855 Odek H30-b1 525105 4472370 slope 1028 4 126 0,57 top 856 Hisarcik H30-b2 538733 4472524 slope 1148 6 139 0,16 valley 857 Hisarcikkayi H30-b2 540801 4474172 slope 1063 8 135 0,12 valley 858 Bakirli H30-b2 532062 4479847 slope 1050 4 264 0,63 valley 859 Martkoy_Kuzey H30-b2 533675 4475539 slope 1025 9 166 0,25 valley 860 Martkoy_GuneyH30-b2 533871 4475112 valley 1012 6 315 0,49 slope 861 Karamusa H30-b4 521647 4466041 valley 860 7 227 0,69 slope 862 Karahaci H30-b4 524071 4467532 slope 899 1 130 0,59 valley 863 Akoren H31-a1 550296 4474927 valley 805 6 182 0,47 slope 864 Buyuk Hacibey H31-a1 543341 4475920 valley 1030 9 190 0,20 slope 865 Elmaci H31-a1 546835 4480650 valley 1001 3 58 0,81 slope 866 Golez H31-a1 546583 4483116 slope 978 8 17 0,44 valley 867 Alica H31-b4 571099 4467234 flood 557 2 128 0,03 slope 868 Terme H31-a1 550867 4470796 flood 666 7 271 0,15 slope 869 Kucuk Hacibey H31-a1 544111 4478025 top 1106 7 105 0,19 slope 870 Yukari Pelitozu H31-a1 551985 4480496 valley 797 5 171 0,63 slope 871 Akbulut H31-a1 544365 4481764 valley 1268 12 81 0,80 slope 872 Asagi Pelitozu H31-a2 555318 4479450 valley 756 4 68 0,61 slope 873 Germece H31-a2 557444 4473427 valley 650 0 70 0,68 slope 874 Konak H31-a2 554208 4471409 flood 651 7 299 0,28 slope 875 Bozkir H31-b1 572188 4477551 slope 622 1 48 0,46 valley 876 Dedekoy_H31b H31-b1 566116 4478528 flood 601 2 144 0,04 valley 877 Ciftlik H31-b1 564944 4479319 flood 617 5 132 0,06 slope 878 Asagi Ovacik H31-b2 574226 4478497 flood 580 2 218 0,07 slope 879 Yukari Alagoz H31-b2 577032 4471457 valley 606 2 83 0,91 slope 880 Yeniyapan_H3 H31-b2 578905 4477612 top 699 0 75 0,11 slope 881 Yuvalar F29-c4 485381 4539486 slope 1078 13 340 0,49 valley 882 Acioz F29-d3 469172 4542114 valley 540 4 57 1,00 flood 883 Yukari Caykoy F29-d3 468609 4541244 flood 550 0 -1 0,28 slope 884 Buyuktarla F29-d3 469704 4542593 flood 518 6 284 0,21 slope 885 Yurtpinar G30-a2 513122 4532922 slope 811 8 148 0,48 flood 886 Kullar_Kuzey G31-c2 579603 4510466 valley 1129 6 290 0,37 slope 887 Icmederesi G32-d1 591052 4498846 valley 800 8 144 0,76 slope 888 Yaylakent Y. H30-a1 500080 4482983 slope 1521 6 117 0,43 valley 889 Kayi Y. H30-a1 509759 4481769 valley 1760 10 251 0,62 slope 890 Osmanbey H32-a1 586346 4478060 slope 564 6 203 0,06 flood 891 Adiller Y. G28-b1 445793 4527602 slope 1552 10 14 0,71 top