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Multipath is a major sidereally-repeating error affecting GPS. The repetition of satellite-receiver geometry approximately every sidereal day enables filtering to minimize multipath. Computing the exact error repeat interval using the day-to-day autocorrelation with a 10-hour window yields a consistent and steady value of 23h 55m 54s. A 2-hour window gives fluctuating lag values with >97% of the optimal lag's correlation, suggesting little advantage in using a satellite-specific or timevarying lag in double-difference processing. GPS data are filtered by stacking at the optimum lag, and applying, either coordinate residuals ("coordinate filtering"), or double-difference carrier phase residuals ("observation filtering"). Coordinate filtering yields better coordinate repeatability than observation filtering, but with similar hour-to-hour consistency. The variance reduction in a high multipath environment over a 24-hour dataset reaches 73%, using a 3-day coordinate-filter in a high multipath enviromnent. However, observation filtering requires less processing time to generate and apply the filter. As the time gap betweent he days generatingth e filter and the applied day increases, the variance reduction worsens gradually, reaching zero at a gap of -30 days. The optimal variance reduction (61% in a low multipath environment) is achieved by stacking seven days immediately before the applied day, but a stack of 3-9 days is acceptable. A switched-antenna array system may be adopted instead of continuous GPS for cost minimization. According to the used receivers' hardware, the optimum session interval to use is 119 seconds, which provides sufficient usable epochs per switch interval and is synchronized with the "sidereal" lag. Semi-continuous sidereallyfiltered GPS is efficient in detecting horizontal and vertical deformations in nearstatic enviromnents with high multipath to the millimetre level. In addition, the precision of the deforming stations improved, reaching to a precision better than 5 mm and 8 mm in the horizontal and vertical plane respectively. Hence, this provides the capability of monitoring slow moving deformations using a quick, cost-effective and precise GPS technique.

The Brazilian Atlantic Forest is one of the Earth's most endangered ecosystems. It has high biodiversity and a high level of plant and animal endemism. One of the largest remnants of that forest is located in the State of Sao Paulo. Most of the significant residual fragments of the State have been designated under various categories of conservation, the largest part of the area being composed of state parks. Information is recognised as a key tool for effective management of parks and protected areas and, therefore, for conservation. GIS is an information management tool which deals with spatial and non-spatial data, and it has been adopted by park organisations in the industrialised developed countries such as Canada and USA. Such information technology demands skilled human resources and budget commitment. However, the organisational and managerial context in tropical developing countries such as Brazil, is restricted by a shortage of adequate human resources and government funds for establishment and management, lack of continuity in policy and in support for parks and protected areas. Therefore, the adoption of GIS technology for the state parks in the State of Sao Paulo is likely to be constrained. However, the Appropriate Technology approach can offer a more comprehensive and adequate framework to deal with the issues of technology choice and implementation in circumstances where they are limited. Whist recognising the benefits of GIS, the precise context and timing of any possible installations demands more careful consideration than has been offered so far, either by the State of Sao Paulo or elsewhere in Brazil. A qualitative approach based on two case studies was adopted to collect and analyse data on issues of park organisation. The research findings suggest that human resource and government funding shortages are the critical issues. Some alternatives were identified, based on principles of Appropriate Technology. A start can be made using a PC mapping system such as a simple version of AutoCAD, which is now available in the park central agency. Furthermore the three State Universities could contribute in a more systematic manner in resource data collection and training. However, the inadequate salary policy, the lack of management and information plans, and administrative discontinuity may hinder the successful implementation and use of the spatial data handling system. A strong commitment to conservation issues is essential for the better management of parks and therefore for improved data management. Future research could profitably monitor the success of using AutoCAD or any other simpler automated data handling system before any more sophisticated method of GIS is adopted.

This thesis investigates the roles of computer modelling and writing in Geography undergraduates' learning about the system dynamics of social and environmental systems. It treats modelling as a cognitively and culturally novel practice that challenges conventional notions of the 'Three Rs'. A working conception of 'learning by modelling' is developed from a human evolutionary perspective on symbolic representation; an analysis of 'how maps work'; a conversational model of learning; recent science studies accounts of computational modelling, and a cultural literacy perspective on academic writing. The synthesised conception informs a critique of the pedagogic literatures on modelling in undergraduate Geography and introductory system dynamics, which are found to privilege formal reasoning and technical skills whilst relatively neglecting the roles of written assessment in student learning The empirical research is based on a one-semester, introductory module launched to improve the quality of undergraduates' written accounts of positive and negative feedback within systems. The study adopts a naturalistic and inductive strategy to investigate the outcomes of learning by modelling. Adapting methods of discourse and content analysis, it interprets the summatively assessed modelling project coursework reports of eleven participants with respect to the module's intended learning outcomes. Participants' adopted approaches ranged from the exploratory to the expressive, with different types and amounts of tutor involvement. Their modelling and writing activities are interpreted as serving to mediate personal and prior interests, the consulted literatures of their selected topics, the methods of introductory systems dynamics, and the institutional context. That is to say, modelling by students is interpreted as being educationally situated and to differ from scientific modelling construed as mediating theory and experiment. The latter interpretation itself may be treated as being professionally situated and, not so much a 'correct understanding' of modelling, as a further manifestation of a new cognitive-cultural mode of symbolic representation.

The Global Positioning System (GPS), a space-based system, employs dozens of satellites to provide location determination and navigation services around the world. However, due to the constraints to the power consuming and long-distance transmission, the strength of the GPS signal received on the mobile device is weak. Errors of the detection of the line-of-sight (LOS) propagated components of the signals are expected to be high if the users are in urban areas or in buildings, since obstacles in the surrounding environments could attenuate the LOS propagated components of the GPS signals significantly, but might upfade the multi-path components (constructive multi-path effect). Therefore, GPS should be replaced by other techniques for providing localisation services in urban areas or, especially, in indoor environments. Among all the candidates, received signal strength (RSS) location fingerprint based positioning systems attract great attentions from both the academia and industry. Usually, a time-consuming and labour-intensive site survey to collect dozens of training samples of RSS from access points (APs) in range on every reference position (RP) in the area of interest is required to build the radio map (RM), before the localisation services could be provided to users. The purpose of the thesis is to reduce the workload involved in the site survey while providing accurate localisation service from two aspects, as shown as follows. Firstly, the quantity of the training samples collected on each RP is reduced, by taking advantage of the on-line RSS measurements collected by users to calibrate the RM. The on-line RSS measurements are geo-tagged probabilistically by an implementation of particle filter to track the trajectories of the users. The employed particles in estimation of the users’ states are initialised by a supervised clustering algorithm, propagated according to the analysis of the data sourcing from inertial measurement units (IMUs), e.g., walking detection, orientation estimation, step and stepping moments detection, step length detection, etc., and corrected by the wall constraints. Furthermore, the importance weights of the particles are adjusted to reduce the negative influence of the multi-clustered distribution of the particles to the on-line localisation accuracy, by applying the on-line RSS-based localisation results when significant users' body turnings are detected. The final results confirm that the accuracy of the localisation service with the RM calibrated by the method proposed in this thesis is higher than the previously proposed approach taking advantage of expectation maximisation algorithm. Secondly, a semi-automatic site-survey method which takes advantage of a route-planning algorithm and a walking detection module to recognise automatically the index of the RP for the current site-survey task, inform the system automatically of the start/end of the process of the task on the current RP and switch automatically to the following RPs on the planned route for the following tasks. In this way, human beings' intervention to the site-survey process is greatly reduced. As a result, the errors made in the site-survey tasks, such as incorrect recognition of the index of the RP for the current task which is highly likely to occur when the technicians get absent-minded in the work, misoperations to start/end of the task for collecting RSS samples on the current RP at wrong time moments, forgetting to notify the system of the fact that the technician has moved on to the next RP, etc., are avoided. The technicians no longer feel bored or anxious in the process of fulfilment of site-survey tasks, and the working efficiency and robustness of the RM could be also improved.

Vagueness is an essential part of how humans perceive and understand the geographical world they occupy. It has now become of increasing important to acknowledge this situation in geographical databases and analyses in the field of Geographical Information Science (GIScience). This research has tackled the wholly original topic of modelling vague geographical places (objects) based on fuzzy set theory with a view to assessing the implications of routing problem around those vague places. The research has focused on the modelling of vague places, for a number of villages and rural settlements, working with national address databases which have numerous ambiguous characteristics which add challenge to the work. It has demonstrated the way in which fuzzy set theory can be used to derive approximate boundaries for vague spatial extents (fuzzy footprint) form sets of precise addresses, reporting rural settlements, recorded in different databases. It has further explored the implications of applying the Travelling Salesman Problem (TSP) in traditional hard village extents versus the modelled fuzzy extents. The introduced methods evaluate the usefulness of fuzzy set theory in modelling and analysing such vague regions. The results imply that the fuzzy model is more efficient than the traditional hard, crisp model of approximating the spatial extent of rural areas. However, the TSP results showed that longer tours were mostly found in the fuzzy model than the traditional crisp model. This is mainly affected by the scale factor of rural areas, considering the relatively small distances between villages. One challenge for the approach outlined here is to incorporate this method applied in other novel analyses of geographical information based on fuzzy representation of geographical phenomena.

This thesis reports a series of three experiments undertaken to investigate whether the use of geographic information systems (GIS) and imagery toolsets improved or accelerated learning about new environments in military personnel The first experiment took place within a large rural environment over six days, and the second took place in an urban environment in a single session lasting three hours. Each of these experiments compared the use of GIS and imagery with the use of maps only. All participants were able to have direct navigational experience of the environment The final experiment aimed to investigate the effect of specialisation on the components extracted from real scenes. The results showed that there was evidence of learning exhibited in both environments, and the use of GIS and imagery did provide an increase in the number oflandmarks identified, and the number identified on sketch maps produced by the participants. However, there was little improvement in the accuracy of landmark location from GIS and imagery learning over learning with maps. In general there was a high degree of individual variability in performance for the spatial tests, and it is concluded that this variability masked effects of the experimental conditions. Those participants with specialist technicill or geographic experience were able to identify more components and more details from the images presented than participants from other backgrounds. It was concluded that the use of GIS and imagery provide useful additional information to that provided by mapping, and appeared to increase user confidence.

No description available.

Recently, especially within the last two decades, the demand for DSMs (Digital Surface Models) and 3D city models has increased dramatically. This has arisen due to the emergence of new applications beyond construction or analysis and consequently to a focus on accuracy and the cost. This thesis addresses two linked subjects: first improving the quality of the DSM by merging different source DSMs using a Bayesian approach; and second, extracting building footprints using approaches, including Bayesian approaches, and producing 3D models. Regarding the first topic, a probabilistic model has been generated based on the Bayesian approach in order to merge different source DSMs from different sensors. The Bayesian approach is specified to be ideal in the case when the data is limited and this can consequently be compensated by introducing the a priori. The implemented prior is based on the hypothesis that the building roof outlines are specified to be smooth, for that reason local entropy has been implemented in order to infer the a priori data. In addition to the a priori estimation, the quality of the DSMs is obtained by using field checkpoints from differential GNSS. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the Maximum Likelihood model which showed similar quantitative statistical results and better qualitative results. Perhaps it is worth mentioning that, although the DSMs used in the merging have been produced using satellite images, the model can be applied on any type of DSM. The second topic is building footprint extraction based on using satellite imagery. An efficient flow-line for automatic building footprint extraction and 3D model construction, from both stereo panchromatic and multispectral satellite imagery was developed. This flow-line has been applied in an area of different building types, with both hipped and sloped roofs. The flow line consisted of multi stages. First, data preparation, digital orthoimagery and DSMs are created from WorldView-1. Pleiades imagery is used to create a vegetation mask. The orthoimagery then undergoes binary classification into ‘foreground’ (including buildings, shadows, open-water, roads and trees) and ‘background’ (including grass, bare soil, and clay). From the foreground class, shadows and open water are removed after creating a shadow mask by thresholding the same orthoimagery. Likewise roads have been removed, for the time being, after interactively creating a mask using the orthoimagery. NDVI processing of the Pleiades imagery has been used to create a mask for removing the trees. An ‘edge map’ is produced using Canny edge detection to define the exact building boundary outlines, from enhanced orthoimagery. A normalised digital surface model (nDSM) is produced from the original DSM using smoothing and subtracting techniques. Second, start Building Detection and Extraction. Buildings can be detected, in part, in the nDSM as isolated relatively elevated ‘blobs’. These nDSM ‘blobs’ are uniquely labelled to identify rudimentary buildings. Each ‘blob’ is paired with its corresponding ‘foreground’ area from the orthoimagery. Each ‘foreground’ area is used as an initial building boundary, which is then vectorised and simplified. Some unnecessary details in the ‘edge map’, particularly on the roofs of the buildings can be removed using mathematical morphology. Some building edges are not detected in the ‘edge map’ due to low contrast in some parts of the orthoimagery. The ‘edge map’ is subsequently further improved also using mathematical morphology, leading to the ‘modified edge map’. Finally, A Bayesian approach is used to find the most probable coordinates of the building footprints, based on the ‘modified edge map’. The proposal that is made for the footprint a priori data is based on the creating a PDF which assumes that the probable footprint angle at the corner is 90o and along the edge is 180o, with a less probable value given to the other angles such as 45o and 135o. The 3D model is constructed by extracting the elevation of the buildings from the DSM and combining it with the regularized building boundary. Validation, both quantitatively and qualitatively has shown that the developed process and associated algorithms have successfully been able to extract building footprints and create 3D models.

This thesis takes a multidisciplinary approach to understanding the characteristics, quality and production of Volunteered Geographic Information (VGI), through examining the emergent method of Community Mapping in developing countries. While a good understanding exists of the nature of the characteristics, quality and production of VGI in developed countries there is little covering developing countries. This thesis reviews the state of the art and theoretical approaches in Geography, Human Factors and Geographic Information Science. Research methods of Human Factors, specifically Cognitive Work Analysis (CWA) and geospatial quality assessment are also discussed. Through a mixed methods approach, the characteristics of Community Mapping are examined and contrasted against those in developed countries. Consequently the quality of data produced and its mode of production are examined, enabled through the construction of a CWA to situate and explore constraints of the developing world case. By discussing the results and conclusions of these studies, this thesis provides an agenda for the understanding geospatial data quality in developing countries and, specifically, informal urban areas known by their more colloquial moniker of `slums'. By involving the community in data production and decision making it adheres to the CWA principles and ethics of respectful, user centric design. In assessing the quality of the data produced and the needs of community members around tools we create design guidelines for the development of future tools. Finally, this thesis considers how the characteristics of Community Mapping could and should be considered in the use and reuse of spatial data by its integration into Spatial Data Infrastructures (SDI). In conclusion, a conceptual framework for the development of VGI in developing countries is produced, alongside other avenues for further work for the theories, software and communities nurtured as part of this thesis.