Infrastructure Engineering - Research Publications

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    Developing and testing a 3D cadastral data model: a case study in Australia
    Aien, A ; Kalantari, M ; Rajabifard, A ; Williamson, IP ; Shojaei, D (ISPRS Comm V Symposium, 2012-07-16)
    Population growth, urbanization and industrialization place more pressure on land use with the need for increased space. To extend the use and functionality of the land, complex infrastructures are being built, both vertically and horizontally, layered and stacked. These three-dimensional (3D) developments affect the interests (Rights, Restrictions, and Responsibilities (RRRs)) attached to the underlying land. A 3D cadastre will assist in managing the effects of 3D development on a particular extent of land. There are many elements that contribute to developing a 3D cadastre, such as existing of 3D property legislations, 3D DBMS, 3D visualization. However, data modelling is one of the most important elements of a successful 3D cadastre. As architectural models of houses and high rise buildings help their users visualize the final product, 3D cadastre data model supports 3D cadastre users to understand the structure or behavior of the system and has a template that guides them to construct and implement the 3D cadastre. Many jurisdictions, organizations and software developers have built their own cadastral data model. Land Administration Domain Model (DIS-ISO 19152, The Netherlands) and ePlan (Intergovernmental Committee on Surveying and Mapping, Australia) are examples of existing data models. The variation between these data models is the result of different attitudes towards cadastres. However, there is a basic common thread among them all. Current cadastral data models use a 2D land-parcel concept and extend it to support 3D requirements. These data models cannot adequately manage and represent the spatial extent of 3D RRRs. Most of the current cadastral data models have been influenced by a very broad understanding of 3D cadastral concepts because better clarity in what needs to be represented and analysed in the cadastre needs to be established. This paper presents the first version of a 3D Cadastral Data Model (3DCDM_Version 1.0). 3DCDM models both the legal and physical extent of 3D properties and associated interests. The data model extends the traditional cadastral requirements to cover other applications such as urban planning and land valuation and taxation. A demonstration of a test system on the proposed data model is also presented. The test is based on a case study in Victoria, Australia to evaluate the effectiveness of the data model.
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    Innovative modelling and visualisation platform for sustainable cities - MUtopia
    Mendis, PA ; Ngo, TD ; Aye, L ; Malano, HM ; Rajabifard, A (University of Moratuwa, 2012)
    Now more than half the world’s population lives in towns and cities and this proportion will rise to nearly two thirds by 2030. Many cities worldwide are facing acute challenges, and therefore it is essential that all future developments are carried out on a sustainable footing. Through a web-based platform, MUtopia visualises and demonstrates in a quantifiable manner what impact a planned site development would have by representing best practice in all aspects of sustainable urban living on a relatively large scale. Sites may be new suburbs or rebuilt sections of the city large enough to require systematic planning. The project focuses on the development of an integrated modelling, analysis and visualization tool that helps the government and developers to make informed decisions to achieve such sustainable urban development and implementation. MUtopia integrates the streams of energy, waste, water and transport, based on land use, as well as social and environmental factors so that various planning scenar os or dependencies between factors can be tested. It is an integrated BIM and GIS tool. MUtopia would be an international first in an area of growing interest and need.
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    Urban structure and transport: Melbourne case study
    Reisi, M ; Aye, L ; Rajabifard, A ; Ngo, DT (Transport and Traffic Organisation, Tehran, 2012-02-21)
    Studies about relationship between urban form and travel are generally at household level. Australian Bureau of Statistics (ABS) and Victorian Integrated Survey of Travel and Activity (VISTA) data at statistical local area (SLA) level for Melbourne, Australia were used to estimate greenhouse gas emissions from personal transport. An integrated model which consists of three sub-models (car ownership, vehicle km travel, mode share) has been proposed in this paper. The model suggests that population density, distance from central business district (CBD) and dwelling types are influencing factors for urban structure measurement and can be used for estimating energy consumption and greenhouse gas emissions. It was found that the model developed is not complex enough for considering the relationship between urban form and personal travel.
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    Harnessing BIM for 3D digital management of stratified ownership rights in buildings.
    Atazadeh, B ; Kalantari, M ; Rajabifard, A ; Champion, T ; Ho, S (International Federation of Surveyors - available at http://www.fig.net …, 2016)
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    Comparing Three Types of BIM-based Models for Managing 3D Ownership Interests in Multi-level Buildings
    Atazadeh, B ; Kalantari, M ; Rajabifard, A (International Federation of Surveyors (FIG) - available at http://www.gdmc …, 2016)
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    Towards integrating multi-sourced sensors for natural disaster management - Case study in flood management
    Alamdar, F ; Kalantari, M ; Rajabifard, A (Mallee Catchment Management Authority (CMA), 2014)
    Having access to and usage of real-time spatial information is central for the functioning of natural disaster management, and in particular disaster response. Exiting spatially-enabled solutions for managing urban natural disasters provide no or not sufficient support for time-sensitivity and dynamism underling disaster situation. These approaches mainly suffer from low temporal resolution, incapability of sourcing broad range of required disaster data, accompanied with limited support for automated operations. Incorporating in situ sensing into the disaster management process can potentially address such challenges with providing wide-range of real-time data coupled with automated operations for data acquisition and management. In this research we study the process of integrating multi-sourced sensors for supporting natural disaster management, particularly an urban flood response. The results highlight sensor information integration as a needing emphasis and less focused area in the pathway for sensor data enablement of flood management.
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    Spatio-Temporal Event Detection Using Probabilistic Graphical Models (PGMs)
    Mousavi, A ; Duckham, M ; Kotagiri, R ; Rajabifard, A (IEEE, 2013)
    Event detection concerns identifying occurrence of interesting events which are meaningful and understandable. In dynamic fields, as time passes the attribute of phenomenon varies in spatial locations. Detecting events in dynamic fields requires an approach to deal with the highly granular data arriving in real time. This paper proposes a spatiotemporal event detection algorithm in dynamic fields which are monitored by wireless sensor networks (WSNs). The algorithm provides a method using probabilistic graphical models (PGMs) in WSNs to cope with the uncertainty of sensor readings. The algorithm incorporates the ability of Markov chains in temporal dependency modelling and Markov random fields theory to model the spatial dependency of sensors in a distributed fashion. Experimental evaluation of the proposed algorithm demonstrates that the decentralized approach improves the F1-score to 82% and 29% better precision than simple threshold technique. In addition, the performance of the algorithm was evaluated and compared with respect to the scalability (in terms of communication complexity). In comparison with the centralized approach the decentralized algorithm can substantially improve the scalability of communication in wireless sensor networks.
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    Spatially Enabling Government – an International Challenge
    Williamson, I. P. ; Rajabifard, A. ; Wallace, J. ( 2007)
    The popular use of spatial technologies involves showing images and tracking assets and inventory in an increasing array of instruments, the most common being the ubiquitous mobile phone. These technologies penetrate into even low income poor countries, but their take-up and development concentrates in highly developed countries. This high-end use of these technologies will determine their future. Remarkable as these popular applications are, spatial technologies can also be used in even more dynamic, transformational ways. Transformational use of spatial technologies occurs when they are used to improve business processes of government, and assist delivery of policies for equitable taxation, conservation of natural resources and planning for rational growth. Use of this transformational capacity of spatial technologies in government creates a spatially enabled government (SEG). The major impediment to take-up of spatial information is counter-intuitive. We all use the new technology in our daily lives, but our capacity to understand the power of spatial information is remarkably small. In fact only about 1% of people in any society really understand spatial information with about 5% of people knowing something about the special technology. For 95% of people, spatial information and its supporting technologies is a mystery. Teaching people about spatial information and its technologies is therefore the first task in painting a vision of what is possible. The attractions of spatial technologies lie in how they present information, whether users rely on computers and the Internet, or on communications technologies. The adage of a “picture tells a thousand words” is now out of date. New digital pictures tell many stories, and, if the enabling platform is built, the pictures will become management tools of government. Spatial technologies are moving quickly. In Australia, since October 2006, Google Maps and Google Earth, combined with a geocoded national address
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    Spatial Data Integration Challenges: Australian Case Studies
    MOHAMMADI, H ; RAJABIFARD, A ; BINNS, A ; WILLIAMSON, I (Spatial Sciences Institute, 2007)