The National Superficial Deposit Thickness Model. (Version 5)

The Superficial Deposits Thickness Model (SDTM) is a raster-based dataset designed to demonstrate the variation in thickness of Quaternary-age superficial deposits across Great Britain. Quaternary deposits (all unconsolidated material deposited in the last 2.6 million years) are of particular importance to environmental scientists and consultants concerned with our landscape, environment and habitats. The BGS has been generating national models of the thickness of Quaternary-age deposits since 2001, and this latest version of the model is based upon DiGMapGB-50 Version 5 geological mapping and borehole records registered with BGS before August 2008

Terrain modelling by kinematical GPS survey

This work presents the first results of an experiment aiming to derive a high resolution Digital Terrain Model (DTM) by kinematic GPS surveying. The accuracy of the DTM depends on both the operational GPS precision and the density of GPS samples. The operational GPS precision, measured in the field, is about 10cm. A Monte Carlo analysis is performed to study the dependence of the DTM error on the sampling procedure. The outcome of this analysis is that the accuracy of the topographic reconstruction is less than 1m even in areas with a density of samples as low as one sample per 100m², and becomes about 30cm in areas with at least one sample per 10m². The kinematic GPS technique gives a means for a fast and accurate mapping of terrain surfaces with an extension of a few km². Examples of application are the investigation of archaeological sites and the stability analysis of landslide prone areas

Application of Geographic Information Systems

The importance of Geographic Information Systems (GIS) can hardly be overemphasized in today’s academic and professional arena. More professionals and academics have been using GIS than ever – urban & regional planners, civil engineers, geographers, spatial economists, sociologists, environmental scientists, criminal justice professionals, political scientists, and alike. As such, it is extremely important to understand the theories and applications of GIS in our teaching, professional work, and research. “The Application of Geographic Information Systems” presents research findings that explain GIS’s applications in different subfields of social sciences. With several case studies conducted in different parts of the world, the book blends together the theories of GIS and their practical implementations in different conditions. It deals with GIS’s application in the broad spectrum of geospatial analysis and modeling, water resources analysis, land use analysis, infrastructure network analysis like transportation and water distribution network, and such. The book is expected to be a useful source of knowledge to the users of GIS who envision its applications in their teaching and research. This easy-to-understand book is surely not the end in itself but a little contribution to toward our understanding of the rich and wonderful subject of GIS

An Adjectival Interface for procedural content generation

Includes abstract.Includes bibliographical references.In this thesis, a new interface for the generation of procedural content is proposed, in which the user describes the content that they wish to create by using adjectives. Procedural models are typically controlled by complex parameters and often require expert technical knowledge. Since people communicate with each other using language, an adjectival interface to the creation of procedural content is a natural step towards addressing the needs of non-technical and non-expert users. The key problem addressed is that of establishing a mapping between adjectival descriptors, and the parameters employed by procedural models. We show how this can be represented as a mapping between two multi-dimensional spaces, adjective space and parameter space, and approximate the mapping by applying novel function approximation techniques to points of correspondence between the two spaces. These corresponding point pairs are established through a training phase, in which random procedural content is generated and then described, allowing one to map from parameter space to adjective space. Since we ultimately seek a means of mapping from adjective space to parameter space, particle swarm optimisation is employed to select a point in parameter space that best matches any given point in adjective space. The overall result, is a system in which the user can specify adjectives that are then used to create appropriate procedural content, by mapping the adjectives to a suitable set of procedural parameters and employing the standard procedural technique using those parameters as inputs. In this way, none of the control offered by procedural modelling is sacrificed â although the adjectival interface is simpler, it can at any point be stripped away to reveal the standard procedural model and give users access to the full set of procedural parameters. As such, the adjectival interface can be used for rapid prototyping to create an approximation of the content desired, after which the procedural parameters can be used to fine-tune the result. The adjectival interface also serves as a means of intermediate bridging, affording users a more comfortable interface until they are fully conversant with the technicalities of the underlying procedural parameters. Finally, the adjectival interface is compared and contrasted to an interface that allows for direct specification of the procedural parameters. Through user experiments, it is found that the adjectival interface presented in this thesis is not only easier to use and understand, but also that it produces content which more accurately reflects usersâ intentions

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