Kevin McDougall

Development of validation rules to support digital lodgement of 3D cadastral plans

Abstract Validation is a familiar topic in computing, generally as a mechanism to protect a database from the effects of inappropriate data with the side effect of detecting some errors. As such, the validation rules are determined from the database schema using well understood methodologies. This paper takes a different view by examining digital validation as one of a set of processes that are designed to ensure that the incoming data (in this case, a plan of cadastral survey) is unambiguous and contains sufficient detail to define the legal spatial extents of a property. This is a complex question, especially since the rules and the decisions based on these processes must be defensible (therefore cannot contain arbitrary requirements imposed by a specific database model). Using the jurisdiction of Queensland, Australia, as a case study, this paper discusses the manual submission and lodgement of cadastral survey plans and the current 2D digital process as precursors to the automatic lodgement of all plans of survey. A set of validation rules is proposed for application to single geometric objects, to the relationship of objects on a single survey plan, and to objects that are independently defined on separate plans. It is asserted that, by the nature of the problem, this set is incomplete and will remain so. However, this research has identified a “checklist” of issues to be addressed by jurisdictions hoping to implement digital cadastral survey plan lodgement. The implications of this work in the context of the broader challenges in land administration and within the topic of 3D cadastral data are discussed.

SDI and crowdsourced spatial information management automation for disaster management

Abstract Modern disaster reporting is becoming increasingly sophisticated with the ready access to social media and user-friendly online mapping tools. Citizen engagement in location enabled disaster reporting is more obvious, and the availability of crowd generated geospatial data is higher than ever before. Crowd generated geospatial content is current and more diverse than conventional geographic information; however, quality and credibility issues exist. Although spatial data infrastructures (SDIs) have proven to be successful in supporting disaster management activities in the past, delays in providing public mapping portals and gaps in data are common. Crowd support and crowd generated spatial data have the potential to speed up disaster management actions and disaster mitigations. Within the study, crowd communications that occurred during the 2011 Queensland floods through the Australian Broadcasting Corporations (ABCs) QLD flood crisis map were critically analysed to investigate the readiness of current information sources to support disaster management. The accuracy of the reported event locations were compared to the authoritative Queensland Government street network, Open Street Maps (OSMs) streets and Google streets to compare the accuracy of the street and address names provided through the crowdsourced data. The study reveals that several issues exist regarding the quality of the data provided and the intent of the data provider. Moreover, the results indicate that the direct usage of reported location is problematic and that the semantic processing of the information location along with available spatial data may be required to improve data quality.

Data validation in 3D cadastre

In a cadastre, the 2D parcel is nowadays correctly considered to be a special case of the 3D parcel because the rights and restrictions extend beyond the surface it-self. Storing, representing and manipulating a true 3D parcel however has not yet been satisfactorily achieved because of constraints in data modeling and soft-ware development. Significant research has been done to identify the best ways to represent a 3D solid, with rigorous mathematical testing on the respective merits of alternative approaches. Software companies have come up with their own ways of storing and validating 3D data, mostly as extensions of the 2D concepts. However, validation rules of one software may not be acceptable within another softwares validation environment. The validation itself can be specified in great detail but sometimes this leads to redundant, repetitive or unnecessary processing. Because of the high volume of data a typical organization may be expected to handle, it is necessary for the rules to be streamlined and efficient. In this paper, validation is initially approached to answer questions such as: what is validation? why it is necessary to validate?, and how do we validate?. Limiting the scope to the 3D geometry or spatial representation of a 3D cadastre, the paper takes a novel approach in identifying the various aspects of validation of a 3D cadastral parcel and identifies the critical validation factors. It examines the validity within individual parcels and the relationship between adjoining or overlapping parcels in 2D or 3D. Although it is difficult to ensure completeness of rules, critical validation rules are examined for each identified factor.

Operational Infrastructure for Quality Distance and Online Geospatial Programs

The Surveying and Land Information Discipline at the University of Southern Queensland (USQ) has delivered full time and distance education programs in surveying and related areas for over 26 years. Academics at USQ have recently embarked on multimedia enhancement and online delivery of curricula to provide an even broader and more contemporary learning environment. These enhancements, when developed professionally, require a significant commitment of resources and expertise, and often necessitate a team approach to their design and development. Although there has been a proliferation of activity in the area of online delivery, little consideration has been given to the support infrastructure that is necessary to establish, deliver and maintain these offerings. This paper examines the operational infrastructure that is critical to distance education students receiving a comprehensive, timely and quality learning experience.

Reliability of a high accuracy image-based system for 3D modelling of the medial longitudinal arch during gait

The Medial Longitudinal Arch (MLA) is the largest arch of the foot and is regarded as the most important foot arch in clinical foot assessments due to its influence on lower limb function, foot stability and foot pain. Each foot is classified as either high arched, low arched or normally arched depending on the structure of the MLA. There are currently a number of techniques that are used to classify the foot in a static state based on measurements of the MLA. These static measurements are then used to predict the behaviour of the foot arch in a dynamic state. However, it is easy to identify limitations with these techniques as the shape of the MLA in a static state cannot predict the behaviour of the MLA during dynamic activities. Therefore, the aim of this chapter is to introduce a high accuracy 3D modelling system that has been developed to map the shape of the MLA during gait using high definition video camcorders. The objectives of the study were hence: (1) to determine whether changes can be detected along the MLA for different weight bearings during gait, (2) to test the accuracy and reliability of the developed imaging system for creating dynamic 3D models of the foot arch and (3) to determine the quality and suitability of the 3D model. The results of the study show that changes can be detected along the MLA during gait with a level of accuracy of less than 0.4 mm when a 3D model of the foot is generated in PhotoModeler Scanner.

VGI and crowdsourced data credibility analysis using spam email detection techniques

ABSTRACT Volunteered geographic information (VGI) can be considered a subset of crowdsourced data (CSD) and its popularity has recently increased in a number of application areas. Disaster management is one of its key application areas in which the benefits of VGI and CSD are potentially very high. However, quality issues such as credibility, reliability and relevance are limiting many of the advantages of utilising CSD. Credibility issues arise as CSD come from a variety of heterogeneous sources including both professionals and untrained citizens. VGI and CSD are also highly unstructured and the quality and metadata are often undocumented. In the 2011 Australian floods, the general public and disaster management administrators used the Ushahidi Crowd-mapping platform to extensively communicate flood-related information including hazards, evacuations, emergency services, road closures and property damage. This study assessed the credibility of the Australian Broadcasting Corporation’s Ushahidi CrowdMap dataset using a Naïve Bayesian network approach based on models commonly used in spam email detection systems. The results of the study reveal that the spam email detection approach is potentially useful for CSD credibility detection with an accuracy of over 90% using a forced classification methodology.

Vulnerability assessment and interdependency analysis of critical infrastructures for climate adaptation and flood mitigation

Purpose – The purpose of this paper is to present a novel approach that examines the vulnerability and interdependency of critical infrastructures using the network theory in geographic information system (GIS) setting in combination with literature and government reports. Specifically, the objectives of this study were to generate the network models of critical infrastructure systems (CISs), particularly electricity, roads and sewerage networks; to characterize the CISs’ interdependencies; and to outline the climate adaptation (CA) and flood mitigation measures of CIS. Design/methodology/approach – An integrated approach was undertaken in assessing the vulnerability and interdependency of critical infrastructures. A single system model and system-of-systems model were operationalized to examine the vulnerability and interdependency of the identified critical infrastructures in GIS environment. Existing CA and flood mitigation measures from government reports were integrated in the above-mentioned finding...

Exploring the application of some common raster scanning paths on lossless compression of elevation images

Raster scanning is a method for producing or recording a video or a digital image by means of a line-by-line sweep. The scanning process basically transforms a 2D image representation into a 1D representation. While such process has been extensively used for data transmission and storage as well as in most image displaying and capturing devices, its application to Digital Elevation Models (DEM) research is infrequent. A DEM is usually a square matrix of elevations (Elevation Image) except that it comprises a single channel of information (heights) and can be compressed in a lossy or lossless manner by way of current standard image compression protocols. Compression has the outcome of reducing memory requirements and speed of transmission over digital links, while preserving the integrity of data. In this context, this proof of concept paper investigates the effects of applying some different scanning paths to 16-bit elevation images of floating point height values representing dissimilar terrain characteristics. The intention is to discern whether different 1D representations of a given elevation image can provide a better correlation or similarity among elevation points, thus resulting in improved compression ratios and run decompression times.

Are equipment simulators effective when used for technology-based training?

Formal technology‐based training can be costly for all concerned. Efficient and effective alternatives to face‐to‐face training need to be found. One option is to use equipment simulators before undertaking formal training so that hands‐on training can be conducted at a more advanced level and thereby increase efficiency. Case studies using Global Positioning System (GPS) simulations were conducted to determine their effectiveness in technology‐based training. This paper demonstrates that it is possible to use equipment simulators to deliver effective training in the use of complicated technical equipment, and that the simulators can replace at least some of the conventional hands‐on training.

Relevance Assessment of Crowdsourced Data (CSD) Using Semantics and Geographic Information Retrieval (GIR) Techniques

Crowdsourced data (CSD) generated by citizens is becoming more popular as its potential utilization in many applications increases due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the data is not generated by professionals nor follows standard data-collection procedures. The quality of CSD can be assessed according to a range of characteristics including its relevance. In this paper, information relevance has been explored through using geographic information retrieval (GIR) techniques to identify the most highly relevant information from a set of crowdsourced data. This research tested a relevance assessment approach for CSD by adapting relevance assessment techniques available in the GIR domain. Thematic and geographic relevance were assessed by analyzing the frequency of selected terms which appeared in CSD reports using natural language processing techniques. The study analyzed crowdsourced reports from the 2011 Australian flood’s Crowdmap to examine a proof of concept on relevance assessment using a subset of this dataset based on a defined set of queries. The results determined that the thematic and geographic specificities of the queries were 0.44 and 0.67, respectively, which indicated the queries used were more geographically specific than thematically specific. The Spearman’s rho value of 0.62 indicated that the final ranked relevance lists showed reasonable agreement with a manually classified list and confirmed the potential of the approach for CSD relevance assessment. In particular, this research has contributed to the field of CSD relevance assessment through an integrated thematic and geographic relevance ranking process by using a user-query specificity approach to improve the final ranking.