Point clouds contain high detail and high accuracy geometry representation of the scanned Earth surface parts. To manage the huge amount of data, the point clouds are traditionally organized on location and map-scale; e.g. in an octree structure, where top-levels of the tree contain few points suitable for small scale overviews and lower levels of the tree contain more points suitable for large scale detailed views. The drawback of this solution is that it is based on discrete levels, causing visual artifacts in the form of data density shocks when creating the commonly used perspective views. This paper presents a method based on an optimized distribution of points over continuous levels, avoiding the visualization shocks. The traditional distribution ratio's of data amounts over discrete levels of raster or vector data is considered the reference. How to convert this to point clouds with continuous levels (still benefiting from the proven advantages of the data distribution in discrete levels for efficient access at a wide range of scales)? In our solution, for each point a cLoD (continuous Level of Detail) value is computed and added as dimension to the point. A SFC (Space Filling Curve)-based nD data clustering technique can be used to organize the points, so that they can be efficiently queried. It should be noted that also other multi-dimensional indexing and clustering techniques could be applied to realize continuous levels based on the cLoD value. Besides the mathematical foundation of the approach also several implementations are described, varying from a 3D web-browser based solution to an augmented reality point cloud app in a mobile phone. The cLoD enables interactive real-time visualization using perspective views without data density shocks, while supporting continuous zoom-in/out and progressive data streaming between server and client. The described cLoD based approach is generic and supports different types of point clouds: from airborne, terrestrial, mobile and indoor laser scanning, but also from dense matching optical imagery or multi-beam echo soundings.

Efficient spatial queries are frequently needed to extract useful information from massive nD point clouds. Most previous studies focus on developing solutions for orthogonal window queries, while rarely considering the polytope query. The latter query, which includes the widely adopted polygonal query in 2D, also plays a critical role in many nD spatial applications such as the perspective view selection. Aiming for an nD solution, this paper first formulates a convex nD-polytope for querying. Then, the paper integrates three approximate geometric algorithms – SWEEP, SPHERE, VERTEX, and a linear programming method CPLEX, developing a solution based on an Index-Organized Table (IOT) approach. IOT is applied with space filling curve based clustering and advanced querying mechanism which recursively refines hypercubic nD spaces to approach the query geometry for primary filtering. Results from experiments based on both synthetic and real data have confirmed the superior performance of SWEEP. However, the algorithm may lag behind CPLEX due to pessimistic intersection computation in high dimensional spaces. In a real application, by properly transforming a perspective view selection into a polytope query, the solution achieves a sub-second querying performance using SWEEP. In another flood risk query, SWEEP also leads the others. In general, the robust and efficient solution can be immediately used to address different polytope queries, including those abstract ones whose constraints on combinations of different dimensions are formed into a polytope model. Besides, the knowledge of high-dimensional computations acquired also provides significant guidance for handling more nD GIS issues.

The prime purpose of Cadastral data – whether in the form of maps, survey plans or notes, or a digital database is the definitive demarcation of the extent of properties – and can be seen primarily as a decision support facility (“Can a structure be built here?”, “Where can I build a fence?”, “Should I buy this property”?). There are, however many additional uses for which this information has been applied – such as a base for the recording of assets such as light poles, underground cables, etc. and as a history of the pattern of land use and subdivision. Although secondary, these uses are important, and should be adequately supported including the historic information. It is a fact that the determination of cadastral boundaries can only be carried out to a certain accuracy, and that that accuracy has been improving over time. Older surveys had been carried out with limited positional control, and using equipment with a low intrinsic accuracy by modern standards, although they correctly represent the topology between properties. As a result, later surveys provide an opportunity to improve the positioning of existing boundaries data without disturbing the topology of the existing data. In addition, engineering works such as road building, can provide a source of high accuracy position data that can be applied to improve low accuracy existing data. This argues that the accuracy of boundaries should be improved in the historic record of the cadastre – after all we would like to see our historic parcels in the position we now know them to have been, so that they are comparable with current boundaries. Likewise, we need to correct inaccuracies in the attributes of the spatial objects and the topology between them (e.g. which spatial units are adjacent to or near a given object). On the other hand, we must not lose sight of the decision-making side of the requirements – so that a past decision can be reviewed in relation to the data as it existed then. If the current knowledge in the database of today is used to review old decisions, they may seem irrational. Data custodians are well aware of this issue, using terms like “update” to indicate a “real-world” change, while using “upgrade” to indicate an improvement of the database representation not accompanied with a change “on the ground”; however database software has not carried this knowledge through – resulting in its loss. This argues for a database with bi-temporal history – where our current best knowledge of the history of the cadastre is recorded, and that history is corrected and maintained, while our past knowledge of the data also recorded as an audit trail (so that we can ask questions like “what did we in 2017 think the definition of this property was in 1994?”). This is realized via two types of time: database (or system) time and real world (or valid) time. The different historic records, combined with changes of datum, can lead to confusion in terminology – where words such as “point”, “position”, “boundary” become overloaded. This paper is intended to provoke discussion of terminology to clear up this confusion, and potentially to assist with an extension of the temporal model as input for the revision of LADM to accommodate bi-temporality.

This paper describes research into the design, development and visualization of mixed 2D and 3D Cadastre. A schema has been developed to accommodate this data, with provision for a time component. This paper describes the schema, the visualization requirements, and the provision of LADM-compatible views of the data for the purpose of developing the 3D Cadastral prototype. A significant volume of 2D + t Cadastral data, which also contained 2D + t footprint representations of 3D parcels, is currently incorporated in the Cadastral Database of Queensland. A moderate number of 3D building units, and a smaller number of volumetric parcels have been hand-encoded (from the survey plans), and added to this database. The mixture has been disseminated and displayed in KML through Cesium JS. The visualization of cadastral parcels in 3D is a challenge, since legal boundaries are, in many cases, invisible in the real world; so how can we properly represent something that is not visible to our eyes? This paper uses the results from research looking into problems of occlusion and ambiguous perception (in terms of position, size and shape) of objects in the context of 3D cadastre visualization. The exploration of specific interaction techniques is essential to overcome these issues. After an initial internal usability test (with colleagues/ friends of the developers) our 3D Cadastres web-based dissemination prototype was improved. Next a public usability test is carried out to obtain feedback from different groups of professional users (legal, survey, ICT backgrounds). During the test, the users are asked to perform a series of tasks typical of cadastral systems. Each task is accompanied by a description to give the users some context. Then, each user is asked to reflect on his or her experience. In this paper we present the main results of the public usability test of the 3D Cadastres web-based dissemination prototype.

Cadastral spatial units around the world range from simple 2D parcels to complex 3D collections of spaces, defined at levels of sophistication from textural descriptions to complete, rigorous mathematical descriptions based on measurements and coordinates. The most common spatial unit in a cadastral database is the 2D land parcel-the basic unit subject to cadastral Rights, Restrictions and Responsibilities (RRR). Built on this is a varying complexity of 3D subdivisions and secondary interests. Spatial units may also be subdivided into smaller units, with the remainder being kept as common property for the owners/tenants of the individual units. This has led to the adoption of hierarchical multi-level schemes. In this paper, we explore the encoding of spatial units in a way that highlights their 2D extent and topology, while fully defining their extent in the third dimension. Obviously, topological encoding itself is not new. However, having mixed a 2D and 3D topological structure is rather challenging. Therefore, despite the potential benefits of mixed 2D and 3D topology, it is currently not used in LandXML, one of the main and best documented formats when representing survey data. This paper presents a multi-level topological encoding for the purposes of survey plan representation in LandXML that is simple and efficient in space requirements, including the question of curved surfaces, (partly) unbounded spatial units, and grouping and division of 2D and 3D spatial units. No off the shelf software is available for validating newly lodged surveys and we present our prototype for this. It is further suggested that the conceptual model behind this encoding approach can be extend to the database schema itself.