Allan J. Brimicombe

Mobile Space-Time Envelopes for Location-Based Services

The convergence and miniaturisation of a range of information and communication technologies, together with increasing bandwidth availability and near ubiquity of mobile phones, are giving rise to a technological environment in which location-based services (LBS) can realistically develop. In this paper we review the nature of location-based services and the implications for data and spatial queries. In doing so, we put forward a research agenda that arises for geographical information science and engineering. Central to LBS are problems of response time and the information utility of responses to queries and any pushed alerts, where information utility refers to content, timeliness and geographical footprint. Within a publish/subscribe model of LBS provision, we propose mobile space-time envelopes as a novel approach to event brokerage. These envelopes simultaneously provide ‘soft clip’ pruning of candidate data sets in anticipation of queries, and provide the trigger that subscribers are pertinently in-range for alerts. We present the geometrical, algebraic and algorithmic concepts of mobile space-time envelopes and provide an example of these mobile envelopes in action. We conclude with a discussion of how this initial implementation could be further developed to incorporate added spatio-temporal intelligence.

Spatial data quality and sensitivity analysis in GIS and environmental modelling: the case of coastal oil spills

Whilst spatial data quality has been recognised as an important issue in geographical information systems (GIS) and has been studied in some aspects of environmental modelling, it has received scant attention from coastal oil spill modellers. This paper sets out the results of some experiments which show the impact of data quality for bathymetry and shoreline representation on the outputs of the hydrodynamics modelling. Due to the large number of potential sources of error, a synthetic modelling approach has been adopted and includes polynomial trend surfaces, fractals and Gaussian error fields. The results show that spatial data quality does have an impact on coastal oil spill modelling and point to some of the critical areas where sensitivity analyses can usefully be carried out by modellers to specify the quality of data inputs needed for outputs to have fitness-for-use. The methodology points to a reconsideration of the coupling strategies for GIS and environmental modelling which should be exposed to include specific spatial data quality analysis tools.

Ethnicity, Religion, and Residential Segregation in London: Evidence from a Computational Typology of Minority Communities

Within the context of the growing polarisation and fragmentation of the urban landscape, this paper presents a computational typology applicable to the study of minority communities, both ethnic and religious, which is useful in understanding their spatial distribution and juxtaposition at neighbourhood levels. The typology has been applied to multicultural London with the use of the 2001 Census, in which there were questions on ethnicity and religion. The landscape of religion is found to be more highly segregated in contrast to the landscape of ethnicity. Furthermore, on the basis of a preliminary analysis of indicator variables, minorities seem on aggregate to be in an improved situation given a level of residential segregation, with the exception of residents of segregated Asian-Bangladeshi areas for ethnicity and residents of segregated Muslim areas for religion. This questions the generally held view that segregation in a multicultural society is undesirable per se and suggests that a ‘one size fits all’ government policy towards residential segregation is insufficiently perceptive. The typology introduced here should facilitate a more critically informed approach to multiculturalism and the contemporary city.

Mapping research journeys across complex terrain with heavy baggage

In this article we review our experience of collaborating in the design and delivery of multidisciplinary training and support programmes for doctoral students and our attempts to locate models and metaphors for research planning and implementation which travel well across disciplines. We extend the metaphor of the journey to conceptualize a mapping of the Ph.D. process and examine the extent to which research students from widely divergent backgrounds may travel together and help each other navigate towards their destinations. We explore some issues of culture and communication involved in working in an interdisciplinary context, showing how we have been provoked to reflect critically on our own research identities and locations in the process of working together. We also identify some tensions between the assumptions about research development embodied in recent government policy documents and the lived experience of the research students with whom we work.

APPLICATION OF GIS TO HAZARD ASSESSMENT, WITH PARTICULAR REFERENCE TO LANDSLIDES IN HONG KONG

This paper reviews some of the factors relevant to the implementation of various GIS facilities with respect to terrain-related hazards prevailing in Hong Kong, with particular reference to landslides. Examples of the current state of practice are described, together with some considerations for future developments with regard to landslide hazard assessment and emergency response. Although Hong Kong faces the combined hazards of landslides, flooding, tidal surge and typhoon winds, the emphasis of this paper is placed on the approach to reducing landslide risks to the public. The approach is discussed within the framework of hazard mitigation (prevention and preparedness), disaster response and to a lesser extent, recovery. The key programmes within the Geotechnical Engineering Office of the Hong Kong Government are given as case studies. These systems continue to be developed to be more responsive to the pressing needs of urban development and to an increasing community awareness of the hazards of slope failure.

A dual approach to cluster discovery in point event data sets

Abstract Spatial data mining seeks to discover meaningful patterns in data where a prime dimension of interest is geographical location. Consideration of a spatial dimension becomes important where data either refer to specific locations and/or have significant spatial dependence which needs to be considered if meaningful patterns are to emerge. For point event data there are two main groups of approaches to identifying clusters. One stems from the statistical tradition of classification which assigns point events to a spatial segmentation. A popular method is the k -means algorithm. The other broad approach is one which searches for ‘hot spots’ which can be loosely defined as a localised excess of some incidence rate. Examples of this approach are GAM and kernel density estimation. This paper presents a novel variable resolution approach to ‘hot spot’ cluster discovery which acts to define spatial concentrations within the point event data. ‘Hot spot’ centroids are then used to establish additional distance variables and initial cluster centroids for a k -means classification that produces a segmentation, both spatially and by attribute. This dual approach is effective in quickly focusing on rational candidate solutions to the values of k and choice of initial candidate centroids in the k -means clustering. This is demonstrated through the analysis of a business transactions database. The overall dual approach can be used effectively to explore clusters in very large point event data sets.

Agent-based services for the validation and calibration of multi-agent models

Agent-based modelling in the form of multi-agent models has been increasingly applied to the simulation of spatial phenomena in silico. Validation and calibration are recurrent problems. The complexity of these models with large numbers of parameters can make validation procedures intractable. In this paper, the novel concept of using agent-based technologies to create services that assist in the validation and calibration of multi-agent models is developed. Such agent-based services offer an efficient solution where large numbers of model runs need to be carried out. In this paper, the agent-based services are collaborative sets of agents that perform calibration and sensitivity analysis as a key task in model validation. In a case study, the prototype agent-based validation services are implemented for a multi-agent wayfinding model as a means of proof-of-concept. The case study demonstrates how agent-based services can be deployed for testing the robustness of emergent patterns through sensitivity analyses and used for model calibration.

Adaptive Recursive Tessellations (ART) for Geographical Information Systems

Adaptive Recursive Tessellations (ART) is a conceptual and generalized framework for a series of hierarchical tessellation models characterized by a variable decomposition ratio and rectangular cells. ART offers more flexibility in cell size and shape than the quadtree which is constrained by its fixed 1:4 decomposition ratio and square cells. Thus the variable resolution storage characteristic of the hierarchical tessellations can be fully utilized. A data structure for the implementation of the ART, called Adaptive Recursive Run-Encoding (ARRE), is proposed. Then a spatial database management system specially for ART, the Tessellation Manager, is constructed based on the ARRE. Space efficiency analysis of three ART models are conducted using the Tessellation Manager. The result shows that ART models have similar space efficiency with the quadtree model. ART also has many potential applications in GIS and is suitable as a spatial data model for raster GIS.

A variable resolution, geocomputational approach to the analysis of point patterns

A geocomputational approach to the solution of applied spatial problems is being ushered in to take advantage of ever increasing computer power. The move is seen widely as a paradigm shift allowing better solutions to be found for old problems, solutions to be found for previously unsolvable problems and the development of new quantitative approaches to geography. This paper uses geocomputation to revisit point-pattern analysis as an objective, exploratory means of evaluating mapped distributions of landforms and/or events. A new variable resolution approach is introduced and tested alongside more traditional approaches of nearest neighbour distance and quadrat analysis and against another geocomputational approach, the K function. The results demonstrate that firstly, the geocomputational paradigm allows new and more useful solutions to be found for old problems. Secondly, a variable resolution approach to geographical data analysis goes some way towards overcoming the problem of scale inherent in such analyses. Finally, the technique facilitates spatiotemporal analyses of event data, such as landslides, thus offering new lines of enquiry in areas such as hazard mitigation. Copyright

Geofencing in a Security Strategy Model

The aim of this research paper is to investigate and create a security strategy model using geofencing; which can then be used to secure wireless local area networks (WLANs). In order to do so, the investigation will use the systematic arrangement and design used by geofencing technology for locating pre-configured wireless laptop. The objective is for the wireless laptop to function within a defined geographical area and be served by a specified wireless intercommunication unit. This is so that the defined geographical area can be used as a geo-fenced test bed to monitor the acts of the wireless laptop when communicating with the electromagnetic waves which is the medium through which it transmits data and communicates with the wireless intercommunication unit. By performing this experiment the security strategy model will be used to observe, detect and record the operations of the electromagnetic waves as they convey information within the geo-fenced test bed to the wireless laptop. Finally, by recording the operations the investigation will look to identify if predetermined acts took place within the geo-fenced test bed and in so doing develop a trusted security strategy model.