Infrastructure Engineering - Theses
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ItemBIM-based Property Ownership Evaluation in Land Administration : Minimizing Property Disputes( 2022)Multi-owned buildings (MOBs) have been primary living spaces for urban residents but also properties prone to disputes, wherein owners fight over their use and management. Over the last decades, as an increasing number of people have moved into such buildings, disputes over these properties have become a global issue threatening seamless urban management. Under strata title systems, MOB ownership systems serve as authoritative governance mechanisms, and their inappropriate forms from a governance perspective are regarded as critical sources of disputes. This shows the potential for proactive dispute minimization by identifying and addressing dispute causes within the ownership system. Although all MOBs are generated in a legally valid form through building subdivision, their ownership systems do not always create good governance structures as they are shaped and validated only to create property titles adequate for land registration purposes. Common approaches to property disputes interpret disputes as a social matter and focus on mitigation by controlling social and behavioral factors after occupancy. There are no legal prescriptions or industry principles for building subdivision to ensure the seamless operation of MOBs, while minimizing disputes. Ownership systems have been determined at surveyors’ discretion, without any systematic approaches for managing controllable causes of dispute in MOB ownership systems. In addition, the current 2D-based practice reliant on individual experience limits surveyors’ capability to explore dispute-leading aspects of MOB ownership systems in consideration of associated building design. These circumstances have led to inconsistent performance of building subdivision from the governance point of view and occasionally generated ownership systems that contain dispute triggers. This research investigates how MOB ownership systems are evaluated to identify dispute triggers during building subdivision, and how this evaluation facilitates the minimization of property disputes. Based on the identified research gaps and requirements from the literature review, the thesis proposes a novel approach to evaluating MOB ownership systems toward proactive dispute minimization during building subdivision, using Building Information Modeling (BIM). The approach comprises three components: (1) a Sociotechnical System (STS) model of MOB ownership systems, (2) indicators of MOB ownership systems for minimizing disputes, and (3) a BIM-based framework for checking the indicators to identify dispute triggers. In the BIM data environment, this approach identifies and visualizes geometrical and semantic dispute triggers in the 3D by representing MOB ownership systems as BIM expressions of the STS models and checking them against BIM-based rules for measuring the indicators. In this research, the indicators represent characteristics of MOB system components in terms of performance, violations of which can cause disputes. They are established, focusing on MOB aspects affecting disputes identified by empirical analysis with a machine learning algorithm. The approach is developed by implementing its prototype to demonstrate its viability in evaluating MOB ownership systems. The feasibility of the approach is evaluated from two perspectives. First, the plausibility of the proposed indicators in minimizing disputes is validated based on the opinions of industry experts since they serve as a core knowledge base to detect dispute sources. The effectiveness of the approach is validated by applying the implemented prototype to a case study. The findings from the interview and case study show that the approach can be adopted in surveying practice on the grounds of the high satisfaction level obtained from experts, the availability of required technologies, and its effective role in identifying dispute sources. As the main contribution of this research, the proposed approach could improve understanding and communication of dispute-leading conditions of MOB ownership systems to aid better decision-making during building subdivisions to produce dispute-preventive governance structures.
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Item3D Spatial Data Validation in Urban Land Administration( 2022)The world’s growing and increasingly unsustainable rate of urbanisation has resulted in attempts to utilise spaces more efficiently and a higher level of spatial complexity in metropolitan areas. This has led to the building proliferation of multi-storey apartment blocks, offices, and other urban infrastructure to accommodate more people and provide more facilities. Multi-storey buildings are the most prominent components of an urban built environment. The complexity of urban built environments is progressively being increased by developing and designing overly complex multi-storey constructions. A collection of ownership spaces associated with privately, commonly, and publicly owned properties are defined within multi-storey buildings. Property ownership rights include a variety of rights, restrictions, and responsibilities (RRRs). Land administration systems provide a platform for implementing land management policies and strategies. Cadastre is an engine of land administration systems that is responsible for registering RRRs information. The information and processes associated with documenting and managing legal ownership of properties in multi-storey building developments are what urban land administration systems deal with. The spatial and legal definition of arrangements and boundaries of RRR spaces plays an underpinning role in urban land administration practices. The spatial extent of ownership spaces within multi-storey buildings is often outlined as complex 3D volumetric spaces in complex ownership settings. However, the current urban land administration practices have been founded around 2D-based systems and technologies. This means that different components of land administration such as data representation, visualisation, storage, and validation are managed by either fully analogue or partially automatic 2D technologies. For example, 2D subdivision plans and cross-sections represent 3D ownership spaces within multi-storey buildings. The examination process serves as a manual one in the current practice. This 2D-based system introduces a gamut of challenges and issues in terms of communicating, storing, and examining various complex volumetric ownership spaces defined within multi-storey buildings. 3D geospatial technologies have shown their excellent potential and maturity for managing complex, vertical multi-layered ownership arrangements. However, the current 2D examination system is not mature enough to examine the spatial and legal volumetric ownership spaces. The current 2D examination system utilising 2D validation rules is not capable of ensuring an unambiguous and definitive spatial and legal definition of 3D property parcels when dealing with 3D digital data. Hence, as part of land administration modernisation, not only is 2D analogue data being replaced with 3D digital models, but the examination process and its principles and validation rules must be able to validate 3D digital data. Developing principles and validation rules is a critical requirement to guarantee that the diverse cadastral data is trustworthy and contains enough detail to define ownership’s spatial and legal boundaries. Therefore, this thesis aimed to develop a set of 3D principles and validation rules to ensure the spatial and legal integrity of legal boundaries as well as volumetric legal spaces defined in a 3D digital representation of built environments. To develop a framework for 3D cadastral data validation, the current examination practice in Victoria, Australia was investigated. Subsequently, methods and approaches using computational geometry algorithms were devised to check the internal and external spatial consistency and integrity of 3D parcels and their relationships in multi-storey buildings. The research was also extended to investigate the required stages: firstly, for generating cadastral data using the Building Information Model (BIM); and secondly, to develop criteria and standards to check the validity of BIM-based cadastral data during and at the end of data generation. A wide range of complex cadastral datasets was used to evaluate the reliability and viability of the developed methods. The findings of this research will potentially enable modern land administration processes to function more efficiently, by avoiding the accumulation of errors in 3D cadastral data generation and automating the 3D cadastral data examination process.
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ItemNo Preview AvailableSpatial query and analysis for 3D urban land administration( 2022)Urban land administration includes the essential information and processes for supporting rights, restrictions, and responsibilities (RRRs) in multi-storey structures. The rapid growth of multi-storey buildings and urban infrastructure challenges the efficiency of the current 2D land administration systems in managing and communicating RRRs in spatially complex situations. Therefore, 3D digital approaches and models are being researched to make it easier to manage RRRs in urban environments. Recent studies have shown that building information models (BIMs) should have the required features for managing 3D RRR data in urban land administration. In order to transfer information between different BIM applications, the Industry Foundation Classes (IFC) data model is used. In IFC, most 3D objects are modelled using solid models. IFC supports different types of geometric representations for solids. 3D RRR spaces (3D volumetric representation of property) are typically modelled using swept solid geometry in IFC. For retrieving property boundaries from an IFC model, faces of the 3D legal space that represent property boundaries should be extracted. The type of boundary will then be assigned to each face based on the spatial relationships between the 3D legal space and the surrounding building elements. This procedure is called boundary identification analysis. However, faces of objects that are modelled using the swept solid geometry cannot be extracted. Consequently, using file-based IFC data to undertake boundary identification analysis is not feasible. To overcome the geometry data storage issue of IFC data in modelling 3D RRR spaces, and its limitations in doing spatial analyses (e.g. boundary identification analysis), a 3D spatial database can be used to replace file-based approaches. In a 3D spatial database, 3D objects are modelled using polyhedral surface geometry. In this way, data can be accessed not only at the object-level but also at the surface level. As a result, performing spatial analyses that combine several object and surface-level queries is possible. Furthermore, different access privileges can be defined on the object level or even surface level for different users. Consequently, only specific users can edit or manipulate the data. Within an organisation, files are created by different programmers working in various departments over long periods of time, which will lead to data redundancy. However, using a spatial database eliminates data redundancy and data only needs to be stored once. By considering the land management paradigm as the basis, this research aims to develop a 3D spatial database to answer the analysis requirements of urban land administration. In order to achieve this aim, the Victorian land administration system was considered as a case study. In the first step, the spatial analysis requirements of the Victorian land administration system (required Level of Detail (LoD) for each analysis, legal data, etc.) and the knowledge gaps were identified. It was found that boundary identification analysis is the most important spatial analysis in urban land administration; however, no methodology was developed for conducting this analysis. In the next step, the capabilities of current 3D data models for performing boundary identification analysis were evaluated. In addition, a new methodology for boundary identification analysis using the ray projection method for identifying the topological relationships between 3D legal spaces and building elements was devised and implemented. It became clear that current 3D data models do not support topological operators and no methodology for modelling complex 3D legal spaces, which are surrounded by oblique and curved building elements, had been developed prior to this research. Following this, by considering the identified spatial analysis requirements and knowledge gaps in previous steps, a framework for creating a unified 3D spatial analysis system for urban land administration is proposed. Based on the proposed framework, developing an IFC-based database that takes into account the spatial analysis requirements of urban land administration would lead to: firstly, reducing the number of tables and entities in the database; secondly, increasing its functionality; and thirdly, guaranteeing that the designed database can answer all the analysis requirements of this domain. As mentioned before, no methodology for modelling complex 3D legal spaces, surrounded by oblique and curved building elements, was detected in the previous steps. In the next step, by taking into account the identified 3D spatial analysis requirements, a new methodology for modelling complex legal spaces was proposed. An IFC-based 3D spatial database for urban land administration was developed and to evaluate the database’s performance, two real datasets (multi-storey buildings with four and three levels) and one test dataset with oblique and curved building elements were stored in the developed 3D spatial database. Furthermore, a methodology for boundary identification analysis using the spatial operators of the database was developed. The proposed methodology can identify the property boundaries of both simple (surrounded by vertical walls and horizontal roof and floor) and complex 3D legal spaces. The thesis concludes with several suggestions for future research in urban land administration.
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ItemLeveraging BIM to enhance public procurement for infrastructure projects( 2021)Australian public policy references to building information modelling (BIM), a 3D digital attributable object based built environment representation capability, continue to evolve. Whilst BIM is heralded as a means to lift productivity in the architecture, construction and engineering industry, developments are converging with other emerging narratives. The shifting intent has meant different objectives, opportunities and challenges are presented, particularly for broad and socially orientated applications that involve BIM. However, public policy responses remain unresolved, whether to reconcile or leverage these Big Picture perspectives or overcome prevailing limitations. As a result, directions for public procurement of infrastructure projects in view of BIM remain unclear. In progressing policy orientated debates, the current thesis presents constructive-interpretivist research to develop public procurement policy options aimed at capitalising on the opportunity afforded by BIM for infrastructure projects. From the abductive conceptual study, unique theoretical informational systems-based perspectives and concepts are developed to interpret BIM and its place in context. BIM systems (technology, modelling and model) are distinguished from other forms and features of informational systems. An idealised frame for policy development is proposed, setting the relativity of BIM systems at scale and evolutionary economics-based orders of rules. Application of the theoretical perspectives is presented and validated through a deductive case study of nested “systems”. Focusing on the roads sector between early 2017-2018, the resulting constructed narrative vertically profiles Australian organisational, project, industry and government positions and policies in view of BIM. Comparative qualitative analyses expose policy distinctions and coordination risks in terms of “BIM”, BIM systems, pre-BIM states and other systems characteristics. Predicted transformational implications draw from the consistent omission or narrow referencing of “rules” relating to BIM and the roads sector. However, outcomes highlight that despite indicative embryonic features, the underlying pre-text of analogous BIM characteristics (including functionality) is also qualified. Even before getting to BIM, the necessity and value propositions for consolidated or integrated and granular detailing and performance about the built environment is underdeveloped. Responding to the identified issues and risks, the research qualifies the demand for BIM to assist decision makers understand the extent and investment of proposed policy changes in response to BIM. The point of BIM is reset to engender scaled productivity towards “digital infrastructure” and reconcile business as usual presumptions and the creative-destructive implications of change. The recommended policy options target multi-stakeholder interventions and mechanisms that range from the development of strategic internal positioning on BIM for the road agency and extend through to a proposed intergovernmental agreement that advances capability in the Australian built environment sector. In preparation for BIM rather than “BIM” per se, the public policy options are developed as a first pass step for the future development of more comprehensive, longer term programs. From the theoretical perspectives, this includes acknowledging data or digital based approaches as a necessary but qualified step towards predicted future directions predicated on informational systems outcomes.
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ItemVisual indoor localisation using a 3D building model( 2020)With the emergence of the global navigation satellite system (GNSS), the performance of outdoor localisation has become excellent over the years. Applications like navigation, location-based services and augmented reality demand seamless localisation capabilities in all environments. However, a single technology that can satisfy the needs of localisation in indoor spaces is absent to date. The major limiting factor in the large scale adoption of indoor localisation systems is the overhead cost of installation and maintenance of dedicated local infrastructure. Consequently, infrastructure-independent indoor localisation has become a focus of research during the past decade. The ubiquity of smartphones with integrated cameras has resulted in a renewed interest in infrastructure-independent visual localisation approaches for the indoor environments. However, the existing visual approaches face two challenges that restrict the wide applicability of such approaches. Firstly, current visual simultaneous localisation and mapping (SLAM) approaches, where the challenge is the drift caused by the accumulation of errors. Loop closing is a solution to eliminate drift but it poses a limitation in the practical application of visual positioning. For navigation purposes, revisiting the same location might be impractical. The second challenge for the existing visual approaches is the requirement of an initial location. The existing visual approaches that are independent of the initial locations require either the construction of large database of images with known location or a 3D reconstruction of the indoor environment in the form of depth images or 3D point clouds. However, the creation of a database of images with known locations and the acquisition of additional data for large indoor spaces is a challenge due to the cost, time and post-processing involved. This research presents approaches to address the two above-mentioned challenges of the existing visual approaches by using a 3D building model that is usually available through the building information modelling process or can be generated with little effort from existing 2D plans. The motivation of using BIM for this research comes from the fact that BIMs of modern buildings are readily available, as they are jointly maintained by the constructors and facility managers. The research can be broadly classified into two parts. The first part proposes a novel 3D model-based visual tracking approach called BIM-Tracker. BIM-tracker uses the 3D building model to perform a drift-free localisation and addresses the challenge of accumulation of error. Localisation is performed by integrating image sequences captured by a camera, with the 3D building model. A comprehensive evaluation of the approach with photo-realistic synthetic datasets shows the robustness of the localisation approach under challenging conditions. Additionally, the approach is evaluated on real data captured by a smartphone, and achieves an accuracy of ten centimetres. Similar to the requirement of many visual approaches, BIM-Tracker depends on the availability of the initial location. The second part of the research proposes a deep learning-based method called BIM-PoseNet to estimate the initial location. The requirement of image-based reconstruction of the indoor environment is eliminated by using a 3D building model, thereby addressing another challenge of the existing visual approaches that estimate the initial location. BIM-PoseNet is based on training a CNN with synthetic images obtained from the 3D indoor model to regress the location of a real image taken by a camera. In addition, the uncertainties of camera location estimates are modelled by adopting a Bayesian CNN, as uncertainty provides an indication of confidence and trust in an estimated location in the absence of ground truth. Furthermore, the use of sequences of synthetic images is explored to exploit the spatio-temporal information from the images to improve the performance of BIM-PoseNet by using recurrent neural networks. The results of the qualitative and quantitative experimentation of the proposed approaches with photo-realistic synthetic and real datasets indicate the proposed research addresses the two major limitations of the existing visual indoor localisation approaches. In addition, the proposed research demonstrates the potential of visual indoor localisation as a single technology for achieving an infrastructure-independent localisation.