498

 DOKUZ EYLÜL UNIVERSITY
GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
MONITORING AND EXPLORING NATURAL
HAZARD RISK IN TEOS ANCIENT CITY USING


ACKNOWLEDGMENT
I would like to express my special thanks of gratitude to my thesis advisor Asst.
Prof. A. Hüsnü Eronat for not only being my thesis advisor and guiding me every
step of the way, but also for showing me the power of education and demonstrating
how kind and loving teachers can be.
I also would like to thank Assoc. Prof. Fethi Bengil and Sue Eronat for their
unconditional support. I would like to thank my parents and brother for everything. I
am grateful to the Department of Scientific Research Projects at Dokuz Eylül
University for including my thesis in the scope of Scientific Research and for all
their support (Scientific Research Project Number: 2021.KB.FEN033). I would also
like to thank General Directorate of Mapping for providing me orthophoto images
that include the study area and also would like to thank İTÜ UHUZAM for high
resolution satellite images. Lastly, I want to thank Prof. Dr. Musa Kadıoğlu from
Ankara University for his support and convenience for me to be able to work in Teos
Ancient City.

iv
MONITORING AND EXPLORING NATURAL HAZARD RISK IN TEOS
ANCIENT CITY USING REMOTE SENSING AND GIS
ABSTRACT
Both natural and human-induced risks have posed a threat to residential areas and
important artifacts from past to present. Since cultural heritages are structures
coming from the past, they are more vulnerable to several threats. This research work
was conducted to define natural and anthropogenic hazard risk factors which
possibly can affect the integrity and the permanence of Teos Ancient City and to find
solutions for these risk factors. High resolution satellite images taken in different
years were utilized in order to effectively carry out the research work based on
revealing the changes in urban sprawl and transportation route lengths from past to
present in Teos. Soil erosion risk and coastal flood risk analyzes were conducted
with the created Digital Elevation Model. Unmanned Aerial Vehicle (UAV) flights
were carried out to observe the most up-to-date status of the ruins in Teos. Analytic
Hierarchy Process (AHP) method was used to identify the risk factors of highest
importance. After the realization of the AHP analysis, The most important among the
risk factors for Teos were determined as urban sprawl, proximity to transportation
routes and earthquake. In conclusion, some important risks in Teos were determined,
thus it was observed that regulations and control mechanisms have to be reviewed
more frequently.
Keywords: Cultural heritage, natural hazards, GIS, remote sensing, natural and
anthropogenic risks, Analytic Hierarchy Process
v
TEOS ANTİK KENTİ’NDE DOĞAL TEHLİKE RİSKİNİN UZAKTAN
ALGILAMA VE CBS KULLANILARAK İZLENMESİ VE ARAŞTIRILMASI
ÖZ
Gerek doğal gerekse insan kaynaklı riskler geçmişten günümüze kadar yerleşim
alanları ve önemli eserler için tehdit oluşturmuştur. Kültürel miraslar geçmişten
kalan yapılar oldukları için çeşitli tehditlere karşı daha savunmasızdırlar. Bu
araştırma, Teos Antik Kenti'nin bütünlüğünü ve kalıcılığını etkileyebilecek doğal ve
insan kaynaklı tehlike içeren risk faktörlerini tanımlamak ve bu risk faktörlerine
çözüm bulmak amacıyla yapılmıştır. Teos'ta geçmişten günümüze kentsel yayılma ve
ulaşım yollarının uzunluklarındaki değişimin ortaya konulmasına dayalı araştırma
çalışmasının etkin bir şekilde yürütülebilmesi için farklı yıllarda çekilmiş yüksek
çözünürlüklü uydu görüntülerinden yararlanılmıştır. Oluşturulan Sayısal Yükseklik
Modeli ile toprak erozyonu riski ve kıyı taşkın risk analizleri yapılmıştır. Teos'taki
kalıntıların en güncel durumunu gözlemlemek için İnsansız Hava Aracı (İHA)
uçuşları gerçekleştirilmiştir. Analitik Hiyerarşi Prosesi (AHP) yöntemi, en yüksek
öneme sahip risk faktörlerini belirlemek için kullanılmıştır. AHP analizi sonucunda
Teos için en önemli üç risk faktörü kentsel yayılma, ulaşım yollarına yakınlık ve
deprem olarak belirlenmiştir. Sonuç olarak Teos'ta bazı önemli riskler tespit edilmiş,
bu nedenle düzenlemelerin ve kontrol mekanizmalarının daha sık kurulması gerektiği
görülmüştür.
Anahtar kelimeler: Kültürel miras, doğal tehlikeler, CBS, uzaktan algılama, doğa
ve insan kaynaklı riskler, Analitik Hiyerarşi Proses
vi
CONTENTS
Page
M.Sc THESIS EXAMINATION RESULT FORM .....................................................ii
ACKNOWLEDGMENT .............................................................................................iii
ABSTRACT ................................................................................................................ iv
ÖZ .................................................................................................................................v
LIST OF FIGURES .....................................................................................................ix
LIST OF TABLES ..................................................................................................... xii
CHAPTER 1 – INTRODUCTION .........................................................................1
1.1 Study Area ......................................................................................................... 3
1.1.1 Location of Teos ......................................................................................3
1.1.2 Archaeological Research Background in Teos ........................................5
1.1.3 History of the City ................................................................................... 6
1.1.4 Urban Development and the Buildings ................................................... 7
CHAPTER 2 – RESEARCH REVIEW .................................................................9
2.1 Risk Factors ................................................................................................ 9
2.1.1 Urban Sprawl Analysis ....................................................................... 10
2.1.2 Defining Proximity to Transportation .................................................13
2.1.3 Soil Erosion Risk Analysis ................................................................. 14
2.1.4 Watershed Risk Assessment ............................................................... 14
2.1.5 Coastal Flood Risk Analysis ...............................................................16
2.1.6 Earthquake Risk Assessment .............................................................. 18
vii
2.1.7 Structural Damage Assessment ...........................................................21
2.1.8 UAV Imaging ......................................................................................22
2.1.9 Monitoring Displacements with PSI Technique .................................22
2.2 Analytic Hierarchy Process (AHP) ...........................................................23
CHAPTER 3 – MATERIALS AND METHOD ............................................... 24
3.1 Exploratory Factor Analysis .....................................................................26
3.1.1 Urban Sprawl Analysis ....................................................................... 28
3.1.2 Defining Proximity to Transportation Routes .....................................31
3.1.3 Soil Erosion Risk Analysis ................................................................. 33
3.1.4 Watershed Risk Assessment ............................................................... 34
3.1.5 Coastal Flood Risk Analysis ...............................................................41
3.1.6 Earthquake Risk Assessment .............................................................. 43
3.1.7 Structural Damage Assessment ...........................................................44
3.1.8 UAV Imaging ......................................................................................46
3.2 Analytic Hierarchy Process (AHP) ...........................................................46
CHAPTER 4 – RESULTS.................................................................................. 50
CHAPTER 5 – DISCUSSION ............................................................................ 59
CHAPTER 6 – CONCLUSION ..........................................................................62
REFERENCES .................................................................................................... 64
ix
LIST OF FIGURES
Page
Figure 1.1 Location of Teos Ancient City..............................................................5
Figure 1.2 Detailed borders of Teos Ancient City..................................................6
Figure 1.3 Colonies of Teos in the 6th Century BC................................................8
Figure 2.1 Natural hazard events...........................................................................11
Figure 2.2 Risk evaluation studies in Teos Ancient City......................................12
Figure 2.3 Total Population Change in Seferihisar Between 1965-
2020......................................................................................................14
Figure 2.4 Total Population Change in Seferihisar Between 2007-
2020......................................................................................................14
Figure 2.5 Climate graph of Seferihisar................................................................17
Figure 2.6 Before the beginning of tsunami.........................................................19
Figure 2.7 14 seconds after the beginning of tsunami...........................................20
Figure 2.8 34 seconds after the beginning of tsunami...........................................20
Figure 2.9 Spread seismicity along Turkey territory in PGA in 475 years ...........21
Figure 2.10 a) TOPEX topography map
b) TOPEX satellite free air gravity anomaly map.............................21
Figure2.11 Earthquake risk map and rectangle covering
Teos.....................................................................................................23
Figure 2.12 Working principle of InSAR..............................................................24
x
Figure 3.1 Flow chart of supervised classification analysis...................................34
Figure 3.2 SPOT-6 image taken in 2013 of Teos Ancient City and
Seferihisar.......................................................................................34
Figure 3.3 SPOT-6 image taken in 2020 of Teos Ancient City and
Seferihisar.......................................................................................35
Figure 3.4 Maximum likelihood classification for SPOT-6 image taken in
2013..................................................................................................36
Figure 3.5 Maximum likelihood classification for SPOT-6 image taken in
2020.................................. ...............................................................36
Figure 3.6 Road network in Sığacık town and in the center of Seferihisar in
1957..................................................................................................37
Figure 3.7 Road network in Sığacık town and in the center of Seferihisar in
1986...................................................................................................37
Figure 3.8 Road network in Sığacık town and in the center of Seferihisar in
2020.................................................................................................38
Figure 3.9 Slope map of Teos Ancient City.........................................................39
Figure 3.10 Flow chart for delineating a watershed..............................................40
Figure 3.11 Flow chart for delineating a watershed..............................................41
Figure 3.12 Small imperfections in the data were removed using Fill tool.........41
Figure 3.13 Flow direction analysis of the study area..........................................42
Figure 3.14 Delineated watersheds in the study area............................................42
Figure 3.15 Basin polygons in the study area.......................................................43
Figure 3.16 Clipped basin.....................................................................................43
Figure 3.17 Flow accumulation analysis..............................................................44
Figure 3.18 Stream network in Teos Ancient City...............................................45
Figure 3.19 Chosen pour points in the study area.................................................45
Figure 3.20 Delineated watersheds in the study area............................................46
Figure 3.21 Coastal flood risk in case of a 1m. of sea level rise...........................47
Figure 3.22 Coastal flood risk in case of a 3.8m. of sea level rise........................47
Figure 3.23 Coastal flood risk in case of a 5m. of sea level rise...........................48
Figure 3.24 Displacement map after applying InSAR..........................................49
xi
Figure 3.25 Terrestrial LiDAR output image in the study area.............................50
Figure 3.26 Terrestrial LiDAR output image in the study area without
vegetation......................................................................................50
Figure 3.27 UAV image of Teos made with UAV flight outputs in
2021.............................................................................................. 51
Figure 3.28 UAV image from 2021 that shows Acropolis....................................52
Figure 3.29 UAV image from 2021 that shows Theatre.......................................52
Figure 3.30 UAV image taken in 2021 that shows Dionysus Temple..................53
Figure 3.31 UAV image taken in 2021 that shows Bouleuterion.........................53
Figure 3.32 UAV image taken in 2021 that shows Southern Port........................54
Figure 4.1 Displacement map made with PSI technique......................................60
Figure 4.2 Displacement map made with PSI technique......................................60
Figure 4.3 Consolidated results after AHP analysis.............................................62
Figure 5.1 Comparison of gains and losses for each class after supervised
classification analysis......................................................................63
xii
LIST OF TABLES
Page
Table 3.1 Satellite images used for risk evaluation studies......................................30
Table 3.2 Software used for risk evaluation studies.................................................31
Table 3.3 Representation of natural and human-induced measurable risk factors...32
Table 4.1 Areas (in km²) for each class after maximum likelihood classification for
SPOT - 6 image taken in 2013..................................................................55
Table 4.2 Areas (in km²) for each class after maximum likelihood classification for
SPOT - 6 image taken in 2020..................................................................56
Table 4.3 Total road length (km) by year.................................................................56
Table 4.4 Slope value range of each ruin.................................................................57
Table 4.5 Soil erosion risk classes. Adapted from...................................................57
Table 4.6 The state of being in the direction of the watershed flow........................58
Table 4.7 Possible impact areas for the selected sea level rises..............................58
Table 4.8 Maximum positive and maximum negative values on the displacement
map.........................................................................................................59
Table 4.9 AHP priorities for the risk factors............................................................61
Table 4.10 Weights obtained as a result of comparisons.........................................62
Table 5.1 Increment of total road length over years...............................................64
xiii
ABBREVIATIONS
GIS : Geographical Information Systems
UAV : Unmanned Aerial Vehicle
AHP : Analytic Hierarchy Process
BC : before Christ
n.d. : no date
TÜİK : Türkiye İstatistik Kurumu
Mw : Moment magnitude
km : kilometer
InSAR : Interferometric Synthetic Aperture Radar
SAR : Synthetic Aperture Radar
LiDAR : Light Imaging Detection and Ranging
TLS : Terrestrial Laser Scanning
UAV-RS : Unmanned Aerial Vehicles with Remote Sensing
DInSAR : Differential Synthetic Aperture Radar Interferometry
PSI : Persistent Scatterer Interferometry
AHP-OS : AHP online system
CORINE : Coordination of Information on the Environment
Fig. : Figure
DEM : Digital Elevation Model
km² : square kilometer
1
CHAPTER 1
INTRODUCTION
Cultural heritages are the immutable traces left by societies to future generations.
Each cultural heritage contains social, economic and cultural elements of the period
in which it takes place. Language, belief and folk traditions of societies are abstract
aspects and all these form a part of culture. Among the factors that make up cultures,
there are customs, religious understandings and behavior patterns specific to societies
that provide the intersection of traditions and religious understandings. Cultural
values that express the belonging of societies should be protected.
Cultural heritages, which are in danger of extinction due to the necessity of
preserving the historical values they contain and being built in the past, are faced
with human-based risk factors (Ilies et al., 2020, p. 1103), as well as nature-based
risks (Ilies et al., 2020, p. 1103).
Human and natural elements that threaten cultural assets can cause serious
damage and even permanent extinction (Ilies et al., 2020, p. 1103).
Cultural heritage are in danger of security due to the structure of nature and the
reasons this natural structure brings with it (Frodella et al., 2020 as cited in Ilies et al.,
2020, p. 1104). It is a serious need to protect the living cultural heritage that have
survived from the past to the present. Meeting this need is possible by detailed
analysis of risk factors and reducing the possible negative consequences of risks as a
result of these analyses (Vojtekova & Vojtek, 2020 as cited in Ilies et al., 2020, p.
1104).
With the development of technology, alternative solutions have emerged for the
risk analysis and protection of cultural heritage (Ilies et al., 2020, p. 1104). These
techniques are GIS and digitization approaches, which have the advantages of being
coherent, user-friendly and affordable. Current researches use GIS methods to
observe the details of cultural heritage in an organized and unified way (Ilies et al.,
2020, p. 1104).
2
Digitization aims to create geometric models that aim high accuracy in the long
term, examine future transformation and restructuring in the matter of any calamity
(Ilies et al., 2020, p. 1104).
The validity of this concept has been confirmed by many researches on the
evaluation and protection of cultural heritage (Ilies et al., 2020, p. 1104).
Up-to-date technologies with remote sensing since the time they were developed
have played an important role in the preservation of cultural assets (Agapiou et al.,
2015, p. 230).
Within the systems containing remote sensing, analyzes that help decision-making
are carried out effectively in order to examine the changes caused by environmental
effects, to detect possible harmful situations and to prevent such situations before
they occur (Agapiou et al., 2015, p. 230).
Since remote application methods are integrated with Geographic Information
Systems, cultural assets can be observed effectively, without delay and goal-oriented
(Agapiou et al., 2015, p. 230).
In large study areas where in-situ observations will take a lot of time, much faster
and relatively affordable results can be obtained when satellite images are used
(Agapiou et al., 2015, p. 230).
Cultural elements of a society and traditions from the past are represented by
cultural heritages (Nicu, 2017a as cited in Ilies et al., 2020, p. 1103). This bond that
enables cultural heritages to come from the past to the present (Indrie et al., 2019 as
cited in Ilies et al., 2020, p. 1103) has a great importance in terms of forming a sense
of belonging to societies and cultural authenticity (Ilies et al., 2020, p. 1103).
Capabilities to interact with memory (Vecco, 2010 as cited in Ilies et al., 2020, p.
1103) has the greatest share in the permanence of cultural heritage. Society chooses
to protect works of such great value (Ilies et al., 2020, p. 1103).
3
Conservation is more than just preserving the appearance of physical ruins. The
ambience, character, and the living pieces of history are preserved by conserving
cultural heritages. Cultural heritage should be protected not only because they are
historical buildings but also because they represent the unchanging identity of
societies. Additionally, architectural elements from the past contribute to the
development of beauty of streetscapes.
By keeping the cultural assets alive and transferring them to future generations,
all segments of the society will have preserved their identities and left a unique
legacy to the next generations.
Aim of this study is to define natural and anthropogenic hazard risk factors which
possibly can affect the integrity and the permanence of Teos Ancient City and to find
solutions for these risk factors. The fact that to present no study has been conducted
related to conserving Teos Ancient City against natural and anthropogenic risks and
natural hazards that have affected Sığacık town recently created an awareness and
become the motivation for this study.
There is a need for natural protection in this study area, where archaeological
studies are quite intense. Coastal areas, which are also part of the study area, are
ecologically important. Sustainable coastal management is required not only to
safeguard Teos Ancient City's Southern Port, but also to combine the social, cultural,
ecological, and economically productive components of the coastal environs.
1.1 Study Area
1.1.1 Location of Teos
Located on the coast of Ionia, Teos was a historical Greek city built on a
peninsula between Chytrium and Myonnesus. Although the date of its foundation is
not clear, it was founded by Minyans from Orchomenus, Ionians and Boeotians. The
Ionian League consisted of 12 cities, and Teos was one of them. Teos was located on
a low hill. The remaining parts of the ancient city are located in the southern part of a
4
coastal town called Sığacık, which is connected to the district of Seferihisar in İzmir.
(“Teos,” 2022) (Fig 1.1).
Town of Sığacık can be located at 38°11′N 26°47′E. Distance from Sığacık to the
center of Seferihisar can be observed as 5 kilometres (3.1 mi). It is located on a
peninsula oriented to the north (“Sığacık,” 2022).
Teos, located in the Sığacık district of Seferihisar in the southwest of İzmir,
consists of the Acropolis, the ancient harbor and the Hellenistic city walls in general
terms (Kadıoğlu, 2012, p. 2).
The borders of Teos Ancient City are marked with a red outline and its position
relative to Seferihisar and Sığacık appears in Figure 1.1
Figure 1.1 Location of Teos Ancient City (Red Outline) (Source: ©Google Maps, 2021)
After the excavation process realized between 2010 and 2015, detailed borders of
Teos Ancient City were discovered and they can be seen in Figure 1.2.
5
Figure 1.2 Detailed borders of Teos Ancient City (Polat, 2016)
1.1.2 Archaeological Research Background in Teos
Kadıoğlu (2018, pp. 3-4) explained that since the beginning of the 18th century,
Teos has attracted the attention of researchers in the West. The first excavations and
simultaneous researches in the city were carried out in 1764-1765. Turkish scientists
started their excavations and researches in Teos in the 1960s. Chronologically, Yusuf
Boysal and Baki Öğün from Ankara University directed the excavations in 1962-
1967; then, between 1980-1992, architect Duran Mustafa Uz directed a small number
of excavations. This was followed by the studies of Numan Tuna from Middle East
Technical University between 1993-1996. Finally, Prof. Dr. Musa Kadıoğlu from
Ankara University (Faculty of Letters, Department of Classical Archeology) has
been carrying out excavation, research and conservation works in Teos since 2010.
6
1.1.3 History of the City
According to Kadıoğlu (2018, p.5), researches have revealed that the Teos region
has been used as a settlement since the Protogeometric Period. Thales suggested that
Teos was supposed to be the center of Ionia because of its useful placement.
Increasing commercial relations in the beginning of 600 BC and so on reached as far
as Egypt but due to the conquest of Teos by the Persian commander Harpagos in 545
BC and the increasing Persian pressure, the people of Teos had to leave where they
had been settled and established Abdera (around Xanthi) in Thrace (Figure 1.3).
Some of those who had to leave Teos and went to Abdera returned to Teos later.
Also, approximately in 544 BC, the people living in Teos built the city of Phanagoria
in the location of the Taman Peninsula, but soon returned to their homeland of Ionia.
(Figure 1.3). Teos, which held a great wealth, gave serious support with seventeen
ships in the Battle of Lade.
Figure 1.3 Colonies of Teos in the 6th Century BC (Kadıoğlu, 2018)
Teos, which has its name written on the pages of history culturally, has hosted
names such as Antimachus and Anacreon who were well-known poets, the
7
philosophers Nausiphanes and Democritus, the historian Hecataios and the famous
book collector Apellicon (Kadıoğlu, 2018, pp. 5-6).
1.1.4 Urban Development and the Buildings
Kadıoğlu (2018, p.7) defined that observations revealed that the orthogonal street
structure was not located in Teos. The results that indicate the fact that the streets are
neither in perpendicular nor parallel form respectively have showed that the city was
not demolished severely during the Persian invasion. The property structure and
infrastructure in Teos from 1000 BC were maintained until the traces of the Roman
Empire were erased from history.
1.1.4.1 Acropolis
According to Kadıoğlu (2018, pp. 7-8), Teos Acropolis is on a hill called Kocakır
Hill, which can be observed from the location where both of the northern and
southern ports stand. The roots of the Acropolis, represented in the Roman Period, go
back to the Archaic Period, according to W. Hoepfner. Observation results dating
back to 630-590 BC show that the building hosted religious rituals.
1.1.4.2 Temple of Dionysus
Kadıoğlu (2018, pp. 9-10) explains that temple is seen as one of the most valuable
structures of the ancient city which is located within the Hellenistic walls. Some
blocks and friezes found in the temple are thought to date back to the Hellenistic
period.
1.1.4.3 Theatre
According to Kadıoğlu (2018, p.11), although Theatre, located on the southeast
slopes of the Acropolis, was built according to Greek traditions, no pre-Roman
findings have been observed until today.
8
1.1.4.4 Bouleuterion (Senate House)
Bouleuterion stands out as the best preserved ruin in Teos. According to
Polythros, proficiency tests by grammar and music teachers had been moved to the
Bouleuterion. Accordingly, it can be concluded that the Bouleuterion hosted other
purposes besides political meetings (Kadıoğlu, 2018, pp. 13-14).
1.1.4.5 Hellenistic City Wall
Kadıoğlu (2018, p.17) explains the walls are well preserved, from the Acropolis to
the South Harbor, and this area is the best studied part of the walls as a result of
excavations.
1.1.4.6 South Harbour (Southern Port)
According to Kadıoğlu (2018, p.19), Teos, one of the most important cities of
Ionia, had ports in both the north and south. Although there is no significant remains
of the port in the north, the South Port has been well preserved and has survived to
the present day.
9
CHAPTER 2
RESEARCH REVIEW
Natural hazards such as floods, storms, landslide, and tropical cyclones
have caused environmental damages and loss of human lives. Flood hazard is
one of the most frequent phenomena in the world. As summarized by
Sivakumar (2005, p.4), during 10 years (1993–2002) there were 2,654 hazard
events in the world where floods and windstorms accounted for approximately
70% of the hazards while the remaining 30% of the disasters were brought
about by droughts, landslides, forest fires, heat waves and others (Marfai et al.,
2008, p.1507) (Fig. 2.1).
According to Centre for Research on the Epidemiology of Disasters United
Nations Office for Disaster Risk Reduction & Wallemacq, House, (2018), between
1998 and 2017, 1.3 million people died and 4.4 billion were injured, lost their homes,
or were displaced as a result of climate-based and geophysical disasters. Earthquakes
and tsunamis are among the most damaging phenomena. In addition, drought, storm
and flood are natural events that should be considered.
Figure 2.1 Natural hazard events (Sivakumar, 2005, p.5)
2.1 Risk Factors
Risk analyzes are important both to reveal the sociological situation and to make
the natural environment sustainable. Due to the lack of studies conducted on the risk
factors that may threaten Teos at present, the following factors will be analyzed
10
(Figure 2.2).
For each risk analysis, the appropriate material and method that will allow risk
analysis to be performed will be used. As a result of all risk analyzes, it is aimed to
reveal the risk factors that threaten the ancient city of Teos the most.
Figure 2.2 Risk evaluation studies in Teos Ancient City
2.1.1 Urban Sprawl Analysis
Deelstra & Girardet (2000) stated that urban development leads to land structure,
land use and, accordingly, ecosystem change caused by humans.
Urban sprawl is a factor that negatively affects the ecosystem and prevents the
efficient use of the environment both in rural and urban terms (Congedo and Macchi,
2015).
Defining
Proximity to
Transportation
Routes
Watershed
Risk
Assessment
Urban
Sprawl
Analysis
Soil Erosion
Risk Analysis Coastal Flood Risk
Analysis
Earthquake
Risk
Assessment
Monitoring
Displacements
with PSI
Structural Technique
Damage
Assessment
11
As stated in Urban Sprawl (2021), urban sprawl is a concept that forces people to
travel long distances between trade centers, workplaces and homes in a poorly
planned city without considering all factors, and also negatively affects nature and
other living things.
Some of the effects of urban sprawl can be counted as increasing level of
pollution in air and water, higher water consumption due to population, deteriorated
human health, decrease in green areas, farmlands and fauna, increasing traffic
congestion and flood risk rate (Urban Sprawl, 2021).
Izmir, which has a population of about 4 million, is Turkey's third-largest city
(Yakut et al., 2021). According to the data published by Türkiye İstatistik Kurumu
(TÜİK) in 2021, annual population growth rate of Izmir province between 2019 and
2020 was 6.3% while the annual population growth rate of Seferihisar district was
8.52% .
As seen on population change graph (Fig. 2.3) and on total population change
graph (Fig. 2.4) made with the data provided from TÜİK (2021), in 1965, total
population of Seferihisar district was 9,661, the urban population was 5,269 while
the rural population was 4,392; until 2007, urban and rural population were almost
equal, as of 2007, urban population became 1.5 times more than the rural population;
in 2007, urban population was 16,114 while the rural population was 9,716. In 2008,
rural population demonstrably decreased to 3,276 while the urban population showed
an increase to 23,669. Since 2013, there is no sufficient rural population data that the
total population is equal to the urban population. As of 2020, total population of
Seferihisar district is 48,320. As for the town of the study area: Sığacık, the actual
total population is 3,637 while 32% is elderly (65 years and older) and 18% is young
population (TÜİK, 2021).
12
Figure 2.3 Total Population Change in Seferihisar Between 1965-2020 (Graph made by using the data
obtained from (TÜİK, 2021)
Figure 2.4 Total population change in Seferihisar between 2007 – 2020 (Graph made by using the data
obtained from (TÜİK, 2021)
Supervised Classification analysis will be used for urban sprawl detection in the
study area. In order to process satellite images, an empirical classification algorithm
known as Maximum Likelihood classifier will be utilized.
13
2.1.1.1 Supervised Classification
Killeen et al. (2015, p.492) stated that supervised classification analysis provides
the display and representation of areal data of each unit to be classified. Maximum
likelihood is one of the most frequently used algorithms today, which uses statistics,
functions and data suitable for the fields to be classified.
Foody (2002) emphasizes the importance of accuracy evaluation during remote
sensing based land-cover mapping process to be able to assess the end product in
remote sensing thus the quality improvement of the classification can be ensured.
2.1.2 Defining Proximity to Transportation
United States Environmental Protection Agency (2014) stated that pollution
emitted into the air from all kinds of motor vehicles is more common on roads with
high density due to the passing of more vehicles. Nitrogen dioxide (NO2) and ozone
(O3) were observed in the atmosphere, especially around the roads with high traffic
density.
Varotsos et al. (2009, p.590) explained that polluted substances in the atmosphere
play a negative role in the deterioration of the condition of both buildings and
cultural heritage. When these pollutants are combined with environmental effects,
the damage they cause increases exponentially.
The amounts of these gases in the study area were not measured, but it was
concluded that negative effects would occur as a result of the increase in vehicle
traffic due to the increase in roads
The negative effects of air pollution are not only seen on buildings, but also on
people. According to (DeJarnett et al., 2015, p.2), “close proximity to roadways has
been associated with the health problems of increased coronary artery disease
mortality, myocardial infarction, heart failure, deep vein thrombosis and stroke
mortality.”
14
The proximity of houses to public transport networks is a key factor in explaining
urbanization. The increase in the road networks over the years near the ancient city
of Teos, which is the study area, will be examined by digitizing orthophoto images.
2.1.3 Soil Erosion Risk Analysis
Siswanto & Sule (2019, p.1) stated that the steep slope is seen as one of the
important triggers of erosion. Although there are other factors that affect soil erosion,
slope has a significant importance in defining soil erosion. The steep slope will
increase the amount and velocity of runoff, thereby accelerating erosion due to more
transported and dissolved material. Generally, places with slopes of 8-15%, 15-25%,
25-40% have erosion risk.
Within the scope of this study, a slope map was created to determine soil erosion
risk in Teos Ancient City.
2.1.4 Watershed Risk Assessment
USGS (2019) stated that water covers about 71% of the Earth's surface. In this
case, the land covering the earth would be approximately 29%. According to Hooke
et al. (2013), more than half of the natural land cover is estimated to have been
altered by human action, as a result, situations that influence natural water resources
and their quality emerged.
Urbanization and the resulting deforestation and desertification are among the
factors that negatively affect water resources.
In Fig. 2.5, climate graph and rain measures of Seferihisar in a year can be
observed on (Climate-data.org, 2022).
15
Figure 2.5 Climate graph of Seferihisar (Climate-data.org, 2022)
According to the definition of Sesli Sözlük (2022), “a watershed is a land area
within which water flows down to a specific body of water, such as a river, lake, or a
drainage basin.”
Topographic boundaries between two or more neighbouring catchment basins,
such as a ridge or a crest, also form a watershed. The health of local streams is
severely impacted by urbanization.
United States Environmental Protection Agency (2022) explained the watershed
as a hydrologically-bounded ecosystem and that watershed management helps to
identify the problems associated with ground and surface waters, to observe the
effects of these problems on the environment and people, and to find solutions.
Major drainage networks will be identified and a watershed inventory will be
developed for environmental risk assessment in Teos Ancient City. The created
Digital Elevation Model (DEM) will be used to delineate the watersheds in the study
area.
16
2.1.5 Coastal Flood Risk Analysis
Samanta et al. (2014, p. 961) explained that factors causing coastal flooding
include storm surges and/or extreme high tidal waves flooding low coastal areas.
In densely populated coastal urban areas, rapid urbanization has significantly
increased susceptibilities. Sığacık is a coastal town whose population and the urban
sprawl have recently escalated, therefore it is crucial to monitor coastal flood risks to
avoid possible hazards.
“The earthquake that occurred on October 30, 2020, (Mw=6.9) triggered a
tsunami that resulted in the death of one person. This person was the first to die
because of a tsunami in Turkey” (Onat et al., 2022, p.78).
Özacar et al. (2020, p.17) observed the maximum tsunami height measured as
2.31 m. The maximum wave run-up, which can be explained as the distance between
the mean sea level and the highest point of wave crest that touches the structure
(Diwedar, 2016), was calculated as 3.82 m in Akarca Region.
According to the studies of Özacar et al. (2020, p.16) carried out in the field and
the statements of the people who were in the region at the time of the incident, it was
concluded that the places that were most heavily affected after the earthquake were
Sığacık Marina, Sığacık Bay and Akarca region. The distance of these places to the
epicenter was seen as 30 km. Tsunami generation zone, distribution of the tsunami
wave and wave run-up were seen spatio-temporally in the study of Özacar et al.
(2020, p.16) (Fig. 2.6, Fig. 2.7 & Fig. 2.8).
17
Figure 2.6 Before the beginning of tsunami (Özacar et al., 2020, p.16)
Figure 2.7 14 seconds after the beginning of tsunami (Özacar et al., 2020, p.16)
Figure 2.8 34 seconds after the beginning of tsunami (Özacar et al., 2020, p.16)
For hypothetical scenarios, flood maps will be created to determine the water level
18
and potential inundated ruins of Teos. In order to generate maps for vulnerable areas
and infrastructure elements in Teos Ancient City, impact status of risk factors and
flood hazard maps will be examined on ArcMap.
2.1.6 Earthquake Risk Assessment
Turkey is a country where active fault lines and tectonic movements are intense.
Onat et al. (2022, pp. 1-43) stated that Western Turkey has a high seismic
risk due to the subduction zone of the Eastern Mediterranean. The Hellenic Arc
is the most seismologically and geodynamically active region in the Alpine-
Himalayan Belt. Nineteen earthquakes of M≥6 occurred between 2008 and
2017, with epicenters often located in Southern Greece and Western Anatolia
and bordering the Aegean plate. In 2005, Seferihisar was shaken by a 5.9 (Mw)
earthquake. The Aegean Sea region in Turkey was shaken for two months
before 30 October, especially in 2020. These seismic activities were the
harbinger of the main shock. On October 30, 2020, a strong (Mw=6.9) and
shallow (14.9 km) earthquake struck Samos for 16 seconds. In the month
following the mainshock, 5068 aftershocks occurred, resulting in 117 deaths
and 1632 injuries.
In order to express the earthquake-prone region at the same level as this
earthquake, a potential ground motion activity map was created in Figure 2.9 and this
map includes a time period of 475 years (Onat et al., 2022, p. 2).
19
Figure 2.9 Representation of seismicity in PGA in 475 years. Adapted from (Onat et al., 2022, p. 3)
Sığacık is located in an earthquake-prone region due to the location of the fault
lines.
Bakak et al. (2015, pp. 233-234) stated that Gülbahçe Fault has been the most
important line in the morphological and structural separation of Izmir Bay and
Karaburun Peninsula and that epicenters were formed predominantly along the
southern part of the mentioned fault line. Active right-lateral strike-slip Seferihisar
Fault was located between the Gulf of Sığacık and Güzelbahçe which can be seen in
Figure 2.10, and this length was measured approximately as 30 km.
Figure 2.10 a) TOPEX topography map and b) TOPEX satellite free air gravity anomaly map (Bakak
et al., 2015, p. 234)
20
Figure 2.11 shows areas with seismic risk and Teos located in high risk area
(Zone I) (Halicioglu & Ozener, 2008, p. 4745).
Figure 2.11 Turkey earthquake risk map and rectangle covering Teos (Halicioglu & Ozener, 2008)
Geoscience Australia (2022) explained that Interferometric Synthetic Aperture
Radar (InSAR) is a useful geodetic technique that can identify movements of the
Earth's surface. InSAR observations can be utilized to detect, measure, and monitor
changes related to geophysical activities. When combined with ground-based
geodetic monitoring, such as Global Navigation Satellite Systems (GNSS), InSAR
can identify surface movements precisely.
Working mechanism of InSAR
According to Geoscience Australia (2022), InSAR uses two or more Synthetic
Aperture Radar (SAR) images of an area to observe surface movements over a period
of time. Remote sensing satellites collecting SAR images transmit pulses of
microwave energy to the Earth's surface and record the amount of backscattered
energy. SAR images contain information about the Earth's surface in the form of
amplitude and phase components of the backscattered radar signal.
In Figure 2.12, working principle of InSAR can be observed.
21
Figure 2.12 Working principle of InSAR (Geoscience Australia, 2022)
Displacements in Sığacık will be identified based on a specific earthquake that
occurred in 2017.
2.1.7 Structural Damage Assessment
“Light Imaging Detection and Ranging (LiDAR) can remotely detect the surface
and deformation shape of structures without the need for attached sensors” (Jo et al.,
2020, p. 1).
According to Olsen et al. (2010, pp. 264-265), Terrestrial Laser Scanning (TLS)
has been developed to effectively model 3D objects with remote sensing.
Chen et al. (2013, p. 487) stated that 3D LiDAR is a scanning laser technology
that can gather millions of optical-photonic points that contain the light diffraction
and XYZ position data of each scanned point.
Chen et al. (2013, pp. 487-493) explained that LiDAR scanning effectively
performs damage assessment in large structures with its speed and high resolution.
Oblique and multi-perspective imagery will be obtained. These images will be
photogrammetrically analyzed and utilized to determine millimetric deformation in
22
Teos Ancient City.
2.1.8 UAV Imaging
According to Ngadiman et al. (2018 pp. 1-6), Unmanned Aerial Vehicle (UAV)
refers to a class of aircraft that can fly without the onboard presence of a pilot.
Orthophotographs are produced by scanning an aerial photo diapositive,
orthorectifying the digital image, and registering it to a coordinate system and map
projection. Traditional methods are time consuming and costly compared to UAV so
UAV has become an alternative in orthophoto map making because it is also
considered time-effective. Furthermore, with user-friendly imaging software it is
easy to turn images into georeferenced orthomosaic models (Ngadiman et al., 2018
pp. 1-6).
UAV flights were carried out to observe the most up-to-date status of the ruins in
Teos.
2.1.9 Monitoring Displacements with PSI Technique
Monitoring of ground deformations caused by natural processes (tectonics,
subsidence or slope movements) or by anthropogenic transformation of the
natural environment (groundwater exploitation, gas, oil and drilling) is a key
factor to mitigate risks on civil structures and the surrounding environment. In
particular, the monitoring of linear infrastructure networks is crucial for the
safety of population in terms of socioeconomic resources and for the
sustainability of production processes. .... In recent years, the use of a long
series of continuous differential radar interferometry data has emerged as a
very useful method for monitoring slow-moving landslides that can lead to
damage of structures. The SAR technique can be used to analyze the static
behavior of civil structures in both disrupted (during construction or
restoration work) and undisrupted conditions and can aid in damage
assessment analysis and scenario-based risk assessment. .... Over the years,
DInSAR deformation time series have been exploited in a wider variety of
23
geophysical contexts, such as seismic, volcanic, and mass movement scenarios,
with a dual purpose: to map ground displacements and monitor them over time
(D’Aranno et al., 2021, pp. 1-2).
Displacements in Teos Ancient City will be monitored by using Persistent
Scatterer Interferometry (PSI) Technique as an alternative for LiDAR surveys.
2.2 Analytic Hierarchy Process (AHP)
Saha et al. (2021, p. 6) stated that Analytical Hierarchy Process (AHP) is a
common and subjective method that includes many criteria and helps to decide by
determining the weights of the criteria when it is necessary to decide between these
criteria.
Goepel, (2017, p. 1) has developed a web-based, free of charge AHP online
system that allows comparison of decision criteria and analysis to aid decision
making. The software can compute group concurrence based on Shannon α and β-
entropy and estimate weight uncertainties based on random small variations that
come from judgements the user enters.
The mentioned Analytic Hierarchy Process system (AHP-OS) which can be found
online and free of charge will be used to determine the order of importance of risk
factors.
24
CHAPTER 3
MATERIALS AND METHOD
Satellite images and software used to analyze the risk factors mentioned in the
introduction are shown in the tables below (Table 3.1 & Table 3.2).
The reason why satellite images of different dates and resolutions were used was
due to the fact that the risk analyzes to be made have different contents.
The materials mentioned within the scope of "service acquisiton" were covered by
the "Department of Scientific Research Projects at Dokuz Eylül University" since the
thesis was evaluated as a scientific research.
Table 3.1 Satellite images used for risk evaluation studies. Table made by the data obtained from
(ESA, n.d.-a; ESA, n.d.-b)
Image Date Resolution Usage Obtained
from
SPOT –
6
2013 Panchromatic: 1.5
m at nadir
Multispectral: 6 m
at nadir
Supervised
Classification
Analysis
İTÜ UHUZAM
(https://web.cscrs.itu.
edu.tr)
SPOT –
6
2020 Panchromatic: 1.5
m at nadir
Multispectral: 6 m
at nadir
Supervised
Classification
Analysis
İTÜ UHUZAM
(https://web.cscrs.itu.
edu.tr)
Sentinel
- 1
2017 High: 10m/px for
IW and 25m/px for EW
Medium: 40m/px for
IW and EW
Earthquake
Risk Assessment
Copernicus Sentinel
data 2015, processed
by European Space
Agency
(https://www.esa.int/)
25
Table 3.1 continues
The software used in the risk analysis covering the work area are shown in Table 3.2.
Table 3.2 Software used for risk evaluation studies
Ortophot
o Image
1957 0.74x0.93 cm Defining
Proximity to
Transportation
Routes
General Directorate of
Mapping
(https://www.harita.gov.tr)
Ortophoto
Image
1986 0.22cmx0.28cm Defining
Proximity to
Transportation
Routes
General Directorate of
Mapping
(https://www.harita.gov.tr)
Ortophoto
Image
2020 0.22cmx0.28cm Defining
Proximity to
Transportation
Routes
General Directorate of
Mapping
(https://www.harita.gov.tr)
UAV
Image
2021 Service
acquisition
Structural
Damage
Assessment
Department of Scientific
Research Projects at Dokuz
Eylül University
Lidar
Image
2021 Service
acquisition
Structural
Damage
Assessment
Department of Scientific
Research Projects at Dokuz
Eylül University
Software Usage Obtained from
IDRISI - Supervised Classification Analysis GIS laboratory of The
Graduate School of Natural
and Applied Sciences at
Dokuz Eylül
University(https://fbe.deu.edu.
tr/)
26
Table 3.2 continues
3.1 Exploratory Factor Analysis
The representation of natural and human-induced measurable risk factors
threatening the ancient city of Teos with their inputs can be found in the table below
(Table 3.3).
ArcMap - Defining Proximity to
Transportation Routes
- Soil Erosion Risk Analysis
-Watershed Risk Assessment
- Coastal Flood Risk Analysis
GIS laboratory of The
Graduate School of Natural
and Applied Sciences at
Dokuz Eylül University
(https://fbe.deu.edu.tr/)
The Sentinel Application
Platform (SNAP)
- Earthquake Risk Assessment ESA
(https://www.esa.int/)
Service acquisition - UAV Imaging Department of Scientific
Research Projects at Dokuz
Eylül University
27
Table 3.3 Representation of natural and human-induced measurable risk factors
Evaluation
of the most
recent
population data
Supervised
Classification
Urban
Sprawl
Analysis
Digitizing
orthophoto
images taken
in different
years
Defining
Proximity to
Transportation
Routes
Creating a
slope map
based on a
DEM
Soil Erosion
Risk Analysis
Delineating
watersheds
based on a
DEM
Watershed
Risk
Assessment
Creating
flood hazard
maps
Coastal
Flood Risk
Analysis
Identifying
displacements
with InSAR
Earthquake
Risk
Assessment
Determining
millimetric
deformation
with LiDAR
Monitoring
displacements
with PSI
Technique
Structural
Damage
Assessment
Carrying
out UAV
flights
Observing
the most up-todate
status of
the ruins with
UAV imaging
28
3.1.1 Urban Sprawl Analysis
The studies to monitor and explore anthropogenic hazard risks in Teos Ancient
City consist of urban sprawl which is the the rapid geographic growth of cities and
towns. By making this analysis, urban growth in the study area can be determined.
Another study to analyze the anthropogenic risk in Teos was compromised of
defining proximity to transportation routes. Accessibility to transportation routes is
seen to be a major factor in urbanization.
It is important to perform these two analyzes in order to accurately assess the
anthropogenic impact.
Urban sprawl can also be demonstrated with official statistical data. These data
show the numerical increase in the urban sprawl in the region over the years (Fig. 2.3
& Fig. 2.4).
3.1.1.1 Supervised Classification Analysis
Another way to monitor the urban sprawl can be realized by land use/land change
observation which can be determined by making supervised classification analysis.
This analysis was carried out in accordance with the basis of comparing the change
of classes in the satellite images obtained on two different dates based on the flow
chart which consists of acquiring satellite images, enhancing and classifying them
(Fig. 3.1).
Satellite image classification was implemented according to the CORINE Land
Cover nomenclature. The classes covering the study area were observed as
"continuous urban fabric, pastures, meadows and other permanent grasslands, annual
crops associated with permanent crops, bare rock and sea".
29
Figure 3.1 Flow chart of supervised classification analysis
SPOT-6 images from 2013 and 2020 were acquired to create training areas and
signature files for image classification (Fig. 3.2 & Fig. 3.3).
Figure 3.2 SPOT-6 image taken in 2013 of Teos Ancient City and Seferihisar
30
Figure 3.3 SPOT-6 image taken in 2020 of Teos Ancient City and Seferihisar
Acquired SPOT-6 images were enhanced. For each class, polygons as training
sites were chosen across the images. All of the drawn polygons were merged into
their respective class. Signature files were created. Finally, maximum likelihood
classification was realized which created an image that includes the colors for each
class based on the CORINE Land Cover nomenclature and the images were
classified (Fig. 3.4 & Fig. 3.5)
Figure 3.4 Maximum likelihood classification for SPOT-6 image taken in 2013
31
Figure 3.4 continues
Figure 3.5 Maximum likelihood classification for SPOT-6 image taken in 2020
3.1.2 Defining Proximity to Transportation Routes
Road network in Sığacık town and in Seferihisar district were analyzed in 1957,
1986 and 2020 using digital ortophoto images in order to observe the variation of the
total path length in the study area with time.
Initially, new shapefiles as polylines were created using ArcMap software. Spatial
reference of the digital ortophoto images were imported. All of the the paths were
digitized. The separate digitized lines were merged and they became one single line
32
so that the total length of the routes for each year was calculated (Fig. 3.6, Fig. 3.7 &
Fig. 3.8).
Figure 3.6 Road network in Sığacık town and in the center of Seferihisar in 1957
Figure 3.7 Road network in Sığacık town and in the center of Seferihisar in 1986
33
Figure 3.8 Road network in Sığacık town and in the center of Seferihisar in 2020
3.1.3 Soil Erosion Risk Analysis
In order to analyze soil erosion, one of the natural risks threatening Teos Ancient
City, a slope map was created using the Digital Elevation Model (DEM).
DEM of Teos was obtained from the contour layer using Google Earth data from
2020. In the next step, the slope map was obtained from Digital Elevation Model
using “Slope” tool on ArcMap software (Fig. 3.9).
Places with a higher percentage of slope on the slope map have a higher risk of
soil erosion.
34
Figure 3.9 Slope map of Teos Ancient City
3.1.4 Watershed Risk Assessment
A watershed analysis was carried based on the flow chart (Fig. 3.10) to reveal the
basins in the study area and to identify possible risks.
35
Figure 3.10 Flow chart for delineating a watershed
36
A Digital Elevation Model (Fig. 3.11) was created to delineate the watersheds in
the study area.
Figure 3.11 Flow chart for delineating a watershed
“Fill” tool was used to remove imperfections or sinks on the raster (Fig. 3.12).
Figure 3.12 Small imperfections in the data were removed using Fill tool
37
Then “Flow Direction” tool was used to determine the direction which water
would flow out of each cell (Fig. 3.13)
Figure 3.13 Flow direction analysis of the study area
“Basin” tool was used to create a raster delineating all drainage basins (Fig. 3.14)
Figure 3.14 Delineated watersheds in the study area
38
The result raster of basin was transformed into the vector polygon (Fig. 3.15)
Figure 3.15 Basin polygons in the study area
Basin polygon was chosen and the chosen basin was cut from the rest of the basin
polygons (Fig. 3.16).
Figure 3.16 Clipped basin
39
Subsequently “Flow accumulation” tool was used to calculate the number of
upslope cells flowing to a location (Fig. 3.17)
Figure 3.17 Flow accumulation analysis
“Raster Calculator” tool was used to define the stream network system. The
accumulation value was set greater than 2,500 which means all cells with more than
2,500 cells flowing into them would be part of the stream network. This value
depends on the size of the pixel and the raster. “Raster to Polyline” tool was used in
order to transform the stream network raster to a polyline layer (Fig. 3.18).
40
Figure 3.18 Stream network in Teos Ancient City
DEM was clipped based on the selected basin. Finally, based on the study area, 5
pour points were chosen according to the proximity status of each ruin to delineate
the watersheds (Fig. 3.19)
Figure 3.19 Chosen pour points in the study area
41
Finally, based on the chosen pour points, watersheds were delineated (Fig. 3.20).
Figure 3.20 Delineated watersheds in the study area
3.1.5 Coastal Flood Risk Analysis
Sea levels of 1m, 3.8m and 5m were selected as a result of the tsunami observed
after the earthquake with a magnitude of Mw 6.9 on October 30, 2020, which greatly
affected İzmir and Seferihisar. Coastal flood risk analysis was realized to evaluate
the possible impact in case of a larger earthquake or another natural hazard likely to
result in a tsunami.
“Reclassify” tool was used in order to modify the values in the raster using userdefined
values of 1m, 3.8m and 5m (Fig. 3.21, Fig. 3.22 & Fig. 3.23).
42
Figure 3.21 Coastal flood risk in case of a 1m. of sea level rise
.
Figure 3.22 Coastal flood risk in case of a 3.8m. of sea level rise
43
Figure 3.23 Coastal flood risk in case of a 5m. of sea level rise
3.1.6 Earthquake Risk Assessment
Synthetic aperture radar interferometry was applied to create a displacement map
to measure the topography of the surface and its changes over time (before and after
the earthquake that occurred on 12.05.2017 in the Gulf of Kuşadası).
Satellite images (Sentinel-1) were acquired on two different dates (07.05.2017 and
13.05.2017) to produce co-seismic interferograms and observe post-seismic
deformation due to the earthquake that occurred on 12.05.2017 in the Gulf of
Kuşadası. The Sentinel Application Platform (SNAP), which is free of charge, was
used to perform differential interferometric processing of two Single Look Complex
(SLC) data (Fig. 3.24).
The processing steps of Interferometric Synthetic Aperture Radar (InSAR)
analysis for two selected Sentinel-1 satellite images can be found as coregistration,
interferogram formation, deburst, topographical phase removal, phase filter,
unwrapping, and phase to displacement.
44
Figure 3.24 Displacement map after applying InSAR
3.1.7 Structural Damage Assessment
Terrestrial LiDAR scanner was planned to be used in order to detect millimetric
changes in the structures between two different dates. However, because of the
pandemic conditions and the lack of economic funding, second measurements could
not be realized.
LiDAR outputs obtained as a result of the first measurement are 2 pieces (Fig.
3.25 & Fig. 3.26). In the 2nd output image (Fig. 3.26), vegetation has been removed
for more accurate LiDAR studies.
45
Figure 3.25 Terrestrial LiDAR output image in the study area
Figure 3.26 Terrestrial LiDAR output image in the study area without vegetation
46
3.1.8 UAV Imaging
The UAV images were used to produce the most up-to-date map of the study area
(Fig. 3.27).
The UAV flights included oblique picture acquisition and were pre-planned using
modern UAV systems' waypoint capability.
Figure 3.27 UAV image of Teos made with UAV flight outputs in 2021
47
In addition, the most up-to-date UAV images of the important ruins in Teos were
obtained during the UAV flights (Fig. 3.28, Fig. 3.29, Fig. 3.30, Fig.3.31 & Fig. 3.32)
Figure 3.28 UAV image taken in 2021 that shows Acropolis
Figure 3.29 UAV image taken in 2021 that shows Theatre
48
Figure 3.30 UAV image taken in 2021 that shows Dionysus Temple
Figure 3.31 UAV image taken in 2021 that shows Bouleuterion
49
Figure 3.32 UAV image taken in 2021 that shows Southern Port
3.2 Analytic Hierarchy Process (AHP)
An online software called AHP Online System - AHP-OS developed by Klaus D.
Goepel, BPMSG which works based on the AHP Statistics technique was used for
evaluating all the risk analysis results together and to compare each risk factor with
the others. In determining the order of importance of risk factors relative to each
other, besides my personal views, the views of my thesis advisor Asst. Prof. A.
Hüsnü Eronat and Assoc. Prof. Fethi Bengil were also used.
If the influence of two criteria was the same or had equal importance, a score of 1
was given and a score of 9 was given when the influence of one criterion was
extreme over another criterion in the comparison table that was adapted from Goepel,
K.D. (2018) in which the scale was defined as 1- Equal Importance, 3- Moderate
importance, 5- Strong importance, 7- Very strong importance, 9- Extreme
importance (2,4,6,8 values in-between). After normalizing each value by dividing the
actual value to its sum of column value, weights were derived by arithmetic mean
method by using the software.
50
CHAPTER 4
RESULTS
The results obtained after the analysis of each risk factor are presented under the
respective headings.
Urban Sprawl Analysis
Population change, which is a part of urban sprawl, was observed according to
official statistical data (Fig 2.3 & Fig. 2.4).
As an alternative perspective to official statistical population data, obtained
SPOT-6 images from 2013 and 2020 were subjected to Supervised Classification
Analysis (Fig. 3.4 & Fig. 3.5), thus the values of each class in km² were revealed
(Table 4.1 & Table 4.2).
Table 4.1 Areas (in km²) for each class after maximum likelihood classification for SPOT - 6 image
taken in 2013
51
Table 4.2 Areas (in km²) for each class after maximum likelihood classification for SPOT - 6 image
taken in 2020
Defining Proximity to Transportation Routes
After digitizing orthophoto images from 1957, 1986 and 2020 (Fig. 3.6, Fig. 3.7
& Fig. 3.8), the total path length in the study area for each year was calculated. In
1957, the total length of roads was 23.13 km. The total road length increased by 1.8
times and reached 41.63 km in 1986. Compared to 1986, the total road length
increased by 1.9 times and reached 79.10 km in 2020 (Table 4.3).
Table 4.3 Total road length (km) by year
Year Total Path Length (km)
1957 23.13
1986 41.63
2020 79.10
52
Soil Erosion Risk Analysis
After the slope map was created (Fig. 3.9), the slope value range of each ruin was
revealed (Table 4.4).
Table 4.4 Slope value range of each ruin
Ruin Slope Value Range (cm)
Acropolis 7.92 -17.9
Theatre 4.70 - 7.91
Dionysos Temple 2.67 - 4.69
Bouleuterion 1.20 - 2.66
Southern Port 0.00031 - 1.19
According to the slope value range data obtained from the slope map, the
appropriate slope level of each ruin was determined (Table 4.5). The boxes show
which slope column each ruin belongs to.
Table 4.5 Soil erosion risk classes. Adapted from (Scotland’s soils)
Ruin Almost
Level Slope
(1-2°)
Gentle
Level Slope
(2-5°)
Moderate
Level Slope
(5-10°)
Moderately
Steep Level
Slope
(10-18°)
Steep
Slope
(18-
30°)
Southern Port 1 2 3 4 5
Dionysus
Temple
1 2 3 4 5
Bouleuterion 1 2 3 4 5
Theatre 1 2 3 4 5
Acropolis 1 2 3 4 5
53
Watershed Risk Assessment
It was shown whether the ruins could be in the flow direction of the delineated
watersheds (Fig. 3.20) that emerge according to the selected pour points (Fig. 3.19).
It was also stated which watersheds could influence the ruins that are in the flow
direction (Table 4.6). Dionysos Temple does not seem to be affected in any
watershed but since it is located close to the stream network, it is still under the
influence, although not as much as other ruins.
Table 4.6 The state of being in the direction of the watershed flow
Ruin The state of being in the direction of the
watershed flow
Acropolis Yes / Watershed - 5
Theatre Yes / Watershed - 5
Dionysos Temple No
Bouleuterion Yes / Watershed - 1
Southern Port No
Coastal Flood Risk Analysis
Possible impact areas of the selected sea level rises of 1m, 3.8m and 5m whose
visual results were shown before in Fig. 3.21, Fig. 3.22 and Fig. 3.23 are indicated in
km² (Table 4.7).
Table 4.7 Possible impact areas for the selected sea level rises
Hypothetical sea level rise (m) Possible impact area (km²)
1 0.087445
3.8 0.270287
5 0.42518
54
Earthquake Risk Assessment
The surface deformation outputs were shown by the interferograms generated
from the InSAR study (Fig. 3.24). The following table shows the values of maximum
positive and maximum negative on displacement map (Table 4.8).
Table 4.8 Maximum positive and maximum negative values on the displacement map
Maximum Positive Value (cm) 21
Maximum Negative Value (cm) 6.6
Structural Damage Assessment
The first measurements made with terrestrial LiDAR could not be completed due
to Covid-19 and adverse weather conditions. No conclusion could be reached with
the output images obtained (Fig. 3.25 & Fig. 3.26).
UAV Imaging
A map covering the ancient city of Teos and its surroundings, which was created
with the data obtained after the UAV flights, was revealed (Fig. 3.27).
High resolution UAV images of all important ruins in Teos were obtained after
UAV flights (Fig. 3.28, Fig. 3.29, Fig. 3.30, Fig. 3. 31 & Fig. 3.32).
Monitoring Displacements with PSI Technique
Output images created with the PSI technique, which allow displacement
observations in and around Teos Ancient City, were obtained through personal
communication with Ph.D. student Hüseyin Yaşar (Fig. 4.1 & Fig. 4.2).
55
Figure 4.1. Displacement map made with PSI technique (H. Yaşar, personal communication, April 12,
2022)
Figure 4.2. Displacement map made with PSI technique (H. Yaşar, personal communication, April 12,
2022)
56
Analytic Hierarchy Process (AHP)
As a result of the combination of my evaluation and the views of my thesis
advisor Asst. Prof. A. Hüsnü Eronat and Assoc. Prof. Fethi Bengil, the comparative
significance of each risk factor with each other was determined as in the table (Table
4.9).
The boxes in columns A and B indicate the risk factor being compared against the
other risk factor. The boxes in the columns "equal" and "how much more" indicate
how important the factor selected in column A or B is compared to the other risk
factor. If the two factors are of equal importance, "equal" was selected. If the
selected factor is more important than the other risk factor, the most appropriate
value between 1 and 9 was chosen (Table 4.9).
57
Table 4.9 AHP priorities for the risk factors
As a result of the AHP analysis made with the software by Goepel, K.D. (2018),
the three most important risk factors for Teos were determined as urban sprawl,
proximity to transportation routes and earthquake (Table 4.10). While the number of
comparisons was 21, consistency ratio was calculated as 5.4%.
58
Table 4.10 Weights obtained as a result of comparisons
Percent consolidated results of all risk factors were also obtained as a result of the
application (Fig. 4.3).
Figure 4.3. Consolidated results after AHP analysis
59
CHAPTER 5
DISCUSSION
According to the literature review, no previous study has been found in which the
risk factors of any cultural heritage are discussed on such a large scale though similar
results were found as Agapiou et al. (2015) stated that cultural heritage can be
damaged by both human and natural hazards, and it has been understood that the
most effective detection of these hazards and taking the necessary precautions are
possible with remote sensing and GIS. As a result of all risk analyzes carried out in
the study area, the following conclusions were reached:
- One of the main effects of population growth was seen as the increase of the
urbanization rate. While urbanization rate rises, other classes such as “Annual crops
associated with permanent crops” and “Pastures, meadows and other permanent
grasslands” decrease evenly (Fig. 5.1).
Figure 5.1. Comparison of gains and losses for each class after supervised classification analysis
- With the increase in population in the study area, more roads were needed. The
paving process, making of new roads, the renewal and improvement of old roads
have begun, also the paths in Teos Ancient City have been improved, allowing
visitors to easily navigate. Until today, intermediate roads have been built in order to
make excavation works easier and to connect the existing roads to each other in the
ancient city of Teos (Fig. 3.6, Fig. 3.7 & Fig. 3.8). There has been an increase in the
total road length to meet the need, especially with the increase in the urban
population in the region (Table 5.1).
60
Table 5.1. Increment of total road length over years
Road Network (km) Year Change (%)
23.13 1957 180
41.63 1986 190
79.10 2020 -
- For the soil erosion risk analysis, slope analyzes of the ruins in Teos were made
and it was understood that the ruins with the highest soil erosion risk were Acropolis
Theatre and partly Dionysos Temple (Table 4.4 & Table 4.5.).
- As a result of the watershed risk analysis, the ruins in the direction of the basin
flow that may be under the influence of possible damage were observed as Acropolis,
Theater and Bouleuterion (Table 4.6.).
- According to the selected hypothetical sea level rises, there would be no ruins to
be affected at 1 meter of rise, while 3.8 meters and 5 meters of sea level rise would
affect the vicinity of Bouleuterion.
- Based on the InSAR deformation results (Table 4.8), no significant data were
obtained that could be evaluated. In future studies, a more detailed earthquake
analysis should be done with higher resolution satellite images.
- As a result of the UAV images obtained by UAV flights (Fig. 3.28, Fig. 3.29,
Fig. 3.30, Fig. 3.31 & Fig. 3.32) and the map created with these images (Fig. 3.27),
the most up-to-date images of the ruins in Teos were obtained in high resolution.
According to the images, it was observed that vegetation surrounds the Acropolis,
Theater and Dionysus Temple. Southern Port, on the other hand, is notable for its
obvious proximity to residences and restaurants used by people. The illegal
construction around Teos was not reflected in the orthophoto images, but this
situation was revealed in in-situ observations.
61
- Better results in PSI can be obtained with studies to be carried out by taking
more detailed radar images.
- As a result of the Analytic Hierarchy Process, the most important risk factors
threatening Teos were observed as Urban Sprawl, Proximity to Transportation
Routes and Earthquake.
62
CHAPTER 6
CONCLUSION
This research aimed to reveal the current situation of Teos Ancient City against
natural and human-induced risk factors. Based on the Analytical Hierarchy Process,
in which all risk factors were considered together, it has been concluded that the
most important risk factors were urban sprawl, proximity to transportation routes,
earthquake, watershed, soil erosion, structural damage and coastal flood, in order of
importance.
While analyzing the risk factors threatening Teos, it was understood that the most
important and current risk factor was the urban sprawl, and the risk of proximity to
transportation routes emerged as a result of urban sprawl.
Risk factors other than urban sprawl and proximity to transportation routes are
nature-based risk factors, and if precautions are not taken, the impact area of natural
risk factors will increase directly proportional with the increase in urban sprawl, and
the affected area will not be limited to Teos, but the people in the irregular
settlements around Teos will also be affected.
While examining factors such as urban sprawl (supervised classification),
proximity to transportation routes and earthquake risk assessment, satellite images
taken from different dates were used in the methodology in order to make
comparisons and obtain detailed analysis data.
Each of urban sprawl and structural damage assessments were made using 2
different analyzes in order to address the time-dependent variation of both risk
factors. It was sufficient to use a single method in the evaluation of other risk factors.
When the most recent high-resolution orthophoto images obtained were examined,
it was observed that illegal construction and irregular vegetation cover the ruins of
Teos. Based on these conclusions, irregular vegetation and illegal construction in the
archaeological site should be checked in detail with both in-situ studies and regular
UAV flights and necessary precautions should be taken.
63
Slope map of Teos Ancient City (Fig. 3.9) shows that the most hazardous ruins
that can be affected because of soil erosion are Acropolis, Theatre and partly
Dionysos Temple. Planting grass, adding mulch or rocks and using mulch matting to
hold vegetation on slopes can be the solution to prevent soil erosion around the most
at risk ruins of Teos.
Measures to shield ruins from exposure to exterior city, as well as probable
excessive light exposure and high and changing temperature and humidity, could
lessen the risk of possible damage to ruins.
In conclusion, this research is not limited to an initiative for the protection of Teos,
which is a cultural asset, but also aims to comprehensively reveal the risk factors of
cultural heritages both in Turkey and in various parts of the world using GIS and
remote sensing, and to analyze these risk factors by using the Analytic Hierarchy
Process.
64
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