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Interoperability of Traffic Infrastructure Planning and Geospatial Information Systems

Building Information Modelling (BIM) as a Model-based design facilitates to investigate multiple solutions in the infrastructure planning process. The most important reason for implementing model-based design is to help designers and to increase communication between different design parties. It decentralizes and coordinates team collaboration and facilitates faster and lossless project data exchange and management across extended teams and external partners in project lifecycle.
Infrastructure are fundamental facilities, services, and installations needed for the functioning of a community or society, such as transportation, roads, communication systems, water and power networks, as well as power plants. Geospatial Information Systems (GIS) as the digital representation of the world are systems for maintaining, managing, modelling, analyzing, and visualizing of the world data including infrastructure. High level infrastructure suits mostly facilitate to analyze the infrastructure design based on the international or user defined standards. Called regulation1-based design, this minimizes errors, reduces costly design conflicts, increases time savings and provides consistent project quality, yet mostly in standalone solutions.
Tasks of infrastructure usually require both model based and regulation based design packages. Infrastructure tasks deal with cross-domain information. However, the corresponding data is split in several domain models. Besides infrastructure projects demand a lot of decision makings on governmental as well as on private level considering different data models. Therefore lossless flow of project data as well as documents like regulations across project team, stakeholders, governmental and private level is highly
important. Yet infrastructure projects have largely been absent from product modelling discourses for a long time. Thus, as will be explained in chapter 2 interoperability is needed in infrastructure processes.
Multimodel (MM) is one of the interoperability methods which enable heterogeneous data models from various domains get bundled together into a container keeping their original format. Existing interoperability methods including existing MM solutions can’t satisfactorily fulfill the typical demands of infrastructure information processes like dynamic data resources and a huge amount of inter model relations. Therefore chapter 3 concept of infrastructure information modelling investigates a method for loose and rule based coupling of exchangeable heterogeneous information spaces. This hypothesis is an extension for the existing MM to a rule-based Multimodel named extended Multimodel (eMM) with semantic rules – instead of static links. The semantic rules will be used to describe relations between data elements of various models dynamically in a link-database.
Most of the confusion about geospatial data models arises from their diversity. In some of these data models spatial IDs are the basic identities of entities and in some other data models there are no IDs. That is why in the geospatial data, data structure is more important than data models. There are always spatial indexes that enable accessing to the geodata. The most important unification of data models involved in infrastructure projects is the spatiality. Explained in chapter 4 the method of infrastructure information modelling for interoperation in spatial domains generate interlinks through spatial identity of entities. Match finding through spatial links enables any kind of data models sharing spatial property get interlinked. Through such spatial links each entity receives the spatial information from other data models which is related to the target entity due to sharing equivalent spatial index. This information will be the virtual properties for the object. The thesis uses Nearest Neighborhood algorithm for spatial match finding and performs filtering and refining approaches. For the abstraction of the spatial matching results hierarchical filtering techniques are used for refining the virtual properties. These approaches focus on two main application areas which are product model and Level of Detail (LoD).
For the eMM suggested in this thesis a rule based interoperability method between arbitrary data models of spatial domain has been developed. The implementation of this method enables transaction of data in spatial domains run loss less. The system architecture and the implementation which has been applied on the case study of this thesis namely infrastructure and geospatial data models are described in chapter 5.
Achieving afore mentioned aims results in reducing the whole project lifecycle costs, increasing reliability of the comprehensive fundamental information, and consequently in independent, cost-effective, aesthetically pleasing, and environmentally sensitive infrastructure design.:ABSTRACT 4
KEYWORDS 7
TABLE OF CONTENT 8
LIST OF FIGURES 9
LIST OF TABLES 11
LIST OF ABBREVIATION 12
INTRODUCTION 13
1.1. A GENERAL VIEW 14
1.2. PROBLEM STATEMENT 15
1.3. OBJECTIVES 17
1.4. APPROACH 18
1.5. STRUCTURE OF THESIS 18
INTEROPERABILITY IN INFRASTRUCTURE ENGINEERING 20
2.1. STATE OF INTEROPERABILITY 21
2.1.1. Interoperability of GIS and BIM 23
2.1.2. Interoperability of GIS and Infrastructure 25
2.2. MAIN CHALLENGES AND RELATED WORK 27
2.3. INFRASTRUCTURE MODELING IN GEOSPATIAL CONTEXT 29
2.3.1. LamdXML: Infrastructure Data Standards 32
2.3.2. CityGML: Geospatial Data Standards 33
2.3.3. LandXML and CityGML 36
2.4. INTEROPERABILITY AND MULTIMODEL TECHNOLOGY 39
2.5. LIMITATIONS OF EXISTING APPROACHES 41
INFRASTRUCTURE INFORMATION MODELLING 44
3.1. MULTI MODEL FOR GEOSPATIAL AND INFRASTRUCTURE DATA MODELS 45
3.2. LINKING APPROACH, QUERYING AND FILTERING 48
3.2.1. Virtual Properties via Link Model 49
3.3. MULTI MODEL AS AN INTERDISCIPLINARY METHOD 52
3.4. USING LEVEL OF DETAIL (LOD) FOR FILTERING 53
SPATIAL MODELLING AND PROCESSING 58
4.1. SPATIAL IDENTIFIERS 59
4.1.1. Spatial Indexes 60
4.1.2. Tree-Based Spatial Indexes 61
4.2. NEAREST NEIGHBORHOOD AS A BASIC LINK METHOD 63
4.3. HIERARCHICAL FILTERING 70
4.4. OTHER FUNCTIONAL LINK METHODS 75
4.5. ADVANCES AND LIMITATIONS OF FUNCTIONAL LINK METHODS 76
IMPLEMENTATION OF THE PROPOSED IIM METHOD 77
5.1. IMPLEMENTATION 78
5.2. CASE STUDY 83
CONCLUSION 89
6.1. SUMMERY 90
6.2. DISCUSSION OF RESULTS 92
6.3. FUTURE WORK 93
BIBLIOGRAPHY 94
7.1. BOOKS AND PAPERS 95
7.2. WEBSITES 101

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:31143
Date01 October 2018
CreatorsNejatbakhsh Esfahani, Nazereh
ContributorsScherer, Raimar J., Borrmann, André, Blankenbach, Jörg, Technische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relationurn:nbn:de:bsz:14-qucosa2-805393

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