Michael F. Worboys

Foundations of Geographic Information Science

Geographic Information Science. The Nature and Value of Geographic Information. Communicating Geographic Information in Context. Pragmatic Information Content. Representational Commitment in Maps. Granularity in Change over Time. A Theory of Granular Partitions. On the Ontological Status of Geographical Boundaries. Regions in Geography. Neighborhoods and Landmarks. Geographical Terminology Servers. Placing Cultural Events and Documents. Geographic Activity Models.

Event‐oriented approaches to geographic phenomena

This paper is about the information‐theoretic foundations upon which useful explanatory and predictive models of dynamic geographic phenomena can be based. It traces the development of these foundations, from sequences of temporal snapshots, through object life histories, to event chronicles. A crucial ontological distinction is drawn between ‘things’ and ‘happenings’, that is between continuant and occurrent entities. Up to now, most research has focused on representing the evolution through time of geographic things, whether objects or fields. This paper argues that ‘happenings’ should be upgraded to an equal status with ‘things’ in dynamic geographic representations and suggests ways of doing this. The main research focus of the paper is the application of an algebraic approach, previously developed mainly in the context of computational processes, to real‐world happenings. It develops a pure event‐oriented theory of space and time, and suggests the possibilities that the theory provides by using it to represent the motion of a vehicle through a region. The paper contains a discussion of the scalability and applicability of this model to geographic domains and illustrates some of the ideas by reference to a geo‐sensor example. The paper concludes by summarizing its main ideas, relating the research to other germane areas not covered in the developmental survey, and indicating directions for future work.

From Objects to Events: GEM, the Geospatial Event Model

This paper discusses the construction of a modeling approach for dynamic geospatial domains based on the concepts of object and event. The paper shows how such a model extends traditional object-based geospatial models. The focus of the research is the introduction of events into the object-based paradigm, and consequent work on the classification of object-event and event-event relationships. The specific geospatial nature of this model is captured in the concept of a geosetting. The paper also introduces an extension of UML diagrams to incorporate events and their relationship to each other, and to objects. The paper briefly considers an example to show the working of some of the modeling constructs, and concludes with a discussion of further research needed on event aggregation and event-based query languages.

Monitoring qualitative spatiotemporal change for geosensor networks

Recent technological advances in geosensor networks demand new models of distributed computation with dynamic spatial information. This paper presents a computational model of spatial change in dynamic regions (such as may be derived from discretizations of continuous fields) founded on embeddings of graphs in orientable surfaces. Continuous change, connectedness and regularity of dynamic regions are defined and local transition rules are used to constrain region evolution and enable more efficient inference of a regions state. The model provides a framework for the detection of global high‐level events based on local low‐level ‘snapshot’ spatiotemporal data. The approach has particular relevance to environmental monitoring with geosensor networks, where technological constraints make the detection of global behaviour from local conditions highly advantageous.

Modeling indoor space

This paper begins by reviewing the motivation for an informatics of indoor space. It then discusses application domains and consider why current geospatial technology, with its focus on outdoor space, needs to be extended. We review existing formal models of indoor space, along with their applications, and introduce a new model that is the subject of the authors current research. We conclude with some observations about the development of a unified model of both indoor and outdoor space.

Monitoring dynamic spatial fields using responsive geosensor networks

Information about dynamic spatial fields, such as temperature, windspeed, or the concentration of gas pollutant in the air, is important for many environmental applications. At the same time, the development of geosensor networks (wirelessly communicating, sensor-enabled, small computing devices distributed throughout a geographic environment) present new opportunities for monitoring dynamic spatial fields in much greater detail than ever before. This paper develops a new model for querying information about dynamic spatial fields using geosensor networks. In order to manage the inherent complexity of dynamic geographic phenomena, our approach is to focus on the qualitative representation of spatial entities, like regions, boundaries, and holes, and of events, like splitting, merging, appearance, and disappearance. Based on combinatorial maps, we present a qualitative model as the underlying data management paradigm for geosensor networks. This model is capable of tracking salient changes in the network in an energy-efficient way. Further, our model enables reconfiguration of the geosensor network in response to changes in the environment. We present an algorithm capable of adapting sensor network granularity according to dynamic monitoring requirements. Regions of high variability can trigger increases in the geosensor network granularity, leading to more detailed information about the dynamic field. Conversely, regions of stability can trigger a coarsening of the sensor network, leading to efficiency increases in particular with respect to power consumption and longevity of the sensor nodes. Querying of this responsive geosensor network is also considered, and the paper concludes with a review of future research directions.

An algebraic approach to automated geospatial information fusion

This paper presents a new technique for information fusion. Unlike most previous work on information fusion, this paper explores the use of instance‐level (extensional) information within the fusion process. This paper proposes an algorithm that can be used automatically to infer the schema‐level structure necessary for information fusion from instance‐level information. The approach is illustrated using the example of geospatial land‐cover data. The method is then extended to operate under uncertainty, such as in cases where the data are inaccurate or imprecise. The paper describes the implementation of the fusion method within a software prototype. Finally, the paper discusses several key topics for future research, including applications of this work to spatial‐data mining and the semantic web.

Report from the first workshop on geo sensor networks

Advances in sensor technology and deployment strategies are revolutionizing the way that geospatial information is collected and analyzed. For example, cameras and GPS sensors on-board static or mobile platforms have the ability to provide continuous streams of geospatially-rich information. Furthermore, with the advent of nano-technology it becomes feasible and economically viable to develop and deploy low-cost, low-power devices that are generalpurpose computing platforms with multi-purpose on-board sensing and wireless communications capabilities. Special IT infrastructure challenges are posed by systems consisting of large numbers of unattended, untethered and collaborative sensor nodes that have small, non-renewable power supply and communicate via short range radio frequency with neighboring nodes. All these types of sensors may act collaboratively as nodes within broader network configurations. Such configurations may range in scale from few cameras monitoring traffic to thousands of nodes monitoring an ecosystem. The challenge of sensor networks is to aggregate sensor nodes into computational infrastructures that are able to produce globally meaningful information from raw local data obtained by individual sensor nodes. In geo sensor networks the geospatial content of the information collected, aggregated, analyzed, and monitored by a sensor network is fundamental; this might be performed locally in real-time on the sensor nodes or between sensor nodes, or off-line in a scattered or central repositories. Thus, a geosensor network may be loosely defined as a sensor network that monitors phenomena in a geographic space. This space may range in scale from the confined environment of a room to the highly complex dynamics of a an ecosystem region. The spatial aspect of the overall technology may be of importance in multiple levels of a geo sensor network, as the concepts of space, location, topology, and spatiotemporal events may be recognized on various abstraction levels. For example, the hardware and communication layers handle the physical space of sensor deployment, and communication topologies. The database layer generates execution plans for spatiotemporal queries that relate to sensor node location, and groups of sensors. Applications deal with the relation between sensor networks and phenomena in a geographic space. We feel that the academic and practical expertise of the spatial information theory and engineering domain are crucial to advance the development of sensor networks on all different abstraction levels. The ultimate objective is to develop generic sensor network programming infrastructure that is reusable, and widely applicable in all types of different domains.

Event-based topology for dynamic planar areal objects

Representation and reasoning about dynamic spatial phenomena requires at its foundation a formalism of spatial change. This paper extends our understanding of topological change, by providing a classification and analysis of events associated with changes in topological structures of spatial areal objects as they evolve through time. Tree structures are employed to represent topological relationships between regions and holes of areal objects. Basic and complex changes are specified using structure‐preserving mappings between trees. Furthermore, the paper constructs a normal form, and proves that it is the ‘simplest’ form that can represent all the changes under consideration.

Identifying factors of geographic event conceptualisation

The present paper examines whether the formal topological characterisation of spatial relations between moving geographic regions provides an adequate basis for the human conceptualisation of motion events for those regions. The paper focuses on gradual changes in topological relationships caused by continuous transformations of the regions (specifically, translations). Using a series of experiments, the conceptualisation and perception of conceptual neighborhoods is investigated. In particular, the role of conceptual neighborhoods in characterising motion events is scrutinised. The experiments employ a grouping paradigm and a custom‐made tool for presenting animated icons. The analysis examines whether paths through a conceptual neighborhood graph sufficiently characterise the conceptualisation of the movement of two regions. The results of the experiments show that changes in topological relations—as detailed by paths through a conceptual neighborhood graph—are not sufficient to characterise the cognitive conceptualisation of moving regions. The similarity ratings show clear effects of perceptually and conceptually induced groupings such as identity (which region is moving), reference (whether a larger or a smaller region is moving), and dynamics (whether both regions are moving at the same time).