ISTANBUL TECHNICAL UNIVERSITY  GRADUATE SCHOOL 

M.Sc. THESIS 

JANUARY 2023 

UML MODELLING OF DISASTER MANAGEMENT DATA 

ACCORDING TO TUCBS DATA DEFINITION GUIDE: 

ISTANBUL EXAMPLE 

Özge USAL 

Department of Geomatics Engineering 

 

Geomatics Engineering Programme 

 



 

  



 

   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
JANUARY 2023 

 

ISTANBUL TECHNICAL UNIVERSITY  GRADUATE SCHOOL 

UML MODELLING OF DISASTER MANAGEMENT DATA 

ACCORDING TO TUCBS DATA DEFINITION GUIDE: 

ISTANBUL EXAMPLE 
 

M.Sc. THESIS 

Özge USAL 

 (501191637) 

Thesis Advisor: Associate Prof. Dr. Turan ERDEN 

 

Department of Geomatics Engineering 

 

Geomatics Engineering Programme 

 



 

  



 

   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Geomatik Mühendisliği Anabilim Dalı 

 

Geomatik Mühendisliği Programı 

 

OCAK 2023 

İSTANBUL TEKNİK ÜNİVERSİTESİ  LİSANSÜSTÜ EĞİTİM ENSTİTÜSÜ 

TUCBS VERİ TANIMLAMA KILAVUZUNA GÖRE 

AFET YÖNETİMİ VERİLERİNİN UML İLE MODELLENMESİ: 

İSTANBUL ÖRNEĞİ 
 

YÜKSEK LİSANS TEZİ 

Özge USAL 

(501191637) 

Tez Danışmanı: Doç. Dr. Turan ERDEN 

 



 

 

 

 

 

 

 

 



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Thesis Advisor:  Associate Prof. Dr. Turan ERDEN            ..............................

  Istanbul Technical University  

Jury Members:  Prof. Dr. Himmet KARAMAN  .............................. 

Istanbul Technical University 

Jury Members:  Prof. Dr. Arif Çağdaş AYDINOĞLU        .............................. 

Gebze Technical University 

 

 

 

 
 

 

 

Özge USAL, a M.Sc. student of ITU Graduate School student ID 501191637 

successfully defended the thesis/dissertation entitled “UML MODELLING OF 

DISASTER MANAGEMENT DATA ACCORDING TO TUCBS DATA 

DEFINITION GUIDE: ISTANBUL EXAMPLE”, which she prepared after fulfilling 

the requirements specified in the associated legislations, before the jury whose 

signatures are below. 

 

 

Date of Submission : 29 December 2022 

Date of Defense : 30 January 2023 
 



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To my family and my loved ones, 

 

 

 



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ix 

FOREWORD 

I would like to express my deepest gratitude to my advisors Associate Prof. Dr. Turan 

ERDEN and Prof. Dr. Himmet KARAMAN, for their invaluable guidance and 

gracious support throughout my MSc journey. 

For their valuable contributions to my life, I am grateful to all members of the 

Geomatics Engineering Department. 

I thank my parents and sisters for encouraging me throughout my academic career. 

Lastly, I would like to thank my spouse Deniz USAL for everything that he brought to 

my life as well as his support in this study. 

 

 

 

December 2022 

 

                                   Özge USAL 

                    (Geomatics Engineer) 

 

 

 

 

 

 

 

 

 

 

  



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TABLE OF CONTENTS 

Page 

FOREWORD  ......................................................................................................... ix 

TABLE OF CONTENTS  ......................................................................................... xi 

ABBREVIATIONS ................................................................................................. xiii 
LIST OF TABLES ................................................................................................... xv 

LIST OF FIGURES ............................................................................................... xvii 
SUMMARY  ....................................................................................................... xix 
ÖZET  ....................................................................................................... xxi 
1. INTRODUCTION .................................................................................................. 1 

1.1 Purpose of Thesis ............................................................................................... 2 

1.2 Method  .......................................................................................................... 3 

2. GENERAL INFORMATIONS ............................................................................. 5 
2.1 Geographical Information Systems .................................................................... 5 

2.1.1 GIS components .......................................................................................... 5 
2.1.2 Data models for GIS .................................................................................... 6 

2.1.3 GIS process ................................................................................................. 7 
2.1.3.1 Data capture .......................................................................................... 7 

2.1.3.2 Data manipulation ................................................................................ 7 

2.1.3.3 Data management ................................................................................. 8 

2.1.3.4 Query & analyze ................................................................................... 8 
2.1.3.5 Visualization ......................................................................................... 8 

2.2 Disaster and Disaster Management .................................................................... 8 
2.2.1 Disaster ........................................................................................................ 8 

2.2.1.1 Factor causing disaster ......................................................................... 9 
2.2.1.2  Disaster types..................................................................................... 10 

2.2.1.2.1 Natural disasters .......................................................................... 10 

2.2.1.2.2 Unnatural disasters ...................................................................... 10 
2.2.1.2.3 Complex disasters ....................................................................... 10 

2.2.2 Disaster management ................................................................................ 12 
2.2.2.1 Phases of disaster management and the disaster cycle ....................... 16 

2.3 GIS and Disaster Management ......................................................................... 18 
2.3.1 Development of GIS.................................................................................. 18 

2.3.2 GIS and Disaster Management .................................................................. 19 
2.4 GIS Standards ................................................................................................... 21 

2.4.1 INSPIRE .................................................................................................... 21 

2.4.2 Turkish National Geographical Information System (TUCBS) ................ 21 
2.4.3 OGC (Open Geospatial Consortium) ........................................................ 22 

2.5 Databases  ........................................................................................................ 23 
2.5.1 Database model ......................................................................................... 23 
2.5.2 Geographical databases ............................................................................. 24 



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2.6 Development of TUCBS .................................................................................. 25 

2.7 TUCBS Geodata Themes ................................................................................. 29 
2.7.1 TUCBS Natural risk zones theme ............................................................. 33 

2.7.1.1 “TehlikeAlani” Hazard Area .............................................................. 34 
2.7.1.2 “TehlikeAltindakiVarlik” (ExposedElement) .................................... 35 

2.7.2 “RiskBolgesi” (RiskZone) ......................................................................... 36 
2.7.3 “GozlenenOlay” (ObservedEvent) ............................................................ 37 

2.8 Unified Modelling Language/UML .................................................................. 38 

2.8.1 UML Relation Types ................................................................................. 39 
2.8.1.1 Association ......................................................................................... 39 
2.8.1.2 Inheritance .......................................................................................... 40 
2.8.1.3 Aggregation ........................................................................................ 41 
2.8.1.4 Composition ....................................................................................... 42 

2.8.2 Data Modelling with UML ........................................................................ 42 
2.9 Geography Markup Language/GML ................................................................ 43 

2.10 Hale Studio ..................................................................................................... 45 

3. STUDY  ........................................................................................................ 47 
3.1 Study Area  ........................................................................................................ 47 
3.2 Data Definition ................................................................................................. 48 

3.3 Data Transformation ......................................................................................... 49 
3.4 Data Sharing ..................................................................................................... 56 

4. CONCLUSION AND SUGGESTIONS .............................................................. 59 
REFERENCES  ........................................................................................................ 63 
APPENDICES  ........................................................................................................ 67 

CURRICULUM VITAE .......................................................................................... 73 



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ABBREVIATIONS 

AI : Artificial Intelligence 

CBS : Coğrafi Bilgi Sistemleri  

CRS : Coordinate Transformation Service 

CS/W : Catalog for the Web 

DBMS : Database Management System 

ER : Entity Relationships 

HGK : Harita Genel Komutanlığı 

ITRF : International Terrestrial Reference Frame 

GIS : Geographical Information Systems 

GML : Geography Markup Language 

INSPIRE : Infrastructure for Spatial Information in the European Community 

ISO : Iternational Organization for Standardization 

KBS : Urban Information System (Kent Bilgi Sistemi) 

OGC : Open Geospatial Consortium 

SDI : Spatial Data Infrastructure 

SQL : Structured Query Language 

TRKBIS :  Türkiye Urban Information System Standards  

  (Türkiye Kent Bilgi Sistemleri Standartları) 

TUCBS : Turkish National Geograpic Information System  

 (Türkiye Ulusal Cografi Bilgi Sistemi) 

TUREF : Projected coordinate system for Türkiye 

UML : Unified Modeling Language 

UTM : Universal Transverse Mercator 

WCS : Web Coverage Service  

WFS : Web Feature Service  

WMO : World Meteorological Organization 

WMS : Web Map Service 

XML : Extensible Markup Language 

 

 



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LIST OF TABLES 

Page 

Table 2. 1 : Geographical Data Themes .................................................................... 31 

Table 2. 2 : Sub-theme groups (category information). ............................................ 32 
Table 2. 3 : A GML instance document “exampleRoad.xml”. ................................. 45 
Table 3. 1 : Study data analysis. ................................................................................ 48 

Table 3. 2 : Study data attributes ............................................................................... 49 

Table 3. 3 : Assigned code values. ............................................................................ 54 
Table 3. 4 : HazardArea and RiskZone data sizes..................................................... 55 

  



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LIST OF FIGURES 

Page 

Figure 2. 1 : Vector Data Models. ............................................................................... 7 

Figure 2. 2 : Disaster Management Cycle. ................................................................ 17 
Figure 2. 3 : UML and ER diagrams. (Aydinoglu, 2009) ......................................... 24 
Figure 2. 4 : OGC geometry object model (OGC, 1999; Aydinoglu, 2009) ............ 25 
Figure 2. 5 : TUCBS standard hierarchy. (CBSGM, 2012a) .................................... 27 
Figure 2. 6 : TRKBIS Project work packages. .......................................................... 28 

Figure 2. 7 : Hierarchical structure for modeling Geographical data in Geographical 

data themes. .......................................................................................... 30 
Figure 2. 8 : UML Scheme of Natural Risk Zones. .................................................. 34 

Figure 2. 9 : UML Class Diagram: DogalRiskBolgeleri code lists. ......................... 37 
Figure 2. 10 : UML Relation Types - Association. ................................................... 40 
Figure 2. 11 : UML multiplicity indicators. (Ambler, 2002) .................................... 40 

Figure 2. 12 : UML Relation Types - Inheritance (Generalization). ........................ 41 
Figure 2. 13 : UML Relation Types – Aggregation. (Url-9)..................................... 41 
Figure 2. 14 : UML Relation Types – Composition. (Url-9) .................................... 42 

Figure 2. 15 : UML Relation Types – Association, Aggregation, and Composition. 

(Url-9) ................................................................................................... 42 

Figure 2. 16 : Hale Studio overview. ........................................................................ 46 
Figure 2. 17 : Goals of HUMBOLDT European projec ........................................... 46 
Figure 3. 1 : Location of Umraniye........................................................................... 47 

Figure 3. 2 : Source and target schemas overview. Hale studio. .............................. 50 

Figure 3. 3 : Definition of id target column from source schema in Hale Studio. .... 51 
Figure 3. 4 : Assigning of dogalTehlikeKategorisi code list in Hale Studio. ........... 51 
Figure 3. 5 : Transformation process mapping for erosion data. .............................. 52 
Figure 3. 6 : Reprojection of transformed data. ........................................................ 52 

Figure 3. 7 : Transformation process mapping for landslide data. ........................... 52 
Figure 3. 8 : Transformation process mapping for liquefaction data. ....................... 53 
Figure 3. 9 : Transformation process mapping for flood data. ................................. 53 
Figure 3. 10 : Transformation process mapping for overflowing data. .................... 53 
Figure 3. 11 : Transformation process mapping for risky parcels data..................... 53 

Figure 3. 12 : Transformation process mapping for risky buildings data. ................ 54 
Figure 3. 13 : The sizes of transformed data sets. ..................................................... 54 
Figure 3. 14 : Displaying of result TehlikeAlani data in QGIS desktop software. ... 56 
Figure 3. 15 : Adding data in Geoserver software for sharing. ................................. 57 

Figure 3. 16 : Displaying of result RiskBolgesi data in Geoserver as OpenLayers 

map. ....................................................................................................... 57 
Figure 3. 17 : Displaying of result WFS service in QGIS desktop. .......................... 57 

 

 

 

 

 



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UML MODELLING OF DIASTER MANAGEMENT DATA ACCORDING 

TO TUCBS DATA DEFINITION GUIDE: ISTANBUL EXAMPLE 

SUMMARY 

Various types of disaster occur worldwide and in Türkiye each year due to physical 

and human factors. In recent years, disasters have grown increasingly complex as a 

result of global climate change and human factors, whose mechanisms are difficult to 

understand. As a result, many lives and properties have been lost. Collaboration and 

coordination among institutions and organizations play a significant role in disaster 

mitigation. For institutions working on disasters to effectively intervene, they need to 

have adequate information and data. Coordination is the ability of all institutions to act 

in a coordinated manner. It is therefore possible to minimize the adverse effects of 

disasters in this manner. Disaster management studies are conducted by a number of 

institutions and organizations in Türkiye. 

Production, storage, and update of disaster data sets require the use of a standard 

methodology. Once data has been generated, it must be able to be utilized and shared 

correctly. Geographical data is used by a variety of institutions and organizations to 

meet the needs of these parties to the maximum of their abilities. Therefore, it is 

recommended that different institutions and organizations do not produce the same 

data repeatedly. 

Given that the risk zones geographical data are being used by more than one institution, 

these datasets should adhere to the same standards. 

During the development of Turkish National Geographical Information Systems 

(TUCBS) infrastructure standards, natural risk areas were examined within the scope 

of the thesis. These standards are being developed in accordance with ISO/TC211 

standards for the development of a geographical data model. They are also being 

developed according to those of the Open Geographical Information Consortium for 

the exchange of web services and geographical information. Data related to natural 

risk zones have been examined. Using the risk data of Istanbul province, Umraniye 

county, the data transformation process was carried out. Thus, it is possible to ensure 

compatibility with the TUCBS Natural Risk Zones data theme. 

 

 

  



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TUCBS VERİ TANIMLAMA KILAVUZUNA GÖRE AFET YÖNETİMİ 

VERİLERİNİN UML İLE MODELLENMESİ: İSTANBUL ÖRNEĞİ 

ÖZET 

Dünyada ve Türkiye'de her yıl fiziksel ve beşeri faktörler nedeniyle çeşitli türlerde 

afetler meydana gelmektedir. Afetler, küresel iklim değişikliği ve mekanizmaları, 

anlaşılması güç olan insan faktörleri nedeniyle giderek daha karmaşık hale 

gelmektedir. Bunun sonucunda çok sayıda can ve mal kaybı olmuştur. Kurum ve 

kuruluşlar arasındaki işbirliği ve koordinasyon, afetlerin azaltılmasında önemli rol 

oynamaktadır. Afetlerle ilgili çalışan kurumların etkin bir şekilde müdahale 

edebilmeleri için yeterli bilgi ve veriye sahip olmaları gerekmektedir. Koordinasyon, 

tüm kurumların koordineli bir şekilde hareket edebilmesidir. Dolayısıyla afetlerin 

olumsuz etkilerini bu şekilde en aza indirmek mümkündür. Afet yönetimi çalışmaları 

Türkiye'de birçok kurum ve kuruluş tarafından yürütülmektedir. 

Afet verilerinin üretilmesi, saklanması ve güncellenmesi için standart bir yöntem 

belirlenmelidir. Verilerin çeşitli çalışmalara katkıda bulunabilmesi için, 

oluşturulduktan sonra doğru bir şekilde kullanılabilmesi ve paylaşılabilmesi gerekir. 

Coğrafi veriler, çeşitli kurum ve kuruluşlar tarafından bu tarafların ihtiyaçlarını 

ellerinden geldiğince karşılamak amacıyla kullanılmaktadır. Bu nedenle farklı kurum 

ve kuruluşların aynı verileri tekrar tekrar üretmemeleri önerilir. 

Doğal afet coğrafi verilerinin birden fazla kurum tarafından kullanıldığı 

düşünüldüğünde, bu veri setlerinin aynı standartlara sahip olması gerekmektedir. 

Türkiye Ulusal Coğrafi Bilgi Sistemi (TUCBS) altyapısının tesisi ve coğrafi verinin 

ulusal düzeyde üretimi ile paylaşımına yönelik standartların belirlenmesi görevleri 

Çevre ve Şehircilik Bakanlığı bünyesinde Coğrafi Bilgi Sistemleri Genel 

Müdürlüğü'ne verilmiştir. Bu kapsamda Coğrafi Bilgi Sistemleri Genel Müdürlüğü 

tarafından 2013 yılında 10 adet ulusal coğrafi veri temasına ilişkin standartlar 

belirlenmiştir. Ancak bahsi geçen standartların zamanla değişen güncel ihtiyaçları 

karşılamamasından dolayı standartların güncellemesine ve genişletilmesine ihtiyaç 

duyulmuştur. Bu sebeple paydaş kamu kurumlarının katılımı ile 2018’de 

gerçekleştirilen toplantılarda önceden belirlenen standartlar güncellenmiştir. 

Coğrafi Bilgi Sistemleri Genel Müdürlüğü’nün standart belirleme çalışmaları 

kapsamında 2019 yılında 8 yeni veri teması için de veri tanımlama dokümanları 

hazırlanmıştır. 

OGC (OPEN Geospatial Consortium), açık web jeo-uzamsal standartları geliştirmek 

için çalışan birkaç şirket, devlet kurumu ve üniversiteden oluşan uluslararası bir 

konsorsiyumdur. OGC Standartları mekansal veri paylaşımını web tabanlı servisler 

üzerinden yapar. Karmaşık yöntemlerle üretilen ya da paylaşılan mekânsal veriler, 

herkes için kolay bir şekilde kullanılabilir. 



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OGC, ISO/TC211 komitesi ile paralel çalışmalar yürütmekte ve hazırlanan standartlar 

ile daha uygun çözümler sunmaktadır. Web Map servis, web haritalarını paylaşmak 

için bir OGC standartıdır. WMS sayesinde kullanıcılar, OGC uyumlu istemci 

uygulamaları aracılığıyla stilize edilmiş web haritalarına ulaşabilirler. Mekansal veri; 

Oracle Server, Microsoft SQL Server veya PostgreSQL Server gibi ilişkisel 

veritabanlarinda saklananabilmektedir. Böylece web servislerinde görüntülenmek 

üzere yayınlanabilmektedir. 

Web Feature Servis (WFS), mekansal verileri paylaşmak için bir OGC standartıdır. 

WMS'den farklı olarak, kullanıcılar ilişkisel veri tabanı sisteminde depolanan 

mekansal verilere OGC uyumlu istemci uygulaması üzerinden doğrudan erişebilirler. 

Bu nedenle WFS, mekansal verileri analiz etmek için daha uygundur. 

Web Coverage Servis (WCS), kapsama verilerini paylaşmak için bir OGC standartıdır. 

WFS'den farklı olarak, WCS jeo uzamsal raster veri paylaşım kurallarını açıklar. 

Özellikle uzaktan algılama verileri uydu imgeleri, orto rektifiyeli fotoğraflar gibi WCS 

de raster verileri analiz etmek için uygundur. 

GML, mekansal verileri depolamak için XML tabanlı bir OGC standartıdır. GML, özel 

xml uygulama şeması aracılığıyla konuma bağlı grafiksel ve grafiksel olmayan verileri 

depolayabilir. GML'nin faydaları, platformlar arası ve kolay anlaşılır dosya formatıdır. 

WFS gibi konum tabanlı web hizmetleri de mekansal verileri paylaşmak için GML 

formatını kullanır. 

Uzamsal verilerin oluşturulması, yönetilmesi, saklanması ve güncellenmesi için takip 

edilmesi gereken standart bir yöntem gereklidir. Verinin değerli olması, doğru 

kullanılmasına ve paylaşılabilir olmasına bağlıdır. Verilerin farklı kuruluşlarda farklı 

kullanıcılar tarafından kullanılması, optimum kullanıcı ihtiyaçlarını karşılaması ile 

ilgilidir. Aynı veriler farklı kuruluşlar tarafından tekrar tekrar oluşturuluyorsa verilerin 

çoğaltılması verilerin güncelliğini kaybetmesine neden olur. 

Tez kapsamında Türkiye Ulusal Coğrafi Bilgi Sistemleri (TUCBS) altyapı 

standartlarının geliştirilmesi sürecinde doğal risk alanları teması incelenmiştir. Bu 

standartlar, coğrafi veri modelinin geliştirilmesi için ISO/TC211 standartlarına uygun 

olarak geliştirilmektedir. Ayrıca, web hizmetleri ve coğrafi bilgi alışverişi için Açık 

Coğrafi Bilgi Konsorsiyumu'na göre geliştirilmektedirler. Doğal risk bölgeleri veri 

teması incelenmiştir. İstanbul ili Ümraniye ilçesi risk verileri kullanılarak veri 

dönüştürme işlemi gerçekleştirilmiştir. Böylece TUCBS Doğal Risk Bölgeleri veri 

teması ile uyumluluğun sağlanması mümkün olmuştur. 

Tezin uygulama bölümleri için TUCBS doğal risk bölgeleri veri standardı kullanılarak 

doğal afet verileri GML veri setlerine dönüştürülmüştür. Dönüşüm işlemi Hale Studio 

Masaüstü Yazilimi kullanılmıştır. Açık kaynaklı ETL aracı olan Hale studio ilk olarak 

2006 yılında HUMBOLDT Avrupa entegre projesi kapsamında geliştirilmiştir. Bu 

proje, mekansal verilerin ülkeler arası uyumlaştırılmasını kolaylaştırmaya ve 

desteklemeye odaklanmıştır.  Hale Studio kullanılarak Istanbul ile Ümraniye ilçesine 

ait olan heyelan, erozyon, taşkın, su baskını, sıvılaşma, riskli parsel ve riskli yapılar 

verileri ilk olarak incelenerek veri şemasina uyumlu olabilecek alanların tespiti 

yapılmıştır. Ardından TUCBS Doğal Risk Bölgeleri Veri Temasına uygun olacak 

şekilde transformasyon işlemi gerçekleştirilmiştir. Sonuç veriler GML formatında 

kaydedilmiştir. Üretilen veri setleri QGIS açık kaynaklı GIS yazılımı kullanılarak 

görüntülenmiştir. Sonuc veriler TehlikeAlani ve RiskliBolgeleri olarak iki farklı 

katmanda TUCBS veri temasına uygun olarak QGIS kullanılarak birleştirilerek 

PostgreSQL veri tabanına kaydedilmiştir. 



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Verilerin WMS ve WFS formatında yayınlanbilmesi icin Geoserver aracılıgı ile WMS 

ve WFS formatında paylasımı yapılmıstır. GeoServer, kullanıcıların jeo-uzamsal 

verileri paylaşmasına, işlemesine ve düzenlemesine olanak tanıyan, Java ile yazılmış 

açık kaynaklı bir sunucudur. Birlikte çalışabilirlik için tasarlanmıştir. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



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1 

1. INTRODUCTION 

Geographical Information Systems (GIS) is an information system in which 

geographical data and feature data can be integrated meaningfully in modeling the real 

world, providing decision support with spatial analysis, and presenting them to the 

user. The five essential components of GIS are software, hardware, people, methods, 

and data (Yomralıoğlu, 2000). Data is crucial for GIS. Because of that, the creation of 

geographical data with metadata and GIS standards is vital. Providing a standard and 

keeping updated on geographical data provide multiple usages of geographical data in 

different applications and services. The main of the interoperability of data is 

predetermined data creation standards and usage standards.  

The primary purposes of standardization; can be listed as preventing time and cost 

loss, ensuring effective use of information, preventing information loss, facilitating 

information transfer, and increasing quality. Standard development studies are carried 

out by many national or international organizations in the world (ISO/TC211, 2011; 

OGC,2013; CBSGM, 2012; Aydinoglu, 2009). 

Geographical Information constitutes approximately 80% of all Information and is 

considered adequate in 90% of decision-making mechanisms (Aydinoglu, 2009; 

Yomralıoğlu, 2000). Geographical Information has social importance because of its 

benefits to citizens and public and private sectors by providing the basis for country 

policies and decision-making mechanisms. For using data on local, regional, and 

national, international scales, Integration is essential to prevent loss of Information due 

to time and effort waste by contributing to decision-making in the use of geographical 

data. This approach has resulted in the concept of Geographical /Spatial Data 

Infrastructure that defines the interoperability of geographical data (Aydinoglu, 2009). 

The INSPIRE Directive was adopted and entered into force by the European 

Parliament. The relevant application rules can be accepted as a framework for 

establishing National Geographical / Spatial Data Infrastructures by member states for 

environmental activities (Url-1). 



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Since 2004, actions for establishing Turkish National GIS have been carried out for 

the interoperability of geographical data at the national level. Data standards for basic 

Geographical data themes are developed by the GIS General Directorate, established 

in 2011, and legal and technical components are determined for data sharing with GIS 

Portals in the web environment. 

GIS has an active role in disaster management studies. Accessibility to services is 

important for emergency activities during and after a disaster. Coordination of 

interoperability provides quick and cost-effective service delivery. (Tastan, 2021; 

Mutlu & Bank, 2011). One of INSPIRE' s 34 data themes was developed against 

natural hazards. 

The change in information technologies has increased the use of GIS in disaster 

management. Up-to-date Information is critical in disaster-emergency studies 

Obtaining up-to-date data and accessing dispersed Information quickly are essential 

for effective interventions after a disaster. For disaster management, timely access to 

the Information of critical resources is the most basic requirement. 

The production and use of data in a common standard will facilitate interoperability. 

In addition to simplifying the integrated management of data, allowing different 

institutions and organizations to utilize this data more easily, we will also be able to 

prevent the duplication of geographical data sets, produce them following national 

standards, and use them with open data services (Tastan, 2021; Erhan, 2013; Bilgin, 

2013). Therefore, institutions and organizations can conduct disaster risk studies more 

efficiently. Data can be transferred and manipulated more easily. 

1.1 Purpose of Thesis 

The geographical data controller needs to be able to coordinate interoperable 

approaches for open data change, as various institutions and organizations produce and 

manage geographical data. 

This thesis aims to develop a data model that can be applied to disaster data produced 

by different institutions and organizations under different structures and standards 

according to TUCBS natural risk zones data theme. 

 



3 

1.2  Method 

The aim is to develop a data model suitable for the natural risk zones data theme for 

the integrated management of disaster data produced by different institutions and 

organizations. 

The samples can be used in disaster management-related applications by transforming 

the data samples from the natural risk regions data theme into the defined data 

exchange format. 

It examines and illustrates the necessary transformation methods for converting data 

of different formats into the specified Geographical Markup Language (GML) format 

and storing them there. GML data production, use, updating, presentation, and sharing 

are examined and sampled using open data softwar



4 



5 

2. GENERAL INFORMATIONS 

2.1 Geographical Information Systems 

GIS (Geographical Information Systems) are computer systems for managing, 

creating, analyzing, and mapping various types of data. Location data and attribute 

data which describe location data are shown on a map via GIS. Thanks to this ability, 

a foundation is provided in science and nearly all industries for analyzing and mapping 

(Url-2). When considered the first word for Geographical Information System, 

geographic, refers to the known or calculated location of data from the point of 

Geographical coordinate; the second-word information refers that GIS data are 

arranged to profit useful knowledge; and the third word, systems, refer that GIS 

consists of various related and dependent components that have different functions. 

Storing the features of the location and the different data that arise due to these features 

in different map layers and the use of these layers in the decision-making processes 

has led to the emergence of GIS (Tastan, 2021). The design of GIS includes banding 

together spatial data into a unified database and coming from different sources and 

usually using diverse digital data structures. GIS has a series of data layers, and these 

layers explain spatially changing phenomena in a spatial register, which means 

overlapping accurately at all locations (Bonham-Carter et al., 1994). 

Because the GIS is a system that has a big role in mapping Geographical features on 

the Earth, GIS has a specific role in information systems. This role is becoming more 

important by developing technology. Dynamic maps using GIS data could become 

accessible with web technology and be published on web-based GIS (Web GIS). Also, 

new methods like big data, machine learning, and AI could be implemented into GIS 

data for developing spatial analysis and making predictions with GIS data. These kinds 

of developments increase the importance of GIS and create new usage areas for GIS. 

2.1.1 GIS components 

GIS has five components. These are Hardware, Software, Data, and Methods. 

Hardware consists of all kinds of computer internal and external hardware (Tastan, 



6 

2021). Software procures tools and functions for analyzing, storing, and displaying. 

There are both open and closed sources in GIS software. The third component, data, 

is the most important component. GIS data and related attributes data could be 

collected in-house or could be bought from a commercial data provider. People are 

also an important component because people play roles in the decision-making 

processes for real-life problems. They manage the system and develop plans. 

Achieving a successful GIS depends on the design of the plan and business rules. The 

business rules could be unique for each organization's purpose. 

2.1.2 Data models for GIS  

For visualization of Geographical features, the first process is to determine the way of 

the best representation of Geographical space (Bonham-Carter et al., 1994). Data 

models are a set of rules that explain relationships between data tables, indicate the 

ways for reaching records and detect frames for data explanations and data usage 

(Tastan, 2015; Cabuk et al., 2011). Raster data models and vector data models are two 

major data models.  

Raster data models: Raster data (Also known as cell-based data) is generally used for 

the definition of Geographical presence, which has continuous features (Ates, 2010). 

Each cell is known as a pixel, and each layer of grid cells records a separate attribute. 

The size of the cells is constant, and the shape of the cells is generally square. The 

rows and columns are used for stating the locations of cells (Bonham-Carter et al., 4 

1994). The spatial resolution of the raster model is determined by the area covered by 

each pixel. Square pixels can be measured by measuring one of their sides to determine 

their resolution. The 10m spatial resolution in a raster model refers to pixels 

representing 10 m by 10 m in the real world. (Bonham-Carter et al., 1994). 

Vector data models: There are three types of vector data types which are points, lines, 

and polygons. These vector data models are stored by coding (x, y) coordinates values. 

Only one (x, y) coordinate value is stored for point features, while the (x, y) coordinate 

series value is stored for line features. Polygon features are stored as closed features 

as initial and final points have the same (x, y) coordinate. Points are zero-dimensional 

features that generally present district features like buildings, center points, sample 

points, etc. Lines are one-dimensional features that are a combination of explicit and 

more than one-point features that present linear features like roads, rivers, streams, etc. 



7 

Polygons are two-dimensional features that combinations of multiple lines and 

polygons generally present closed features like city boundaries, lakes, etc. 

 

Figure 2. 1 : Vector Data Models. 

2.1.3 GIS process 

There are six main GIS processes in GIS. There are Data Capture, Data Manipulation, 

Data Management, Querying & Analyze, and Presentation Data. 

2.1.3.1 Data capture 

Manual digitization and scanning are two basic methods of digitization which GIS data 

are generally obtained from. Digitization of photography, digital datasets and paper 

maps, GPS, remote sensing, and satellite imagery data are input sources of GIS. 

2.1.3.2 Data manipulation 

Data manipulation is a necessary process for making GIS projects or GIS data suitable 

for users' systems. Although temporary transformation could be for displaying, 

permanent transformations are necessary for analysis. 



8 

2.1.3.3 Data management 

According to the GIS project size, storage methods may change. Storing as a simple 

file could be adequate for small GIS Projects. But, when data volume and user number 

increase, using a database management system (DBMS) is the best way to store, 

organize and manage data. The relational design of DBMS is the most useful design 

for GIS because of its flexibility and wide deployment in applications. The flexibility 

of the software and its wide deployment within and outside GIS make it an ideal 

solution for a variety of applications. 

2.1.3.4 Query & analyze 

Basic queries such as distances between two locations and analytical questions like 

traffic control by ring roads could be done when Geographical data is entered into GIS. 

Also, results could be taken a few times. It is important for managers and analysts to 

be able to access timely information using GIS, which provides them with both simple 

point-and-click query capabilities and sophisticated analysis tools. Proximity and 

Overlay Analyses are the two most important analytic tools of GIS (Url-2).  Proximity 

analysis is used to determine the proximity between features. Buffering method is used 

for this analysis. Overlay analysis is the combination of different data layers. It could 

be used for visualization for the simplest purpose. Physical join of one or more data is 

required for analytical operations. 

2.1.3.5 Visualization 

The aim of using visualization is to increase complexity and highlight the main 

purpose of information by using the key features. Thanks to visualization, the complex 

process could be clearer, and deciding could be easier. Maps, 2D-3D models, 

simulations, graphs, and other cartographic products are visualization tools that are 

presented in GIS. 

2.2 Disaster and Disaster Management 

2.2.1 Disaster 

There are many definitions of disaster in the literature. It is defined as "a natural or 

human-induced phenomenon affecting humans and other living things that disrupt 

normal life and social activities, causes physical, social, cultural, and economic losses 



9 

to society, and cannot be overcome by the affected community" (Gundogdu & Ozcep, 

2003). Also, it can be expressed as insufficient resources in the intervention. In this 

definition, the prerequisite is that the affected community cannot cope independently. 

It is incorrect to consider every earthquake and fire a disaster. For example, the tsunami 

claimed to have occurred in the August 17 Earthquake cannot be considered a disaster. 

However, on December 26, 2004, the 9-magnitude earthquake and the tsunami that 

occurred off the Indonesian island of Sumatra caused the death of more than 230 

thousand people in more than ten countries, 168 thousand of which were in Indonesia, 

and became one of the biggest disasters in the last century. 

Again, the tsunami caused by the 8.3-magnitude earthquake on the Indonesian island 

of Sumatra did not create a disaster effect. When evaluating its dimensions, it is 

important to consider how the disaster impacts society in its natural cycle. The 

scientific development in all studies on this subject is in parallel with the disaster 

culture of society. 

Societies' view of disasters until recently XIX. It was viewed similarly to diseases at 

the beginning of the century as "an unforeseen, unwanted, and unavoidable risk of 

daily living. With increased social development, scientific progress, and the 

importance given to human life, society's view of disasters has begun to change. It has 

been understood that disasters can be prevented or overcome with minor damage if 

necessary, and precautions are taken beforehand. 

2.2.1.1 Factor causing disaster 

Disaster is the result of an event rather than itself (Ergunay, 2002). Considering the 

consequences of disasters; first, it is seen that they cause loss of life and property. Loss 

of life is death of people and animals, loss of property is damage to property, buildings, 

and agricultural areas. While some losses may occur directly with the disaster, others 

may occur after a certain period. For example, loss of life and property occurs during 

floods. However, after the flood, the debris, sand, and mud brought by the floods can 

also cause indirect and long-term damages by rendering agricultural lands 

unproductive. 

The reason that the disaster phenomenon increasingly occupies the agenda of the 

country, and the world is that there was an increase of 35% in the number of disaster 



10 

events that occurred in the world between 1991 and 1993, announced by the United 

Nations Humanitarian Relations Department. 

2.2.1.2 Disaster types 

Disaster types can best be described as follows: 

2.2.1.2.1 Natural disasters 

These are disasters that are based on natural events. These are examined in two groups, 

geological and meteorological: 

Disasters of geological origin: These are natural disasters that take their source 

directly from the earth's crust or depths. For example, earthquakes, landslides, erosion, 

volcanic eruptions (Volcanoes), mud flood, and rockfall. 

Meteorological origins: They occur because of natural events in the atmosphere. 

These occur when atmospheric events (temperature, precipitation, pressure, and wind) 

exceed the limit of what is beneficial to man. The main factors preparing the formation 

of meteorological disasters originate in the atmosphere, but the characteristics of the 

place where the disaster occurs are also important. Flood, drought, mass movements, 

avalanche, storm, hurricane, tornado, blizzard, hail, extreme cold, storm, forest fire, 

global climate changes, lightning strike, greenhouse effect, frost, fog and excessive 

rain can be given as examples. 

2.2.1.2.2 Unnatural disasters 

Occurrences are man-made disasters. For example, wars and civil wars, some forest 

fires, fires in residential areas, hazardous material accidents, nuclear accidents, air 

pollution, water pollution, soil erosion and epidemics, armed attack, riots, terrorism, 

and displacement of people and becoming refugees. Other events that cause it include 

fires, epidemics, diseases caused by water and food, infectious diseases, cholera, 

malaria, etc. 

2.2.1.2.3 Complex disasters 

They are both man-made and natural disasters. For example, forest fires and fires after 

earthquakes. Fires fall into all three groups listed above. Some disasters also bring with 

them disasters called secondary disasters. For example, earthquakes, tsunamis, 

landslides, epidemics, and fires cause a striking example in this regard.  



11 

Types of disasters are also considered dangerous and classified according to their 

process and nature.  

- Sudden hazards (geological and meteorological hazards): earthquakes, tsunamis, 

floods, volcanic eruptions,  

- Slow emerging hazards (environmental hazards): drought, hunger, environmental 

degradation, desertification, etc.,  

- Industrial/technological hazards: System collapses, accidents, radiation, etc. 

Types of disasters observed in the world. 

Geological Disasters: Earthquake, rockfall, volcanic eruptions, mudflows, tsunami 

Climatic Disasters: Heat waves, cold waves, drought, hail, tornado, lightning, 

hurricane, typhoons, floods, cyclones, tornados, avalanches, heavy snow, rains, acid 

rains, fog, icing, weather pollution, forest fires 

Biological Disasters: Erosion, forest fires, epidemics, insect infestation,  

Social disasters: Fires, wars, terrorist attacks, migrations, 

Technological disasters: Mining accidents, biological, nuclear, chemical weapons 

and accidents, industrial accidents, and transportation accidents (Url-3). 

If it is accepted that there are approximately 52 types of disasters worldwide, it can be 

assumed that approximately 21 occurred in Türkiye. It is seen that meteorological 

disasters form 28 types of thirty-one natural disasters. Natural disaster’s types and 

order of importance also vary from country to country. For example, natural disasters 

in the Mediterranean region are drought, floods, forest fires, landslides, hailstorms, 

avalanches, and frosts. Türkiye's most common meteorological natural disasters are 

hail, floods, frost, forest fires, drought, heavy rain, strong wind, lightning, avalanche, 

snow, and storms.  

According to the World Meteorological Organization (WMO), 700,000 people lost 

their lives due to meteorological disasters in the 1980’s alone (Url-4). In general, 

terms, when we look at the rates of disasters in our country, earthquake comes first at 

61%, followed by landslides at 15% and floods at 14%. Earthquakes and floods have 

taken the top two spots in the last ten years based on historical data. 



12 

According to the Turkish Criminal Code, 1959, 7269/ 1 Disaster Law, the order of 

importance of disasters in Türkiye is:  

 earthquake,  

 fire,  

 flood,  

 landslide,  

 rockfall,  

 avalanche,  

 drought. (İsik et al., 2013) 

The analysis of natural disasters occurring between 1980 and 2017 indicates that an 

average of six to 25 people per million died in natural disasters during this period.  

In terms of the number of major earthquakes since 1900, Türkiye ranks fourth. As 

compared to other types of disaster, earthquakes cause the greatest number of deaths 

and property damage. A significant percentage (60%) of disaster-related deaths are 

caused by earthquakes. Based on statistical evaluations of the earthquakes that have 

occurred in Türkiye to date, it appears that a major earthquake with extensive damage 

occurs once every five years, on average. The number of people who die and are 

injured each year is reported to be approximately 1,000. Additionally, earthquakes 

cause more than 7,000 buildings to be destroyed or severely damaged each year (Url-

5). 

All these data confront us with the reality of developing mitigation strategies before 

the disaster and producing a radical policy within a sustainable development 

framework.  

2.2.2 Disaster management 

There is a need for structuring management organizations in accordance with the 

environmental characteristics of disaster events, which require societies to be prepared 

in an organized manner. Every human community engages in management activities 

to achieve a common goal (İsik et al., 2013; Simsek, 1996). 



13 

"Disaster Management" emerged in response to this need and aims to coordinate and 

manage the activities that need to be carried out during disaster phases (Sarp, 1999).  

This concept envisages not ignoring or eliminating disasters but managing them with 

the acceptance of their existence, reducing and controlling their harmful effects. 

Disaster management, in a broader sense, is a broad concept that requires planning, 

directing, and coordination of the works to be done in the prevention of disasters or 

reduction of damages, mitigation, preparation, rescue and first aid, improvement, and 

reconstruction of a disaster event. In order for this to be feasible, all institutions and 

organizations must use their resources for this common purpose. In summary, it is an 

effort to overcome extraordinary situations that lead to disasters. 

As a brief definition, disaster management includes coordinating and managing the 

activities that need to be carried out during the disaster phase. Furthermore, it entails 

the development and implementation of long-term and comprehensive policies as well 

as the development and implementation of preparedness strategies in disaster-

hazardous regions in the pre-disaster period and the conduct of risk reduction studies 

to prevent or reduce disaster impacts. Management of disasters involves rescue efforts 

after an earthquake, hurricane, or another natural disaster; in the longer term, it 

involves managing the reorganization of social systems and individual lives resulting 

from that disaster. 

In disaster-prone areas, disaster management covers the development and 

implementation of preparedness strategies against a possible disaster, along with the 

development of long-term, comprehensive policies concerning risk reduction studies 

that will be conducted for the prevention or reduction of disaster effects, as well as the 

management of implementation studies (Schramm & Newman, 1997). 

Disaster management is defined as, "A way of preventing disasters and reducing 

damages. "Being prepared for disasters, providing fast and effective rescue, first aid, 

temporary shelter, and reconstruction during disasters, society's resources (manpower, 

material, equipment, and money) need to be guided and used rationally before and 

after a disaster. According to a UNDP/UNDRO Disaster Management Handbook 

published in 1991, disaster management encompasses: 

 Planning and executing measures to reduce the likelihood of disasters by reducing 

the negative effects of possible disasters and considering the economic aspect. 



14 

 Making warning-preparation arrangements against the immediate threat of 

disaster, arranging effective emergency measures in case of alarm or warning 

periods and dire consequences of disaster impact. 

 Determine the situation of the region and the people living there in the event of 

collapse, floods, famine, and "slow progress" disasters, and promptly implement 

solutions and measures. 

 Implementation of emergency relief efforts for (immediately) lifesaving 

immediately after the disaster, 

 Accelerating rehabilitation measures that will accelerate recovery and promote 

continuous post-disaster development. In line with the definitions above, the first 

point to be noted regarding "disaster management" is that disaster management, 

which has a vast scope, does not concern only one sector or administrative unit. A 

holistic approach to disasters and disaster management should be exhibited on a 

sectoral and organizational basis (Ergunay 2002, İsik et al., 2013). 

Disaster management also requires qualified personnel with expertise in a variety of 

disciplines. Regarding disaster mitigation, seismology, hydrology, and meteorology 

come together with wind and earthquake engineering. Furthermore, health experts and 

policy development managers play a crucial role in developing strategies to protect 

society from the socioeconomic and medical effects of disasters. In 1990, disaster 

management practices should consider the following five points. Specifically, the 

following points are in question: 

 Management of disasters is generally not limited to a particular region where 

disasters occur. 

 Because most disasters today are caused by natural causes, disaster management 

should be handled together with environmental problems. These problems are 

attracting global attention now. 

 Before developing disaster mitigation strategies at the national, regional, and local 

levels, it is important to determine which areas will be affected by which disasters, 

and why. 

 The state should apply economic efficiency, economic incentives, and free market 

forces for the health, protection, and welfare of society. 



15 

 Development policies and strategies that contribute to an increase in disaster 

damage should be changed (Bender, 1992). 

As part of the "International 10 Years of Reducing the Damages of Natural Disasters", 

a United Nations organization established in the 1990s to work on natural disaster 

prevention, the Scientific and Technical Committee promotes disaster prevention, 

disaster preparedness, mitigation of disaster damages, and a culture of global 

prevention. Effective disaster management is essential for the realization of the 2000 

strategy, which can be summarized as "development and development". Managing 

disasters is primarily concerned with the rescue of people, the restoration of normal 

living conditions, and the salvaging of damaged property. Achieving this goal requires 

knowledge, experience, planning, and coordination. Comprehensive disaster 

management aims to achieve the following objectives: 

1. By taking the necessary technical, administrative, and legal measures before the 

event, society will be able to deal with the disaster with only minor damage and 

losses. 

2. In cases where measures cannot be taken, the most appropriate intervention studies 

should be carried out. 

3. Incorporating mitigation efforts into all stages of development. 

4. Assuring that every segment of society has access to the necessary information and 

education. 

The design of processes for the most efficient use of resources can be highly beneficial 

to the mitigation and preparedness for disasters. As a result of considering the ability 

to cope with disasters or minimize damage, it is concluded that disaster resources are 

insufficient. Risk analysis and resource development studies can help reduce damages 

before a disaster occurs. Management of resources by considering risk is the essence 

of Disaster Management. Realizing this situation is possible with an organization that 

can coordinate all institutions and organizations that have completed their institutional 

restructuring. To accomplish this, an event command center is established within an 

information system that is capable of utilizing resources efficiently. This organization 

is known as Disaster Management. It is much more devastating when a disaster that 

occurred previously occurs today with the same severity. This can be attributed to three 

main factors: the expansion of the area covered by settlements that are at risk of natural 



16 

disasters, the increase in population density in these settlements, and the difficulty of 

controlling them. When disaster management is examined in different countries, it is 

found that it is structured according to the country's social, geographical, economic, 

and political conditions. Modern disaster management prioritizes a high level of 

mitigation and prevention. All public institutions and organizations participate actively 

in the development of this structure. 

Effective disaster management requires, analizing disaster risks, taking measures to 

minimize damage, determining the procedures to follow during disasters, and 

implementing these measures promptly. 

Keeping this objective in mind should guide the management of all institutions and 

resources of society. 

2.2.2.1 Phases of disaster management and the disaster cycle 

Disaster management system: It consists of two separate management systems that 

are complementary to one another. 

a) Loss Mitigation (Risk) Management, 

b) Emergency (Crisis) Management. Regardless of their origins and pace of 

development, all disaster-related activities are divided into the following four main 

stages: 

a. Mitigation, 

b. Preparedness, 

c. Response to the incident. 

d. Remediation. 

As part of the Disaster Management process, a cycle begins with mitigation and 

preparedness and continues with response, recovery, and reconstruction following a 

disaster. This cycle should include hazard identification, disaster prevention, 

mitigation, reinforcement, rehabilitation preparation, education, early warning, 

support, and emergency planning. Figure 2.2 illustrates the disaster cycle. 



17 

 

Figure 2. 2 : Disaster Management Cycle. 

The first two stages cover the activities before the disaster, and the other two include 

the activities during and after the disaster. The activities that need to be done at these 

stages are not independent of each other, they are intertwined and must follow each 

other, and the effectiveness of the work done in the previous stage is the activities that 

significantly affect the success and efficiency of the work in the next stage and should 

show continuity. 

The concepts to be understood before the disaster can be given as follows: 

Hazard: Everything that has the potential to cause loss of life and property, as well as 

to damage the socioeconomic order and activities, 

Risk: The estimated adverse effect of a hazard on residents, properties, activities, 

unique facilities, or structures of the area. 

Risk Management = mitigation + preparedness 

Risk = Risk Estimation x Sensitivity 

Crisis Management (Fix) = Hazard, Risk 

Vulnerability: This concept can be defined as the relative lack of the power of an 

individual or society to predict the effects of a disaster, fight against it, and even resist 

them. The leading factors that increase people's vulnerability in case of disasters are 

rapid urbanization, population growth, lack of building control, and lack of disaster 

information and awareness (Koç & Thieken, 2017). 

Briefly, in societies that cannot predict and take precautions about the hazards and 

effects of disasters in natural events, natural events appear as a disaster risk that can 

lead to loss of life and property (Rattien, 1990). 



18 

2.3 GIS and Disaster Management 

2.3.1 Development of GIS 

Technology contributes to the development of Geographical Information Systems 

(GIS) on the one hand and their widespread application in a variety of disciplines on 

the other. In general, GIS can be defined in two ways: in terms of technology, GIS is 

a tool that collects, stores, processes, transforms, and displays real-world spatial data. 

From a theoretical and institutional perspective, GIS is a decision-support system that 

interacts with spatial data.  

Combined with both definitions, GIS can be viewed as a digital information system 

that provides decision support. In essence, it collects, stores, processes, and displays 

spatial data in accordance with the needs of the institution with which it is affiliated. 

Each group constitutes a GIS organization based on its functions. Screen maps or 

printed (analog) maps are the main output formats of GIS or digital image processing 

systems.  

Geographical Information Systems differ from other information systems in terms of 

the types of data they contain and how these data are characterized. This type of data 

has the characteristic of allowing the location of objects or events (phenomena) on 

earth to be determined. The purpose of a map is to visualize the location of objects or 

events in relation to one another (Ulugtekin & Dogru). 

To resolve location-related problems, maps are used as visual communication tools. 

Many GIS users have questions regarding the environment or the nature of a particular 

object. Answering these questions poses the question of what type and scale of map to 

use. 

In general, GIS maps can be categorized under the following headings: 

- Cadastral maps 

- Service maps (gas, water, wastewater, electricity, telephone, cable broadcast, etc.) 

- Socio-economic maps (maps derived from statistics on population, infrastructure, 

settlement, job distribution, education, agriculture, etc.) 

- Environmental maps (vegetation, soil, hydrology, geology, forest, etc.) 



19 

- Other maps (maps associated with the use or especially the misuse of resources 

such as water pollution, air, and soil pollution) 

Cadastral and service maps are generally large-scale. Small-scale maps are generally 

used in geospatial analysis. When working with spatial data in a GIS environment, 

"What?, Where?, When?" Three basic types of inquiries are encountered, such as: 

- The spatial comparison is the comparison of features across different regions in the 

same spatial scale. 

- Thematic comparison refers to mapping issues for the same region at the same 

scale and comparing the spatial distribution of similar or different issues. 

- In temporal comparison studies, the same subject changes in the same scale and 

region over time (Ulugtekin & Dogru). 

Prior to the advent of GIS, paper maps and statistics were the most effective tools for 

researchers working with spatial data. For the analysis and use of these paper maps, 

analytical and map-using techniques have been developed. Several of these techniques 

are also included in GIS packages. Researchers use compelling databases, spreadsheet 

software, and graphical tools in their research today. This convenience allows the user 

to access the map data more easily and reduces the processing load. 

GIS is used to support decision-making, and decisions are related to geographical 

objects. It is the goal of GIS to ensure that employees are capable of analyzing and 

interpreting data correctly. The majority of GIS practitioners are evasive at this point. 

Among the goals of GIS is to assist users in making accurate and timely decisions. For 

accurate decision-making, data quality becomes increasingly imperative. In terms of 

integrating data sets, GIS can provide very successful results. Data acquisition dates, 

spatial resolution degrees, and differences between concepts become apparent to GIS 

users.  

2.3.2 GIS and disaster management 

People have migrated significantly from rural areas to metropolitan cities due to rapid 

population growth and economic problems experienced throughout the world. As a 

result of unplanned and irregular urbanization along with these migrations, regions 

that are unprepared for disasters may suffer severe losses in terms of life and property. 



20 

As stated in the book Disaster Management, Expecting the Unexpected, Managing the 

Worst, "it is impossible to reduce environmental problems and achieve sustainable 

development without considering disasters. Sustainable development requires 

reducing disaster risks. Investments that are not made in disaster management 

programs result in post-disaster losses. As a result, identifying, evaluating, and 

managing risks in addition to conducting hazard and damage analyses are integral parts 

of sustainable development." It is critical to be prepared for disasters as a foundation 

for sustainable development (Tasdemir, 2020). 

It is significant to understand that disaster management involves multidimensional 

research and evaluation of a wide range of data simultaneously. In scientific research 

on disasters and in disaster management planning, it is necessary to analyze a wide 

variety of data simultaneously, taking into account the relationships between them. 

The use of Geographical Information Systems has become a very important tool in 

disaster management, as they address all these needs and allow multi-dimensional 

spatial analyses of data of all kinds. 

Geographical information systems refer to the methods of transferring all kinds of data 

relating to the earth to a computer environment. It is possible to store, classify, 

compare, analyze, update, and visualize these data via maps, graphics, and tables using 

these systems. 

In the first half of the 19th century, GIS was first used for the analysis of post-disaster 

damage. It was not until the beginning of the 20th century that GIS was conceptually 

defined. The Canadian GIS project was developed by Roger Tomlinson in 1963. The 

purpose of this project was to calculate the characteristics of the national lands of 

Canada. 

By combining spatial and non-spatial data and ensuring that spatial and non-spatial 

data are evaluated together, Geographical Information Systems have been used for 

epidemic mapping since 1832, conceptualized in 1963, and translated into a project 

affecting countries across the globe to optimize land use. Therefore, using GIS in 

disasters, as in other areas, would ensure that the right decisions are made and that one 

could escape the disaster with the least damage (Tasdemir, 2020). 

There is no doubt that preparing for and responding to disasters is as significant as 

responding during and after them. Both stages are integral to the overall process. GIS 



21 

is one of the most effective tools for determining what needs to be done and how it 

needs to be done. By using GIS, we are able to monitor disasters, develop disaster risk 

maps, develop early warning systems, prepare various disaster scenarios, develop 

emergency support plans, develop alternative evacuation and transportation plans in 

the event of a potential disaster, plan open spaces, protect recreational areas and plan 

for public safety. 

2.4 GIS Standards 

2.4.1 INSPIRE 

A directive called INSPIRE (Infrastructure for Spatial Information in the European 

Community), which was approved and published by the European Union Parliament 

on July 23, 2004, established a legal framework for GIS activities within the European 

Union. All Union member states are obligated to comply with the technical and 

administrative requirements of the INSPIRE DIRECTIVE (Directive of the European 

Parliament and the Council - INSPIRE). It is the objective of the INSPIRE project to 

enable European users to access CURRENT geographical information in REAL 

TIME. There are four main steps to accomplish this objective. 

Documenting the geographical data sets in European Union countries and developing 

the tools required to access them are the first steps. 

 The second stage involves harmonizing data sets accessed from different sources into 

a standard system and making them available. During the third stage, existing data sets 

are integrated by developing standard geographical data models for geographical 

objects (for example, transportation, forests, etc.). The fourth and final stage is to 

provide services that allow the integration of geographical data sets on a national and 

local level, with various levels (scales) and sources, into a continuous geographical 

database based on common standards and protocols (Url-6). 

2.4.2 Turkish National Geographical Information System (TUCBS) 

It is a geographical information system that can be integrated into the Turkish National 

Geographical Information System. TUCBS is local, regional, and national 

geographical information systems that can share data over computer networks and be 



22 

accessed by everyone, including ordinary citizens. TUCBS is also defined as a network 

of data and service providers enabling the joint use of geographical data and services. 

The term "service" refers to the collection, storage, processing, analysis, presentation, 

and sharing of geographical data. With the data and services provided by TUCBS, 

users will be able to model and implement their applications. 

 TUCBS is open to all relevant public and private sector organizations, local 

governments, universities, and other organizations at the country level. 

2.4.3 OGC (Open Geospatial Consortium) 

OGC carries out studies parallel with the ISO/TC211 committee and offers more 

relevant solutions with the prepared standards. OGC, recognized as the GIS industry 

association, consists of member organizations and companies working to ensure and 

improve the interoperability of Geographical information technologies.  

OGC's vision is to create a network, application, or platform that can benefit anyone 

who uses or needs Geographical information. Its mission is to make the relevant 

interface and technical standards available to all users. 

OGC continues its multi-faceted efforts to create web services. As a result of these 

studies, standards based on web service logic have been prepared. In order (OGC, 

2003, 2006).  

- Web Map Service (WMS): It transmits data with coordinate information to the 

client as images or maps. It is an application standard published as ISO 19128 

standard. 

- Web Feature Service (WFS): It is a service that allows sending vector data kept in 

different formats on servers to the client in GML format. Vector includes data 

access, new data creation, query, straightforward analysis, data deletion, and data 

update features. 

- Web Coverage Service (WCS): Provides raster data with its features and allows 

complex queries corresponding to this data. It differs from WFS and WMS in this 

approach. 



23 

- Catalog for the Web (CS/W): Searching, finding, accessing, etc., Geographical 

data from Internet-based metadata catalogs. Transactions can be performed with 

catalog services. 

- Coordinate Transformation Service (CRS): Provides a standard way to define and 

transform coordinate systems. 

2.5 Databases 

2.5.1 Database model 

The database is the storage of related data allowing multi-purpose use and without 

duplication. A database management system interacts with end users, applications, and 

databases for analyzing and capturing data and is defined as software (Url-7). The 

database model includes the rules and tools for database design and the production of 

result enforcement standards. The complicated problems are solved by using database 

models. Real-world problems are transformed into more fundamental and manageable 

problems. As geodatabase models have evolved, this concept has been defined as 

"entity" in a relational database and "object" in object-oriented database models 

(Aydinoglu, 2009). 

Database Modeling provides methods and tools for a high-level description of the real 

world. Database designer, using the required dictionary and schema rules to generate 

the database model. In this sense, the high-level definition provides an approach 

everyone can perceive in the real world. 

An event refers to the use of an object in the database at a specified time. Database 

models and schemas are static and time-independent because they express objects by 

structure and repetition of use. 

The Conceptual Database Model is a function that abstracts real-world entities' 

properties and characteristics depending on the database's purpose. The Conceptual 

Scheme describes the properties of the database independent of computer software and 

hardware requirements. Information is stored in the database, and its attribute and 

relations can be determined with Entity Relationships and Class diagrams.  

The Logical Database Model defines the details defined in the conceptual database 

model with schemas in data structures according to the application. The relational 



24 

database schema of the conceptual database design produced with UML diagrams is 

defined in Figure 2.3. 

 

Figure 2. 3 : UML and ER diagrams (Aydinoglu, 2009). 

The physical Database Model is a more complex and technical process as it requires 

the suitability of the database to the software and hardware in which it is used. With 

the detail catalogs produced in this context, the name, geometry, attributes, type, 

relations, etc. of the detailed class. Information can be identified. 

2.5.2 Geographical databases 

A geodatabase or geographical database is a relational database for storing 

Geographical data. Geographical Databases are the foundation of GIS and are 

generally classified according to the database model. Geometry and attribute data 

related to geometry are stored in geodatabases. 

The concept of geometry has been modified with the publication of the OGC Simple 

Feature Specification for SQL (Aydinoglu, 2009). OGC has proposed the "Geometry 

Object 40 Model" in Figure 2.4, which allows for details to be presented in databases. 

In this model, geometry types are defined in a specific hierarchy, and details are 

presented as a "feature" with at least one attribute in a geometry type. The basic 

geometry class consists of 4 subclasses: Point, Line (Curve), Area (Surface), and 

Geometry Collection (Aydinoglu, 2009). Geographical features have a coordinate 

system, geometries have the same attributes as layer or feature classes and are stored 

in the same tables. 

ER DIAGRAM 
UML DIAGRAM 



25 

 

Figure 2. 4 : OGC geometry object model (OGC, 1999; Aydinoglu, 2009). 

2.6 Development of TUCBS 

Due to the widespread use of computers and information technologies, the volume of 

digital data produced by different institutions, organizations, and companies has 

increased over time. There are several reasons for this development, including: 

 Establishing a standard format for data produced by different institutions on similar 

topics. 

 Identify the principles that will ensure the sharing and use of data produced by 

different organizations by making the necessary legal and organizational 

arrangements. These principles will be under the authority and responsibility of 

different organizations. 

 In the case of data produced by different institutions or obtained on the same 

subject, determine the responsibility areas of each institution. 

 To prevent the waste of time, personnel, and resources caused by the reproduction 

of data obtained, etc., coordination and other mechanisms should be developed. 

Geographical information systems play an integral role in providing the ability to 

combine or use the data produced by multiple organizations. 

Several projects have been conducted to determine the standards for the production 

and sharing of digital geographical information by providing a common standard. This 



26 

has led to interinstitutional coordination of geographical information produced within 

the authority and responsibilities of public institutions and organizations by providing 

a common standard. 

Study on the establishment of Geographical Information Systems Standards in which 

other institutions participated, coordinated by TÜBİTAK and HGK. 

Under the coordination of the Prime Minister and the HGK, these studies can be 

categorized as Inter-Institutional Coordination. 

At the Coordination of GIS Establishment Studies Symposium and Panel held on 

February 4, 1999, the "Turkish National Geographical Information System (TUCBS) 

Policy and Strategy Principles Draft" document was prepared. 

This draft describes the principles for the production, revision, and exchange of 

geographical information by public institutions and organizations according to areas 

of responsibility, according to authorities, and responsibilities to be determined by 

cooperation between institutions. 

TUCBS has been accelerated through the General Directorate of GIS, which was 

established in 2011 under the Ministry of Environment and Urbanization. With the 

concept of Geographical/Spatial Data Infrastructure (SDI) which is expressed around 

the world, TUCBS data standards are created, approaches for interoperability of 

geographical data and systems from local to national level on a service-based basis, 

and TUCBS portal are developed. 

Through the Conceptual Data Model Components, rules are determined to create data 

standards that can be used from national to local levels and are interoperable. 

Establishing the conceptual data model components of data themes based on the 

principles of the ISO/TC211 Geographical Information Technical Committee, the 

Open Geographical Information Consortium, and other internationally accepted 

initiatives such as INSPIRE. 

TUCBS is a common data model that contains standard data sets that different sectors 

are required to share. It is necessary for TUCBS geographical data models to be 

compatible for this purpose. It is therefore essential that interoperability be ensured 

with applications in various sectors, such as the TUCBS primary data standards and 

the TRKBIS standard (Yomralıoğlu & Aydınoğlu, 2014). 



27 

 

Figure 2. 5 : TUCBS standard hierarchy (CBSGM, 2012a). 

Within the scope of the project for the development of TRKBIS standards, analyses 

consisting of 8 work packages were conducted in 2012. The data requirement defined 

in legislation and works related to the Legislation Analysis (IP.1) has been determined. 

In the selected sample municipalities, the current situation analysis was made with 

Institutional Analysis (IP.2), and the process analysis, data requirement analysis, and 

current data analysis of the identified works related to urban information systems were 

made with Data Requirements Analysis (IP.3). With the Analysis of International 

Standards (IP.4), approaches that can be taken as examples from the world have been 

determined. Based on all these analysis results, the TUCBS-compliant TRKBISS 

Conceptual Model Components (IP.5), Data Standards Determination (IP.6), and Data 

Exchange Format Development (IP.7) work packages were completed. In addition, a 

Draft of Administrative and Financial Legislation (IP.8) has been prepared (CBSGM, 

2014). 

 

DATA EXCHANGE 

International Standard 

National Standard 

Sector Standard 

Institutional Standard 



28 

 

Figure 2. 6 : TRKBIS Project work packages. 

In 2014, draft data and schema documents and 1.1 version documents of TUCBS were 

shared openly with users on the General Directorate of GIS website. The TUCBS 

Portal was opened to users in 2020 under the name Atlas. Atlas Portal is a modular 

portal designed to provide users with the data they produce or update in public 

institutions and organizations that produce geographical data. The data is created 

according to the Open GIS Consortium (OGC) standards, which set GIS standards 

worldwide (CBS General Directorate, 2020). 

In 2019, Presidential Decree No. 49 on Geographical Information Systems was 

published in the T.C. Resmî Gazete. No. 30941. By establishing the Turkish 

Geographical Information System Board, the Turkish Geographical Information 

System Executive Board, and the Turkish Geographical Information System Working 

Committee, it will ensure coordination of public institutions and organizations as well 

as provide principles and standards for the production, updating, management, access, 

security, sharing, distribution, and use of geographical data themes. 

The Turkish GIS Board of the General Directorate of GIS produced the National 

Geographical Information Strategy and Action Plan in June 2020. In addition to the 

action plan, a data responsibility matrix has been developed. Six objectives, 27 targets, 

and 46 actions are defined in the Action Plan. 

 

 

 

Analysis of 

International 

Standards (IP4) 

Developmen

t of KBS Data 

Exchange 
Format (IP7) 

Making Administrative and Financial 

Modelling and Preparing Draft Legislation 

(IP8) 

Legislative Analysis 

(IP1) 

Data Requirements 

Analysis (IP3) 

Data Requirements 

Analysis 

Current Data Analysis 

KBS Application 

Examples 

Main Standards 

Conceptual Data 

Model Design (IP5) 

Institutional 

Analysis (IP2) 

Business Process 

Analysis 

Legislative Requirement 

Setting of 

Spatial Data 

Standarts 

(IP6) 

B
u

si
n

e
ss

 D
e

sc
ri

p
ti

o
n

 



29 

In summary, it involves creating a monitoring and reporting system suitable for 

decision support systems that is directly linked to processes. In addition, it involves 

considering the needs of producers and users (T.C. Resmî Gazete, 2020). 

2.7 TUCBS Geodata Themes 

The Definition Documents and Standards for Geographical Data Themes training 

document outlines how to create a roadmap that will enable data producers, public 

institutions, and organizations to share geographical data by standards over the 

National Geographical Information Platform. The general headings in this document 

are listed below: 

- Data Description Documents 

- Data Content and Structure in Data Description Documents 

- Reference Systems, Units of Measure, and Grids 

- ISO 19157 Data Quality Components 

- ISO 19115 Metadata Standard 

- Examples of Data Reconciliation Using Data Definition Documents 

- Conclusion and Evaluation 

In accordance with the scope of Presidential Decree No. 49 on Geographical 

Information Systems, national and international standards are used to determine and 

update geographical data themes. 

As part of the process of preparing Data Identification Documents, the General 

Directorate of Geographical Information Systems prepared the Guidelines for 

Interoperability Procedures and Principles, the Technical Interoperability Procedures 

and Principles, the General Conceptual Model, and the General Concepts Glossary 

documents, which served as the basis for the creation of the Data Identification 

Documents. Relevant documents are published by the General Directorate of 

Geographical Information Systems at Url-8. 

Geographical data, the most essential and fundamental component of the Turkish 

National Geographical Information System (TUCBS), refers to all kinds of data 

containing location information. Geographical data consists of geometry information, 



30 

location information expressed in coordinates, and non-spatial attribute information. 

A hierarchical structure for grouping geographical data is shown in Figure 2.7. 

 

Figure 2. 7 : Hierarchical structure for modeling Geographical data in Geographical 

data themes. 

Within the scope of data themes, the structure of the geographical data and how it will 

be presented are explained together with the schema rules. The data to be shared is 

expected to comply with the theme standards and schema rules. Table 2.1 shows 

Geographical Data Themes. 

Sub-theme groups (category information) belonging to the geographical data theme 

are part of the high-level classification system to support the grouping and subject-

based search of existing spatial data sources. Table 2.2 shows the classification system 

used in the metadata generation phase. After selecting a TUCBS theme group of 

Geographical data from this table, it can be used when creating metadata by 

determining its sub-theme (category). The category information within each theme 

group is also listed in the table in question. 

 

 

 

 



31 

Table 2. 1 : Geographical Data Themes. 

NO THEME 

1 Coordinate Reference Systems and Geographical Grid Systems 

2 Administrative Units 

3 Geographical Names 

4 Cadaster 

5 Buildings 

6 Addresses 

7 Elevation 

8 Orthoimagery 

9 Transport Networks 

10 Hydrography 

11 Geology 

12 Land Cover 

13 Land Use 

14 Soil 

15 Protected Sites 

16 Natural Risk Zones 

17 Infrastructure 

18 Energy Resources 

19 Mines 

20 Human Health and Safety 

21 Population Distribution - Demography 

22 Environmental Monitoring Facilities 

23 Industrial Facilities 

24 Agricultural Facilities 

25 Public Administration Regions 

26 Species Distribution 

27 Habitats 

28 Biogeography 

29 Sea and Salty Water Regions 

30 Atmosphere Data 

31 Meteorological Data 

32 Statistical Reporting Zones 



32 

Different institutions/organizations in terms of data theme, scope, and content. It was 

decided to divide them into sub-theme groups if they are of interest to you, for 

example, Transport Networks Theme - Road Network, Transport Networks Theme - 

Railway Network. Each data theme was studied by the Theme Working Committees 

based on sub-theme groups. There are 52 sub-theme groups related to 32 geographical 

data themes determined within the scope of TUCBS.  

Table 2. 2 : Sub-theme groups (category information). 

NO THEME SUB THEME (CATEGORY) 

1 Coordinate Reference Systems and 

Geographical Grid Systems 

Coordinate Reference Systems 

2 Administrative Units Administrative Units 

3 Geographical Names Geographical Names 

4 Cadaster Cadaster 

5 Buildings Buildings 

6 Addresses Addresses 

7 Elevation Elevation 

8 Orthoimagery Orthoimagery_5000_Under 

Orthoimagery_5000_Above 

9 Transport Networks Road Transport Network (Intercity) 

Road Transport Network (Local) 

Railway Transport Network 

Air Transport Network 

Sea and Water Transport Network 

Inner City Rail Systems and Cable 

Transport Network 

10 Hydrography Hydrography 

11 Geology Geology 

Hydrogeology 

Geophysics 

12 Land Cover Land Cover 

13 Land Use Existing Land Use 

Planned Land Use 

14 Soil Soil 

15 Protected Sites Protected Sites 

16 Natural Risk Zones Natural Risk Zones 

 



33 

Table 2. 2 (continued): Sub-theme groups (category information). 

NO THEME SUB THEME (CATEGORY) 

17 Infrastructure Electric 

Oil/Gas/Chemical 

Sewer 

Water 

Electronic Communication 

Thermal 

Environmental Management Facilities 

Main Administrative and Social 

Services 

18 Energy Resources Energy Resources 

Energy Statistics 

19 Mines Mines 

20 Human Health and Safety Safety 

Human Health 

Environmental Quality 

21 Population Distribution - Demography Population Distribution - Demography 

22 Environmental Monitoring Facilities Environmental Monitoring Facilities 

23 Industrial Facilities Industrial Facilities 

24 Agricultural Facilities Agricultural Facilities 

25 Public Administration Regions Public Administration Regions 

26 Species Distribution Species Distribution 

27 Habitats Habitats 

28 Biogeography Biogeography 

29 Sea and Salty Water Regions Sea and Salty Water Regions 

30 Atmosphere Data Atmosphere Data 

31 Meteorological Data Meteorological Data 

32 Statistical Reporting Zones Statistical Reporting Zones 

2.7.1 TUCBS Natural risk zones theme 

It covers the elements needed to define "TUCBS Natural Risk Areas." It provides 

modeling of hazard, vulnerability, exposure, risk, and observed event concepts. 

In the data definition guides, models are presented in which the concepts are abstract 

and can be represented both as vectors (and therefore based on the TS EN ISO 19107 

standard) and coverage (and therefore based on the TS EN ISO 19123 standard). 



34 

There are four Geographical objects modeled as both vectors and coverage. These; 

 Hazard Area (TehlikeAlani) 

 Exposed Element (TehlikeAltindakiVarlik) 

 Risk Zone (RiskBolgesi) 

 Observed Event (GozlenenOlay) 

The Natural Risk Zones implementation schemes are not entirely independent but have 

interdependencies with other TUCBS implementation schemes. 

 

Figure 2. 8 : UML Scheme of Natural Risk Zones. 

2.7.1.1 “TehlikeAlani” Hazard Area 

The following Geographical feature types are detailed: 

“SoyutTehlikeAlani” (AbstractHazardArea) 



35 

“TehlikeAlani” (HazardArea) 

“TehlikeAlaniCoverage” (HazardAreaCoverage) 

Standart features of “SoyutTehlikeAlani” (AbstractHazardArea):  

 NesneTanimlayici 

 Determination Method: There are several ways to plot the area of a hazard, these 

are modelled by using “BelirlemeYontemDegeri” (Determine Methods Value) 

This data type has two possible values has: 

- “modelleme” (modelling) 

- “yorumlama” (interpretation) 

 Hazard Type: this feature is modelled with the “DogalTehlikeSiniflandirmasi” 

(Natural Hazard Classification) data type. 

The data type “DogalTehlikeSiniflandirmasi” (NaturalHazardClassification) contains 

the code list “DogalTehlikeKategorisiDegeri” (NaturalHazardCategoryValue). 

The representation of a “TehlikeAlani” must have geometry modeled as GM_Surface. 

Therefore, all hazard areas are modeled as polygons. 

Features specific to “TehlikeAlani”:  

Likelihood of Occurrence: LikelihoodOfOccurrence is a general concept of the 

probability of an event to occur. This is modeled with the Likelihood of Occurrence 

data type. This data type has 3 attributes. “degerlendirmeYontemi” 

(assessmentMethod) means the method used to express the probability of the hazard 

event, “nitelOlasilik” (qualitativeLikelihood) defines the evaluation of the probability 

of occurrence of a hazard, “nicelOlasilik” (quantitativeLikelihood) refers to the 

probability of occurrence or the recurrence interval. 

Size: A size can be expressed qualitatively or quantitatively. 

Violence: A violence can be expressed qualitatively or quantitatively. 

It is possible to use an observed event as an input for hazard area modelling. 

Therefore, a hazard area may have an observed event as a source.  

2.7.1.2 “TehlikeAltindakiVarlik” (ExposedElement) 

The following Geographical feature types are detailed: 



36 

“SoyutTehlikeAltindakiVarliklar” (AbstractExposedElement) 

“TehlikeAltindakiVarlik” (ExposedElement) 

“TehlikeAltindakiVarlikCoverage” (AbstractExposedElementCoverage) 

Standard features of “SoyutTehlikeAltindakiVarliklar” 

(AbstractExposedElement): 

It refers to the Geographical representation of people, property, systems, or other 

elements located in hazard areas and, therefore, subject to potential harm. The 

assessment of vulnerability can be calculated on these geographical objects. 

Features specific to “TehlikeAlani”: The geometric representation of the exposed 

element is modeled as GM_Object and allows basically any geometrical construction. 

Also, this vector geo object contains the same named attribute using the data type 

"zararGorebilirlikSeviyesi" (assessmentOfVulnerability). This data type has 4 

attributes. 

“ZararGorebilirlikKaynagi” (sourceOfVulnerability) means the interpretation of the 

vulnerability of the exposed element using the “DogalTehlikSiniflandirmasi” 

(NaturalHazardClassification) data type. 

The “ZararGorebilirlikSeviyesi” (levelOfVulnerability) is the result of the assessment 

of vulnerability. This property is modeled with “SeviyeveyaSiddet” (Level or 

Intensity) data type. “VarliginTipi” (TypeofElement) is defined to facilitate data 

interoperability. 

2.7.2 “RiskBolgesi” (Risk Zone) 

The following Geographical feature types are detailed: 

“SoyutRiskBolgesi” (AbstractRiskZone) 

“RiskBolgesi” (RiskZone) 

“RiskBolgesiCoverage” (RiskZoneCoverage) 

Common features of “SoyutRiskBolgesi” (AbstractRiskZone): A risk zone refers 

to the geographical extent of the combination of the consequences of an event (hazard) 

and the associated probability. 



37 

riskSeviyesi (RiskLevel): riskSeviyesi refers to the assessment of the combination of 

the consequences of a (hazard) event and the probability of that event occurring. 

Features specific to “RiskBolgesi”: Vector representation of a risky region is 

modeled as GM_Surface. Therefore, all risk zones are modeled as polygons. 

Features specific to “RiskBolgesiCoverage”: Values that vary by location are the 

risk level. Since the risk level is modeled by the LevelOrSeverity data type, the 

limitation on the coverage span is for the LevelOrSeverity datatype. 

 

Figure 2. 9 : UML Class Diagram: DogalRiskBolgeleri code lists. 

2.7.3 “GozlenenOlay” (ObservedEvent) 

The following Geographical feature types are detailed: 

“SoyutGozlenenOlay” (AbstractObservedEvent) 

“GozlenenOlay” (ObservedEvent) 



38 

“GozlenenOlayCoverage” (ObservedEventCoverage) 

Common features of “SoyutGozlenenOlay” (AbstractObservedEvent): An 

observed event refers to the geographical representation of a natural phenomenon that 

has occurred or is currently occurring and is related to the study of observed natural 

hazards. 

Features specific to “GozlenenOlay” (ObservedEvent): The vector representation 

is modeled as “GM_Object”. This basically covers all geometric primitive types. 

Features specific to “GozlenenOlayCoverage” (ObservedEventCoverage): Values 

that vary by location, assess the level or severity of vulnerability. 

2.8 Unified Modelling Language/UML 

UML is a unified modeling language produced by OMG (Object Management Group) 

for designing and developing standards for object-oriented systems and programs. 

UML is used in the creation of conceptual schemas for Geographical data 

management. UML is the basis of the object-oriented-relational modeling method in 

determining the conceptual model of the modeling field, creating the logical model, 

and converting it to the physical structure. 

Application Schema: INSPIRE, ISO 19109, and TUCBS Conceptual Model were 

used to create the application schema. It integrates the features of each data theme. 

FeatureType: ISO 19136 and TUCBS geometry standards are considered. A feature 

class that does not define spatial objects. 

DataType: It is used to express non-object descriptive, structured data classes within 

the scope of the ISO 19103 standard. 

Attribute Value (Enumeration): While defining the attribute value, the ISO 19136 

standard is based. A list of values that limits the values that properties and attributes 

can take. 

Code List: Within the scope of the ISO 19136 standard, the value list lists the values 

that properties and attributes can take and defines the code value. 



39 

Classes: It refers to a set of objects that contain the same function, method, 

relationship, attribute, behavior, and constraints. A class is a concept intended to be 

modeled as platform-independent or platform-specific. 

Every UML class has a name. In addition, it has attributes and relationships, and its 

functions and restrictions can be defined according to needs (CBSGM, 2012d).  

UML has two different class types, stereotypes <<interface>> and <<type>>. 

<<interface>> defines an object's properties and attributes do not include. <<type>> 

is a stereotyped class that contains functions/functions, attributes, and relationships 

that can be applied to objects. 

Attributes are used to describe the properties of objects in the data model. Each 

attribute must have a type and be defined. It can have a certain repeatability value. If 

the repetition value is not defined, this value is accepted as 1. 

Attribute values and code lists refer to sets of values, or values attributes can take. The 

code list can be coded according to ISO 3166-1 standard. The selected representation 

of the code list is value/code. 

Relationship types between objects in UML rules are defined within the ISO/TS 

19103:2005 standard. 

2.8.1 UML Relation Types 

2.8.1.1 Association 

Association expresses a weak semantic relationship between two classes. If two classes 

in a model need to relate to each other, there must be a connection between them. The 

Association defines the connection. A straight line between two objects expresses 

Association. 

Figure 2.10 shows the association relationship between SoyutTehlikeAlani and 

SoyutGozlenenOlay feature types. The example indicates that a SoyutTehlikeAlani 

object could associate with no or more SoyutGozlenenOlay objects.  

 



40 

 

Figure 2. 10 : UML Relation Types - Association. 

 

Figure 2. 11 : UML multiplicity indicators (Ambler, 2002). 

2.8.1.2 Inheritance 

Inheritance (Generalization) combines similar object classes into a single and general 

class. A child feature type is a subclass with all the superclass properties and derives 

from it. The inheritance relationship is indicated by the arrow sign between the two 

objects. 

 



41 

 

Figure 2. 12 : UML Relation Types - Inheritance (Generalization). 

As seen in Figure 2.12, there is an inheritance relationship between the 

SoyutTehlikeAlani and TehlikeAlani feature types. TehlikeAlani is a subclass of 

SoyutTehlikeAlani. SoyutTehlikeAlani has all the attributes of the SoyutTehlikeAlani 

parent feature type and its attributes. 

2.8.1.3 Aggregation 

Aggregation is used to divide complex relationships into simple parts. A class in the 

aggregation relationship could be an integration of simple subparts. The child object 

could exist independently of the parent object (UML Association vs. aggregation vs. 

composition). 

 

Figure 2. 13 : UML Relation Types – Aggregation (Url-9). 



42 

2.8.1.4 Composition 

Composition implies a relationship that is a part of the parent class of one or more 

feature classes. The child object could not exist independently of the parent object. 

 

Figure 2. 14 : UML Relation Types – Composition (Url-9). 

 

Figure 2. 15 : UML Relation Types – Association, Aggregation, and Composition 

(Url-9). 

2.8.2 Data modelling with UML 

Object-oriented geographical database modeling provides a complex application that 

the relational model cannot resolve. This is used for expressing objects with similar 

properties in the real world in a specific group and provides flexibility, reusability, and 

ease of usage in GIS applications (Aydinoglu, 2009).  



43 

ISO/TC 211 Geographical Information / Geomatics Technical Committee's ISO 19103 

Conceptual Schema Language and ISO 19109 Rules for Application Schema standards 

are used in developing a Geographical data model. Compliance with other ISO/TC 211 

standards is anticipated. At the logical level, "Class Diagrams," one of the UML 

modeling techniques from the Geographical data model development stage, are used. 

At this stage, the UML definitions recommended in the ISO 19103 standard developed 

by the ISO/TC211 Technical Committee should be considered (Bilgin, 2013). 

The purpose of class diagrams in an object-oriented application is to describe the 

classes in the model. An object or a set of objects which share a common behavior and 

structure is represented by a class. A class consists of the class name, attributes, and 

operations. Also, restrictions, labels, and stereotypes could be included in a class.  

2.9 Geography Markup Language/GML 

Geography Markup Language (GML), developed by OGC, is an XML application 

written using XML Schema for modeling, transporting, and storing geometry and 

attribute information of Geographical features (Alas, 2011). XML Schema files are 

needed to interpret XML applications. Similarly, GML Schema files are used for GML 

applications. Thus, users can define geographical objects (Sarı, 2014). 

GML was developed based on the OGC and ISO 19118 series standards. As part of 

this process, a standard will be established for representing information about spatial 

data and a grammar and dictionary for describing geographical data (CBSGM, 2012c). 

The basic features used by GML are derived from the definitions of OGC (Url-10). 

In addition, WFS, one of the OGC standards, can read and write GML files (Sarı, 

2014). 

A GML file may contain the following concepts. 

  Object 

 Geometry 

 Coordinate Reference System 

 Time 

 Dynamic Object 



44 

 Cellular Object (Geographical graphics) 

 Unit of Measure 

 Map Display Formats 

Although it is not necessary to have all these mentioned concepts, the object, geometry, 

and coordinate system are required for geographical data to be meaningful (Tunccekic 

& Dincer, 2007). 

GML documents are not affected by the method of generation. Since GML schemas 

are XML schemas, a single interpreter can be used for both the schema and the GML 

document. An application schema enforces the accurate construction of application 

specific GML documents by restricting and extending GML definitions. With the aid 

of a hierarchy of GML objects, GML defines various types and elements of XML 

schemas, such as features, geometries, and topologies. As described in the OGC 

specification, the GML objects can be broken down into several schema documents 

that cover such topics as Feature, Geometry, Topology, Value, Coverage, Temporal, 

Coordinate Reference System, XLink, and StyleDescriptor. There are also subtypes of 

Feature, such as Observation, Coverage, and Definition. As a result, the application 

schema applies the necessary features and types to the particular domain. Examples of 

GML documents and schema documents can be found in the OGC