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ItemAdvanced principles of 3D cadastral data modellingAIEN, ALI ; Kalantari, Mohsen ; RAJABIFARD, ABBAS ; WILLIAMSON, IAN ; BENNETT, ROHAN (FIG, 2011)Current cadastral data models use a 2D land-parcel definition and extend it to cover 3D requirements. This approach cannot adequately manage and represent the spatial extent of 3D land rights, restrictions and responsibilities (3D RRRs). This paper aims to develop a 3D Cadastral Data Model (3DCDM) to configure 3D cadastral frameworks, manage and represent 3D RRRs, and facilitate 3D cadastre implementation. Three underlying principles have been proposed to develop the 3D Cadastral Data Model (3DCDM). These principles are: • Principle 1: The 2D cadastral data model is a sub-set of the 3D cadastral data model, • Principle 2: The 3D cadastral data model should not only accommodate 3D RRRs and their association with physical objects: the data model should also represent the spatial extent of 3D RRRs, and; • Principle 3: The 3D cadastre data model should cater for a broad range of land administration functions including land tenure, land value, land use, and land development with sufficient detail. These principles are used to assess and modify the core cadastral data model. Additionally, principles related to the legal property object are also used to modify the 3DCDM. The legal property object combines interests and its spatial dimension into a single entity. This creates more flexibility and enables inclusion of complex commodities and all kinds of RRRs. The first version of a 3D Cadastral Data Model (3CDM_Version 1.0) is provided at the end of this paper. 3DCDM maintains both legal and physical parts of 3D objects. The data model has wider application than the traditional requirements of cadastral systems: it is also usable in applications such as urban planning and disaster management.
ItemBrave new world: innovative tools for spatially enabling land administrationBENNETT, ROHAN (University of Melbourne, The Centre for SDIs and Land Administration, 2007)Introduction The term silo effect gained prominence in government and business circles during the 1990s (Williamson, 2007). It denotes the entrenched lack of communication and collaboration between organisations and their systems. For decades private organisations held onto their capital, information and skills for internal use only. All this changed with the introduction of information and communication technologies: by sharing resources with its business partners and customers a company could decrease costs, streamline processes and create better customer relations. The silo effect had to be overcome. The field of land administration was created in part in response to discussions about the silo effect. It was clear that the institutions dealing with tenure registration, cadastral mapping, natural resource management and so on, needed to be united. Integration of their theories, processes and information would result in better land management. The collaboration of ideas began in the late 1990s and has resulted in academic theories being used to enhance understandings of practical issues: for example hierarchal spatial reasoning has been applied to spatial data infrastructures (Rajabifard, 2002), policy design concepts to land policies (Ting, 2002), benchmarking to land administration systems (Steudler, 2003), cost benefit analysis to decision making about land (Paez, 2005). Organizational theory has advanced collaboration within land administration agencies (Warnest, 2005; McDougall, 2006) and tenure theories have been applied to the rural parts of developing countries (Dalrymple, 2006). Land administration is now multidisciplinary: its ability to use of the tools and theories of diverse disciplines has been its underlying strength. This chapter takes a similar approach: it looks at new theories and concepts from outside the discipline that will assist in spatially enabling land administration. Particularly, the management of the hundreds of new land rights, restrictions and responsibilities that exist over land. Ontological design, social learning, spatial technologies and uncertainty theory are four areas worthy of consideration. Each could profoundly impact upon existing land administration systems.