Individual accessibility and travel possibilities: A literature review on time geography

In the late 1960s, Torsten Hägerstrand introduced the conceptual framework of time geography which can be deemed an elegant tool for analysing individual movement in space and time. About a decade later, the auspicious time-geographic research has gradually lost favour, mainly due to the unavailability of robust geocomputational tools and the lack of georeferenced individual-level travel data. It was only from the early 1990s that new GISbased research gave evidence of resurgence in popularity of the field. From that time on, several researchers have steadily been publishing work at the intersection of time geography, disaggregate travel modeling, and GI-science. This paper reviews the most important timegeographic contributions. From this exercise, some prevailing research gaps are deduced and a way to deal with these gaps is presented. In particular, we focus on space-time accessibility measures, geovisualisation of activity patterns, human extensibility and fuzzy space-time prisms in relation to CAD

Wireless sensor data processing for on-site emergency response

This thesis is concerned with the problem of processing data from Wireless Sensor Networks (WSNs) to meet the requirements of emergency responders (e.g. Fire and Rescue Services). A WSN typically consists of spatially distributed sensor nodes to cooperatively monitor the physical or environmental conditions. Sensor data about the physical or environmental conditions can then be used as part of the input to predict, detect, and monitor emergencies. Although WSNs have demonstrated their great potential in facilitating Emergency Response, sensor data cannot be interpreted directly due to its large volume, noise, and redundancy. In addition, emergency responders are not interested in raw data, they are interested in the meaning it conveys. This thesis presents research on processing and combining data from multiple types of sensors, and combining sensor data with other relevant data, for the purpose of obtaining data of greater quality and information of greater relevance to emergency responders. The current theory and practice in Emergency Response and the existing technology aids were reviewed to identify the requirements from both application and technology perspectives (Chapter 2). The detailed process of information extraction from sensor data and sensor data fusion techniques were reviewed to identify what constitutes suitable sensor data fusion techniques and challenges presented in sensor data processing (Chapter 3). A study of Incident Commanders’ requirements utilised a goal-driven task analysis method to identify gaps in current means of obtaining relevant information during response to fire emergencies and a list of opportunities for WSN technology to fill those gaps (Chapter 4). A high-level Emergency Information Management System Architecture was proposed, including the main components that are needed, the interaction between components, and system function specification at different incident stages (Chapter 5). A set of state-awareness rules was proposed, and integrated with Kalman Filter to improve the performance of filtering. The proposed data pre-processing approach achieved both improved outlier removal and quick detection of real events (Chapter 6). A data storage mechanism was proposed to support timely response to queries regardless of the increase in volume of data (Chapter 7). What can be considered as “meaning” (e.g. events) for emergency responders were identified and a generic emergency event detection model was proposed to identify patterns presenting in sensor data and associate patterns with events (Chapter 8). In conclusion, the added benefits that the technical work can provide to the current Emergency Response is discussed and specific contributions and future work are highlighted (Chapter 9)

OPTIMIZATION OF STATION LOCATIONS AND TRACK ALIGNMENTS FOR RAIL TRANSIT LINES

Designing urban rail transit systems is a complex problem, which involves the determination of station locations, track geometry, right-of-way type, and various other system characteristics. The existing studies overlook the complex interactions between railway alignments and station locations in a practical design process. This study proposes a comprehensive methodology that helps transit planners to concurrently optimize station locations and track alignments for an urban rail transit line. The modeling framework resolves the essential trade-off between an economically efficient system with low initial and operation cost and an effective system that provides convenient service for the public. The proposed method accounts for various geometric requirements and real-world design constraints for track alignment and stations plans. This method integrates a genetic algorithm (GA) for optimization with comprehensive evaluation of various important measures of effectiveness based on processing Geographical Information System (GIS) data. The base model designs the track alignment through a sequence of preset stations. Detailed assumptions and formulations are presented for geometric requirements, design constraints, and evaluation criteria. Three extensions of the base model are proposed. The first extension explicitly incorporates vehicle dynamics in the design of track alignments, with the objective of better balancing the initial construction cost with the operation and user costs recurring throughout the system's life cycle. In the second extension, an integrated optimization model of rail transit station locations and track alignment is formulated for situations in which the locations of major stations are not preset. The concurrent optimization model searches through additional decision variables for station locations and station types, estimate rail transit demand, and incorporates demand and station cost in the evaluation framework. The third extension considers the existing road network when selecting sections of the alignment. Special algorithms are developed to allow the optimized alignment to take advantage of links in an existing network for construction cost reduction, and to account for disturbances of roadway traffic at highway/rail crossings. Numerical results show that these extensions have significantly enhanced the applicability of the proposed optimization methodology in concurrently selecting rail transit station locations and generating track alignment

A geographic knowledge discovery approach to property valuation

This thesis involves an investigation of how knowledge discovery can be applied in the area Geographic Information Science. In particular, its application in the area of property valuation in order to reveal how different spatial entities and their interactions affect the price of the properties is explored. This approach is entirely data driven and does not require previous knowledge of the area applied. To demonstrate this process, a prototype system has been designed and implemented. It employs association rule mining and associative classification algorithms to uncover any existing inter-relationships and perform the valuation. Various algorithms that perform the above tasks have been proposed in the literature. The algorithm developed in this work is based on the Apriori algorithm. It has been however, extended with an implementation of a ‘Best Rule’ classification scheme based on the Classification Based on Associations (CBA) algorithm. For the modelling of geographic relationships a graph-theoretic approach has been employed. Graphs have been widely used as modelling tools within the geography domain, primarily for the investigation of network-type systems. In the current context, the graph reflects topological and metric relationships between the spatial entities depicting general spatial arrangements. An efficient graph search algorithm has been developed, based on the Djikstra shortest path algorithm that enables the investigation of relationships between spatial entities beyond first degree connectivity. A case study with data from three central London boroughs has been performed to validate the methodology and algorithms, and demonstrate its effectiveness for computer aided property valuation. In addition, through the case study, the influence of location in the value of properties in those boroughs has been examined. The results are encouraging as they demonstrate the effectiveness of the proposed methodology and algorithms, provided that the data is appropriately pre processed and is of high quality

An intelligent classification system for land use and land cover mapping using spaceborne remote sensing and GIS

The objectives of this study were to experiment with and extend current methods of Synthetic Aperture Rader (SAR) image classification, and to design and implement a prototype intelligent remote sensing image processing and classification system for land use and land cover mapping in wet season conditions in Bangladesh, which incorporates SAR images and other geodata. To meet these objectives, the problem of classifying the spaceborne SAR images, and integrating Geographic Information System (GIS) data and ground truth data was studied first. In this phase of the study, an extension to traditional techniques was made by applying a Self-Organizing feature Map (SOM) to include GIS data with the remote sensing data during image segmentation. The experimental results were compared with those of traditional statistical classifiers, such as Maximum Likelihood, Mahalanobis Distance, and Minimum Distance classifiers. The performances of the classifiers were evaluated in terms of the classification accuracy with respect to the collected real-time ground truth data. The SOM neural network provided the highest overall accuracy when a GIS layer of land type classification (with respect to the period of inundation by regular flooding) was used in the network. Using this method, the overall accuracy was around 15% higher than the previously mentioned traditional classifiers. It also achieved higher accuracies for more classes in comparison to the other classifiers. However, it was also observed that different classifiers produced better accuracy for different classes. Therefore, the investigation was extended to consider Multiple Classifier Combination (MCC) techniques, which is a recently emerging research area in pattern recognition. The study has tested some of these techniques to improve the classification accuracy by harnessing the goodness of the constituent classifiers. A Rule-based Contention Resolution method of combination was developed, which exhibited an improvement in the overall accuracy of about 2% in comparison to its best constituent (SOM) classifier. The next phase of the study involved the design of an architecture for an intelligent image processing and classification system (named ISRIPaC) that could integrate the extended methodologies mentioned above. Finally, the architecture was implemented in a prototype and its viability was evaluated using a set of real data. The originality of the ISRIPaC architecture lies in the realisation of the concept of a complete system that can intelligently cover all the steps of image processing classification and utilise standardised metadata in addition to a knowledge base in determining the appropriate methods and course of action for the given task. The implemented prototype of the ISRIPaC architecture is a federated system that integrates the CLIPS expert system shell, the IDRISI Kilimanjaro image processing and GIS software, and the domain experts' knowledge via a control agent written in Visual C++. It starts with data assessment and pre-processing and ends up with image classification and accuracy assessment. The system is designed to run automatically, where the user merely provides the initial information regarding the intended task and the source of available data. The system itself acquires necessary information about the data from metadata files in order to make decisions and perform tasks. The test and evaluation of the prototype demonstrates the viability of the proposed architecture and the possibility of extending the system to perform other image processing tasks and to use different sources of data. The system design presented in this study thus suggests some directions for the development of the next generation of remote sensing image processing and classification systems

Ghana airborne geophysics project in the Volta and Keta Basin : BGS final report

This report describes the work undertaken by BGS between November 2006 and March 2009 in collaboration with Fugro Airborne Surveys Pty Ltd on an airborne geophysical survey and ground reconnaissance mapping of the Volta River and Keta Basins, Ghana. The project was supported by the EU as part of the Mining Sector Support Programme, Project Number 8ACP GH 027/13. The initial contract duration was three years, but this was extended by five months to account for acquisition of gravity data by another project. Some parts of Ghana have been airborne surveyed as part of the Mining Sector Development and Environmental Project, co-funded by the World Bank and the Nordic Development Fund, but no work was carried out on the Volta River and Keta basins, which together form a major portion of the Ghanaian territory. The approximate areas covered by the surveys are estimated at 98,000 km² for the satellite imagery and the airborne geophysics, except for the Time Domain Electromagnetic (TDEM) survey which was limited to 60,000 km². The main beneficiary of this project is the Geological Survey Department, GSD. The work enhanced its geological infrastructure and its personnel received hands-on training on modern geological mapping technology. Indirect beneficiaries were the mining and exploration companies that can follow up the reconnaissance work with detailed exploration work. The project was conducted in five phases, and this document reports on the BGS input to Phase 1, 4 and 5, with no inputs required in Phases 2 and 3: • Phase1: geological outline through Radar and optical satellite imageries. • Phase 2: airborne geophysical survey over the two basins for magnetics and Gamma Ray spectrometry (Fugro survey). • Phase 3: airborne electromagnetic and magnetic geophysical survey of specific areas, following the completion and interpretation of phase 2, using fixed wing time domain technology (Fugro survey). • Phase 4: interpretation of the combined geology and geophysics. • Phase 5: production of factual and interpretation maps. The full list of BGS products is outlined in Table 1 below, while Jordan et al. (2006) describe the products delivered on schedule in Phase 1

A Methodology for Natural Resources Analysis Appropriate for County Level Planning

In this thesis a methodology for developing an integrated cumulative analysis of sensitive natural resources was developed. Themes of natural resources-waterways, wetlands, forested lands, prime agricultural soils, and steep slopes-were brought together in a GIS system, in a grid format, in a manner so that each cell of the grid accumulated value according to the increasing presence of resource themes. For example, an area (30 meter x 30 meter grid cell) containing only one of the above themes is given a value of l, whereas an area containing slopes, streams, and forests might, after weighting factors, have a value of 5. The result is a map that demonstrates the cumulative value of sensitivity of a given area and its relative relation to the landscape under analysis. The methodology uses off-the-shelf GIS software and available GIS data sources, and is designed to require a minimum of technical and financial resources. This methodology is particularly useful for counties in Tennessee in meeting the requirements of Public Chapter 1101, the Growth Policy Act. The case study for this thesis reveals that much development does, in fact, occur in sensitive natural areas and that, therefore, this tool could be well utilized by planners to inform the public and to assist in the development of policy aimed toward the protection of sensitive areas from activities that would reduce their capacity to serve their natural functions

Wireless Play and Unexpected Innovation

Part of the Volume on Digital Young, Innovation, and the Unexpected. This chapter considers play as leading to unexpected innovation in advanced wireless technologies. It concludes that much of the potential for new media to enhance innovation actually echoes much older patterns, as evidenced by comparisons to wireless history. These are patterns of privilege, particularly class and gender privilege, reinforced by strict intellectual property protections. Detailed case studies are presented of the "wardrivers," young male computer enthusiasts who helped map wi-fi signals over the past decade, and of earlier analog wireless enthusiasts. The chapter offers a solid critique of many present-day celebrations of technology-driven innovation and of the rhetoric of participatory culture

Transit Feasibility Study for Chesterfield County, VA

This capstone presents a transit feasibility study for Chesterfield County, VA in partial fulfillment of the requirements for the Master of Urban and Regional Planning in the VCU Wilder School of Government and Public Affairs. GRTC Transit System (GRTC) is the primary public transportation operator for the Richmond region. In 2016, the Greater Richmond Transit Vision Plan created a regional transit network that would guide cohesive future transit development in the region. This plan intends to support building the bridge between the existing state of transit in Chesterfield County and implementation of the transit vision plan. Through the completion of a transit propensity index, commuter analysis, and observance of activity density, the plan recommends transit routes for implementation in Chesterfield County

Turning data into information: assessing and reporting GIS metadata integrity using integrated computing technologies

A Geographic Information System (GIS) serves as the tangible and intangible means by which spatially related phenomena can be created, analyzed and rendered. GIS metadata serves as the formal framework to catalog information about a GIS data set. Metadata is independent of the encoded spatial and attribute information. GIS metadata is a subset of electronic metadata which catalogs electronic resources such as web pages and software applications. However, GIS metadata is inherently different than electronic media because each metadata file can be applied to a spatial component that is not implicit with other forms of metadata. Using open source technologies such as R, Perl and PHP, metadata information for large GIS data sets (thousands of layers) can be gleaned quickly and more efficiently than the human element. In doing so, metrics to express the integrity of both the metadata and GIS data can be captured, displayed and compared for use in the decision making process. Supervised and unsupervised techniques allow users and computer algorithms to explore unseen trends about the GIS data not obvious to the human component. The validity of these analyses was tested using a Technology Acceptance Model (TAM). Responses from 40 GIS professionals about the results of this methodology were captured to find a relationship between this technology’s Perceived Ease of Use, Perceived Usefulness, Attitude Towards Using and the Intention to Further use this technology