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

The efficient use of data from different sources for production and application of digital elevation models

The emphasis of the investigation reported in this thesis is on the use of digital elevation data of two resolutions originating from two different sources. The high resolution DEM was captured from aerial photographs (first source) at a scale of 1:30,000 and the low resolution DEM was captured from SPOT images (second source). It is well known that the resolution of DEM data depends a great deal on the scale of the images used. The technique for capturing DEMs is static measurement of the spot heights in a regular grid. The grid spacing of the high resolution DEM was 30 m, and of the low resolution DEM was 100 m. The aims of this thesis are as follows: 1. To assess the feasibility of using SPOT stereodata as a source of height information and merged with data from aerial photography. This is carried out by comparison of the elevation data derived from SPOT with the digital elevation data derived from aerial photography. From the comparison of these two sources of height information, some results are derived which show the possible heighting accuracy levels which can realistically be achieved. A systematic error in the estimated average of the elevation differences was found and many tests have been carried out to find the reasons for the presence of this systematic error. 2. To develop methods to manipulate the captured data. 2.1. Gross error (blunder) detection. Blunders made during the data capturing procedure affect the accuracy of the final product. Therefore it is necessary to trap and to remove them. A pointwise local self-checking blunder detection algorithm was developed in order to check the grid elevation data, particularly those which are derived from the second source. 2.2. Data coordinates transformation. The data must be transformed into a common projection in order to be directly comparable. The projection and coordinate systems employed are studied in this project, and the errors caused by the transformations are estimated. 2.3. Data merging. Data of different reliability have to be merged into a single set of data. In this project data from two different sources are merged in order to create a final product of known and uniform accuracy. The effect of the lower resolution source on the high resolution source was studied, in dense and in sparse form. 2.4. Data structure. To structure the data by changing the format in order to be in an acceptable form for DEM creation and display, through the commercially available Laser-Scan package DTMCREATE. 3. DEM production and contouring. To produce DEMs from the initial data and that derived from the two merged sources, and to find the accuracy of the interpolation procedure by comparing the derived interpolated data with the high resolution DEM which has been derived from aerial photography. Finally to interpolate contours directly from the "raw" SPOT data and to compare them with those derived from the aerial photography in order to find out the feasibility and capability of using SPOT data in contouring for topographic maps

Issues on distributed caching of spatial data

Die Menge an digitalen Informationen über Orte hat bis heute rapide zugenommen. Mit der Verbreitung mobiler, internetfähiger Geräte kann nun jederzeit und von überall auf diese Informationen zugegriffen werden. Im Zuge dieser Entwicklung wurden zahlreiche ortsbasierte Anwendungen und Dienste populär. So reihen sich digitale Einkaufsassistenten und Touristeninformationsdienste sowie geosoziale Anwendungen in der Liste der beliebtesten Vertreter. Steigende Benutzerzahlen sowie die rapide wachsenden Datenmengen, stellen ernstzunehmende Herausforderungen für die Anbieter ortsbezogener Informationen dar. So muss der Datenbereitstellungsprozess effizient gestaltet sein, um einen kosteneffizienten Betrieb zu ermöglichen. Darüber hinaus sollten Ressourcen flexibel genug zugeordnet werden können, um Lastungleichgewichte zwischen Systemkomponenten ausgleichen zu können. Außerdem müssen Datenanbieter in der Lage sein, die Verarbeitungskapazitäten mit steigender und fallender Anfragelast zu skalieren. Mit dieser Arbeit stellen wir einen verteilten Zwischenspeicher für ortsbasierte Daten vor. In dem verteilten Zwischenspeicher werden Replika der am häufigsten verwendeten Daten von mehreren unabhängigen Servern im flüchtigen Speicher vorgehalten. Mit unserem Ansatz können die Herausforderungen für Anbieter ortsbezogener Informationen wie folgt addressiert werden: Zunächst sorgt eine speziell für die Zugriffsmuster ortsbezogener Anwendungen konzipierte Zwischenspreicherungsstragie für eine Erhöhung der Gesamteffizienz, da eine erhebliche Menge der zwischengespeicherten Ergebnisse vorheriger Anfragen wiederverwendet werden kann. Darüber hinaus bewirken unsere speziell für den Geo-Kontext entwickelten Lastbalancierungsverfahren den Ausgleich dynamischer Lastungleichgewichte. Letztlich befähigen unsere verteilten Protokolle zur Hinzu- und Wegnahme von Servern die Anbieter ortsbezogener Informationen, die Verarbeitungskapazität steigender oder fallender Anfragelast anzupassen. In diesem Dokument untersuchen wir zunächst die Anforderungen der Datenbereitstellung im Kontext von ortsbasierten Anwendungen. Anschließend diskutieren wir mögliche Entwurfsmuster und leiten eine Architektur für einen verteilten Zwischenspeicher ab. Im Verlauf dieser Arbeit, entstanden mehrere konkrete Implementierungsvarianten, die wir in diesem Dokument vorstellen und miteinander vergleichen. Unsere Evaluation zeigt nicht nur die prinzipielle Machbarkeit, sondern auch die Effektivität von unserem Caching-Ansatz für die Erreichung von Skalierbarkeit und Verfügbarkeit im Kontext der Bereitstellung von ortsbasierten Daten

Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality

Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants

Online Super-Resolution For Fibre-Bundle-Based Confocal Laser Endomicroscopy

Probe-based Confocal Laser Endomicroscopy (pCLE) produces microscopic images enabling real-time in vivo optical biopsy. However, the miniaturisation of the optical hardware, specifically the reliance on an optical fibre bundle as an imaging guide, fundamentally limits image quality by producing artefacts, noise, and relatively low contrast and resolution. The reconstruction approaches in clinical pCLE products do not fully alleviate these problems. Consequently, image quality remains a barrier that curbs the full potential of pCLE. Enhancing the image quality of pCLE in real-time remains a challenge. The research in this thesis is a response to this need. I have developed dedicated online super-resolution methods that account for the physics of the image acquisition process. These methods have the potential to replace existing reconstruction algorithms without interfering with the fibre design or the hardware of the device. In this thesis, novel processing pipelines are proposed for enhancing the image quality of pCLE. First, I explored a learning-based super-resolution method that relies on mapping from the low to the high-resolution space. Due to the lack of high-resolution pCLE, I proposed to simulate high-resolution data and use it as a ground truth model that is based on the pCLE acquisition physics. However, pCLE images are reconstructed from irregularly distributed fibre signals, and grid-based Convolutional Neural Networks are not designed to take irregular data as input. To alleviate this problem, I designed a new trainable layer that embeds Nadaraya- Watson regression. Finally, I proposed a novel blind super-resolution approach by deploying unsupervised zero-shot learning accompanied by a down-sampling kernel crafted for pCLE. I evaluated these new methods in two ways: a robust image quality assessment and a perceptual quality test assessed by clinical experts. The results demonstrate that the proposed super-resolution pipelines are superior to the current reconstruction algorithm in terms of image quality and clinician preference

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

Microscope Embedded Neurosurgical Training and Intraoperative System

In the recent years, neurosurgery has been strongly influenced by new technologies. Computer Aided Surgery (CAS) offers several benefits for patients\u27 safety but fine techniques targeted to obtain minimally invasive and traumatic treatments are required, since intra-operative false movements can be devastating, resulting in patients deaths. The precision of the surgical gesture is related both to accuracy of the available technological instruments and surgeon\u27s experience. In this frame, medical training is particularly important. From a technological point of view, the use of Virtual Reality (VR) for surgeon training and Augmented Reality (AR) for intra-operative treatments offer the best results. In addition, traditional techniques for training in surgery include the use of animals, phantoms and cadavers. The main limitation of these approaches is that live tissue has different properties from dead tissue and that animal anatomy is significantly different from the human. From the medical point of view, Low-Grade Gliomas (LGGs) are intrinsic brain tumours that typically occur in younger adults. The objective of related treatment is to remove as much of the tumour as possible while minimizing damage to the healthy brain. Pathological tissue may closely resemble normal brain parenchyma when looked at through the neurosurgical microscope. The tactile appreciation of the different consistency of the tumour compared to normal brain requires considerable experience on the part of the neurosurgeon and it is a vital point. The first part of this PhD thesis presents a system for realistic simulation (visual and haptic) of the spatula palpation of the LGG. This is the first prototype of a training system using VR, haptics and a real microscope for neurosurgery. This architecture can be also adapted for intra-operative purposes. In this instance, a surgeon needs the basic setup for the Image Guided Therapy (IGT) interventions: microscope, monitors and navigated surgical instruments. The same virtual environment can be AR rendered onto the microscope optics. The objective is to enhance the surgeon\u27s ability for a better intra-operative orientation by giving him a three-dimensional view and other information necessary for a safe navigation inside the patient. The last considerations have served as motivation for the second part of this work which has been devoted to improving a prototype of an AR stereoscopic microscope for neurosurgical interventions, developed in our institute in a previous work. A completely new software has been developed in order to reuse the microscope hardware, enhancing both rendering performances and usability. Since both AR and VR share the same platform, the system can be referred to as Mixed Reality System for neurosurgery. All the components are open source or at least based on a GPL license