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In the realm of autonomous systems and smart-city initiatives, accurately detecting and localizing pole-like objects (PLOs) such as electrical poles and traffic signs has become crucial. Despite their significance, the diverse nature of PLOs complicates their accurate recognition. Point cloud data and 3D deep learning models offer a promising approach to PLO localization under varied lighting, addressing issues faced by camera systems. However, the distinct characteristics of different street scenes worldwide require infeasibly extensive training data for satisfactory results because of the nature of deep learning. This prohibitively increases the cost of lidar data capture and annotation. This paper introduces a novel few-shot learning framework for the classification of outdoor point cloud objects, leveraging a minimalistic approach that requires only a single support sample for effective classification. Central to our methodology is the development of Pole-NN, a Non-parametric Network that efficiently distinguishes between various PLOs and other road assets without the need for extensive training datasets traditionally associated with deep learning models. Additionally, we present the Parkville-3D Dataset, an annotated point cloud dataset we have captured and labelled, which addresses the notable scarcity of fine-grained PLO datasets. Our experimental results demonstrate the potential of our approach to utilize the intrinsic spatial relationships within point cloud data, promoting a more efficient and resource-conscious strategy for PLO classification. [ABSTRACT FROM AUTHOR]

Effective visualization of spatial data, especially in the realm of 3D cadastral visualization, relies on the utilization of optimal interaction techniques and user interfaces for navigating complex datasets and understanding property delineations. This paper synthesizes findings from diverse studies investigating the efficacy of interaction modalities and user interfaces in 3D visualization across various domains. Drawing parallels to the broader field of 3D visualization, particularly in interaction tasks and user interface paradigms, this paper examines the potential for advancing 3D cadastral visualization systems. The study identifies fundamental interaction tasks crucial for effective 3D cadastral visualization, including object manipulation, widget manipulation, and data selection and annotation. It evaluates a range of user interfaces, from traditional input methods to emerging technologies such as gesture-based interfaces and virtual reality (VR) headsets, highlighting their respective strengths and limitations.Embracing insights from comparative analyses of immersive and non-immersive scenarios, this paper reveals significant insights into the effectiveness of immersive environments, such as virtual reality and augmented reality, in enhancing user experience and task performance for 3D cadastral visualization. Additionally, it aims to address key challenges associated with visualizing 3D cadastral data in immersive environments by proposing a comprehensive framework for evaluating the effectiveness and utility of immersive visualization for 3D cadastral purposes. [ABSTRACT FROM AUTHOR]

Land administration systems are being modernised to streamline the cadastral data lodgement. However, in many jurisdictions, cadastral data are still stored as a flat file. This method of data storage has significant limitations in terms of effective access, management, query, and analysis of cadastral data. Therefore, this study elicited the requirements and proposed an approach to automate the cadastral data storage. The proposed approach was successfully implemented within the land registry organisation in Victoria, Australia and the database management system was rigorously tested. The outcomes can potentially contribute to the implementation of a similar data storage infrastructure in other jurisdictions. [ABSTRACT FROM AUTHOR]

In this work, we implemented line-of-sight (LoS) ray tracing functionality to investigate problems in millimetre-wave propagation modelling and network planning in 3D city model environments. First, we validated an existing LoS propagation probability model expressed as an exponential rule with the link distance. By fitting ray tracing simulation results under different scenarios to the model, the relationships between key parameters in the model and factors including the building density and the transmitter height were qualitatively analysed. Next, we developed a network planning framework for a multi-hop outdoor urban network by formulating a mixed-integer linear programming problem which minimises the overall deployment cost through optimal site selection. Taking the sets of potential site locations and potential links as inputs, we selected a subset of the sites that comprise a tree-structured network that satisfies all the user demands at a minimum deployment cost. We also analysed the time required for solving this optimisation problem in order to provide a prediction of the execution time for larger-sized problems. [ABSTRACT FROM AUTHOR]

Increasing population in urban areas and limitations of suitable lands for developing houses and urban infrastructure have led to the vertical development in cities. However, these developments are managed by a cadastral system which is mainly two-dimensional and cannot efficiently represent Rights, Restrictions, and Responsibilities (RRRs) in complex scenarios. In fact, a three-dimensional cadastre is required for efficiently registering and representing RRRs. In this paper, a 3D proximity analysis was proposed and implemented to determine RRRs and associated easement rights in non-topology-based data structures. This method can be used to investigate the surrounding spaces of a subject apartment unit or storage in a high-rise. The performance of the developed method was evaluated in a large complex high-rise in Tehran, Iran. The results confirmed that the proposed method can correctly identify the neighbor spaces in complex scenarios. [ABSTRACT FROM AUTHOR]

Building Information Models (e.g., IFC) and virtual 3D city models (e.g., CityGML) are revolutionising the way we manage information about our cities. However, the main focus of these models is on the physical and functional characteristics of urban properties and facilities, which neglects the legal and ownership aspects. In contrast, cadastral data models, such as the Land Administration Domain Model (LADM), have been developed for legal information management purposes and model legal objects such as ownership boundaries without providing correspondence to the object's physical attributes. Integration of legal and physical objects in the virtual 3D city and cadastral models would maximise their utility and flexibility to support different applications that require an integrated resource of both legal and physical information, such as urban space management and land development processes. The aim of this paper is to propose a data model that supports both legal and physical information of urban environments. The methodology to develop this data model is to extend the core cadastral data model and integrate urban features into the data model. The outcome of the research can be utilised to extend the current data models to increases their usability for different applications that require both legal and physical information. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) developments of land, such as complex high-rises, put enormous pressure on current land administration systems that have ad hoc approaches to 3D property management. These approaches are unable to support effective 3D storage, analysis and visualisation of property information. Effective visualisation is one of the essential components in realisation of a truly 3D cadastre. Currently, several 3D visualisation applications and cadastral prototypes have been developed around the world. However, they do not effectively represent ownership information in 3D because they have not been developed based on 3D cadastral visualisation requirements. After candidate 3D visualisation solutions were compared with user-derived visualisation criteria, a web-based 3D visualisation prototype was designed and developed. The functionality, usability and efficiency of the prototype were evaluated by potential users involved in the registration and management of property. While there was a high level of enthusiasm for the features of the prototype, the results also suggest further directions for development of 3D cadastral visualisation. [ABSTRACT FROM AUTHOR]

Cities are facing dramatic challenges due to population growth and the massive development of high-rises and complex structures, both above and below the ground surface. Decision-makers require access to an efficient land and property information system, which is digital, three-dimensional (3D), spatially accurate, and dynamic containing interests in land (rights, restrictions and responsibilities—RRRs) to manage the legal and physical complexities of urban environments. However, at present, building subdivision workflows only support the two-dimensional (2D) building subdivision plans in PDF or image formats. These workflows result in a number of issues, such as the plan preparation being complex, the examination process being labor intensive and requiring technical expertise, information not being easily reusable by all subdivision stakeholders, queries, analyses, and decision-making being inefficient, and the RRRs interpretation being difficult. The aim of this research is to explore the potential of using Building Information Modelling (BIM) and its open standards to support the building subdivision workflows. The research that is presented in this paper proposes a BIM-driven building subdivision workflow, evaluated through a case study in the state of Victoria, Australia. The results of the study confirmed that the proposed workflow could provide a feasible integrated mechanism for stakeholders to share, document, visualize, analyze, interpret, and reuse 3D digital cadastral data over the lifespan of a building subdivision project. [ABSTRACT FROM AUTHOR]