Multi-scale data storage schemes for spatial information systems

This thesis documents a research project that has led to the design and prototype implementation of several data storage schemes suited to the efficient multi-scale representation of integrated spatial data. Spatial information systems will benefit from having data models which allow for data to be viewed and analysed at various levels of detail, while the integration of data from different sources will lead to a more accurate representation of reality. The work has addressed two specific problems. The first concerns the design of an integrated multi-scale data model suited for use within Geographical Information Systems. This has led to the development of two data models, each of which allow for the integration of terrain data and topographic data at multiple levels of detail. The models are based on a combination of adapted versions of three previous data structures, namely, the constrained Delaunay pyramid, the line generalisation tree and the fixed grid. The second specific problem addressed in this thesis has been the development of an integrated multi-scale 3-D geological data model, for use within a Geoscientific Information System. This has resulted in a data storage scheme which enables the integration of terrain data, geological outcrop data and borehole data at various levels of detail. The thesis also presents details of prototype database implementations of each of the new data storage schemes. These implementations have served to demonstrate the feasibility and benefits of an integrated multi-scale approach. The research has also brought to light some areas that will need further research before fully functional systems are produced. The final chapter contains, in addition to conclusions made as a result of the research to date, a summary of some of these areas that require future work

Modeling and hexahedral meshing of cerebral arterial networks from centerlines

Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires extracting precise models of arteries from low-resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it encodes both the geometric and topological information and facilitates manual editing. In this work, we propose an automatic method to generate a structured hexahedral mesh suitable for CFD directly from centerlines. We addressed both the modeling and meshing tasks. We proposed a vessel model based on penalized splines to overcome the limitations inherent to the centerline representation, such as noise and sparsity. The bifurcations are reconstructed using a parametric model based on the anatomy that we extended to planar n-furcations. Finally, we developed a method to produce a volume mesh with structured, hexahedral, and flow-oriented cells from the proposed vascular network model. The proposed method offers better robustness to the common defects of centerlines and increases the mesh quality compared to state-of-the-art methods. As it relies on centerlines alone, it can be applied to edit the vascular model effortlessly to study the impact of vascular geometry and topology on hemodynamics. We demonstrate the efficiency of our method by entirely meshing a dataset of 60 cerebral vascular networks. 92% of the vessels and 83% of the bifurcations were meshed without defects needing manual intervention, despite the challenging aspect of the input data. The source code is released publicly

Regular Hierarchical Surface Models: A conceptual model of scale variation in a GIS and its application to hydrological geomorphometry

Environmental and geographical process models inevitably involve parameters that vary spatially. One example is hydrological modelling, where parameters derived from the shape of the ground such as flow direction and flow accumulation are used to describe the spatial complexity of drainage networks. One way of handling such parameters is by using a Digital Elevation Model (DEM), such modelling is the basis of the science of geomorphometry. A frequently ignored but inescapable challenge when modellers work with DEMs is the effect of scale and geometry on the model outputs. Many parameters vary with scale as much as they vary with position. Modelling variability with scale is necessary to simplify and generalise surfaces, and desirable to accurately reconcile model components that are measured at different scales. This thesis develops a surface model that is optimised to represent scale in environmental models. A Regular Hierarchical Surface Model (RHSM) is developed that employs a regular tessellation of space and scale that forms a self-similar regular hierarchy, and incorporates Level Of Detail (LOD) ideas from computer graphics. Following convention from systems science, the proposed model is described in its conceptual, mathematical, and computational forms. The RHSM development was informed by a categorisation of Geographical Information Science (GISc) surfaces within a cohesive framework of geometry, structure, interpolation, and data model. The positioning of the RHSM within this broader framework made it easier to adapt algorithms designed for other surface models to conform to the new model. The RHSM has an implicit data model that utilises a variation of Middleton and Sivaswamy (2001)’s intrinsically hierarchical Hexagonal Image Processing referencing system, which is here generalised for rectangular and triangular geometries. The RHSM provides a simple framework to form a pyramid of coarser values in a process characterised as a scaling function. In addition, variable density realisations of the hierarchical representation can be generated by defining an error value and decision rule to select the coarsest appropriate scale for a given region to satisfy the modeller’s intentions. The RHSM is assessed using adaptions of the geomorphometric algorithms flow direction and flow accumulation. The effects of scale and geometry on the anistropy and accuracy of model results are analysed on dispersive and concentrative cones, and Light Detection And Ranging (LiDAR) derived surfaces of the urban area of Dunedin, New Zealand. The RHSM modelling process revealed aspects of the algorithms not obvious within a single geometry, such as, the influence of node geometry on flow direction results, and a conceptual weakness of flow accumulation algorithms on dispersive surfaces that causes asymmetrical results. In addition, comparison of algorithm behaviour between geometries undermined the hypothesis that variance of cell cross section with direction is important for conversion of cell accumulations to point values. The ability to analyse algorithms for scale and geometry and adapt algorithms within a cohesive conceptual framework offers deeper insight into algorithm behaviour than previously achieved. The deconstruction of algorithms into geometry neutral forms and the application of scaling functions are important contributions to the understanding of spatial parameters within GISc

DESENVOLVIMENTO DE UMA PLATAFORMA DE SOFTWARE PARA A MODELAGEM DIGITAL DE TERRENOS BASEADA EM TIN

Superfícies topográficas podem ser representadas com um bom grau de precisão pormeio de mapas. No entanto, estes nem sempre são as melhores ferramentas para acompreensão de relevos mais complexos. Nesse sentido, a maior contribuição dessetrabalho é a especificação e implementação da arquitetura de uma plataforma desoftware opensource voltado para a representação de modelos digitais de terrenosbaseado em TIN (Triangular Irregular Network), segundo os paradigmas daprogramação orientada a objetos e programação genérica e que possibilitaram aintegração de várias ferramentas de linguagem aberta (opensource), tais comoGDAL, OGR, OpenGL, OpenSceneGraph e Qt. Além disso, o núcleo derepresentação da arquitetura tem a capacidade de trabalhar com múltiplas estruturasde dados topológicas que permitem extrair em tempo constante, todas as relações deconectividade entre as entidades vértices, arestas e faces, presentes numa subdivisãoplanar triangular, facilitando enormemente a implementação de aplicações de temporeal. Esta capacidade é muito importante, por exemplo, na utilização de dados delevantamentos a laser (Lidar, ALS, TLS), possibilitando a geração de modelos demalhas triangulares da ordem de milhões de pontos

Scale, Resolution and Resampling: Representation and Analysis of Remotely Sensed Landscapes Across Scale in Geographic Information Systems.

Earth system scientists are increasingly using the technologies of Geographic Information Systems (GIS) and Remote Sensing (RS) in their analyses of earth system processes and patterns. These investigations take place over a wide range of scales, from the local to the global. Global change researchers focus on both the physical and human dimensions of changes in the earth\u27s landscapes, which occur across a range of scales and may be scale dependent. The way in which landscapes are represented in GIS and RS, using specific spatial data models and data spatial resolutions, affects the subsequent analyses that can be performed. Optimally those analyses are grounded in firm geographical and spatial analytical principles, so as to be appropriate and therefore meaningful interpretations of the data. This research investigates two specific issues of importance to research investigating landscape change across scale, those of resampling and analysis. Four different resampling algorithms, which are used to rescale remotely sensed pixels from higher to lower spatial resolutions, are investigated using Landsat TM data representing the Flint Hills region of Kansas. Two analytical methods for examining scale effects in RS data, local variance analysis and fractal analysis, are used to examine both the effects of the resampling methods on subsequent analyses and the performance of the methods in detecting potential scales of action in the landscapes. Results show differences in the resampling methodologies, which affect the subsequent analyses in different manners. The averaging and convolution methods performed comparably, and are the most reliable type of algorithm examined in this study. Their ongoing use in resampling processes is recommended, recognizing their limitations. The systematic sampling method is not recommended as a resampling procedure. The TM-to-MODIS algorithm, based on the optical properties of the two different resolution sensors, is potentially useful, although the algorithm behaved erratically at times. Both the fractal and local variance methods performed comparably to indicate scale effects in the data, with corresponding results to each other and to the statistical information on the images. As such both methods are deemed appropriate for examining landscapes across scale

Towards extracting artistic sketches and maps from digital elevation models

The main trend of computer graphics is the creation of photorealistic images however, there is increasing interest in the simulation of artistic and illustrative techniques. This thesis investigates a profile based technique for automatically extracting artistic sketches from regular grid digital elevation models. The results resemble those drawn by skilled cartographers and artists.The use of cartographic line simplification algorithms, which are usually applied to complex two-dimensional lines such as coastlines, allow a set of most important points on the terrain surface to be identified, these form the basis for sketching.This thesis also contains a wide ranging review of terrain representation techniques and suggests a new taxonomy