Geographic information systems (GIS) are convenient and potentially powerful platforms for transportation and urban analysis. Most GIS-based tools for transportation and urban analysis continue a place-based representation that is increasingly ill-suited to answer important questions in theory, policy and practice. The increasing disconnection between people and places means that a people-based representation is required to address questions of access, exclusion and evolution at the forefront of transportation and urban analysis and policy. A people-based GIS can be achieved by integrating principles from time geography and activity theory with geographic information science (GISci) representational theories and geographic information technologies. This paper reviews the principles, state of the art and research needs for a people-based GIS based on integrating time geographic and space-time activity concepts with the theories and tools of GISci and GIS.

The well-known distinction between field-based and object-based approaches to spatial information is generalised to arbitrary locational frameworks, including in particular space, time and space-time. We systematically explore the different ways in which these approaches can be combined, and address the relative merits of a fully four-dimensional approach as against a more conventional ‘three-plus-one’-dimensional approach. We single out as especially interesting in this respect a class of phenomena, here called multiaspect phenomena, which seem to present different aspects when considered from different points of view. Such phenomena (e.g., floods, wildfires, processions) are proposed as the most natural candidates for treatment as fully four-dimensional entities (‘hyperobjects’), but it remains problematic how to model them so as to do justice to their multi-aspectual nature. The paper ends with a range of important researchable questions aimed at clearing up some of the difficulties raised.

Abstract not found

A number of related yet distinct subfields of GIScience associated with representing geographic dynamics have recently emerged. Researchers in spatio-temporal theory and data modeling, spatial process modeling, complex systems, and agent-based modeling all consider dynamic (or temporal) aspects of geographic phenomena germane to their respective specialty. Given this common ground, an obvious question arises as to the degree to which these communities have shared goals that might be forwarded through collaboration. In short, where might synergies or unique insights lie, and what redundant efforts might be streamlined? This short position paper looks at two research areas (and communities) that are the focus of this workshop: agent-based modeling and spatiotemporal data modeling. Agent-based modeling of complex systems Agent-based modeling is an active research area that continues to gain momentum. The software tools to support this type of modeling have come a long way both in terms of facilitating rapid model development as well as integrating models with GIS. The area also evolved from the start with a particular emphasis on explicit representation of space

Geospatial data modelling is dominated by the distinction between continuousfield and discrete-object conceptualizations. However, the boundary between them is not always clear, and the field view is more fundamental in some respects than the object view. By viewing a set of objects as an object field and unifying it with conventional field models, a new concept, the General Field (G-Field) model, is proposed. In this paper, the properties of G-Field models, including domain, range, and categorization, are discussed. As a summary, a descriptive framework for G-Field models is proposed. Then, some common geospatial operations in geographic information systems are reconsidered from the G-Field perspective. The geospatial operations are classified into order-increasing operations and non-order-increasing operations, depending on changes induced in the G-Field’s order. Generally, the order can be viewed as an indicator of the level of information extraction of geospatial data. It is thus possible to integrate the concept of order with a geo-workflow management system to support geographic semantics.

Hagerstrand's minimalist representation of individual lives and opportunities as lifelines and prisms predates the technologies available to current GIScience but resonates with many emerging spatio-temporal data model describing human activity in space and time. It also offer strong synergies with the various approaches that use data sets representing the tracks of individuals in order to explore patterns in their movements and associated activities. Almost inevitably such tracking data sets utilise (x,y,t) and activity data (representing lifelines) which are sampled over time and space and are eventually embedded for analysis within a digital geospatial environment. There are clear issues of error in both the data defining the environment used for analysis and that defining the movement as sampled (x,y,t) points, and consequently specific properties of the interaction emerge which would be of interest to us. While the lifeline is one of a number of attempts to represent human (or any object's) presence in space-time the concept of the prism focuses more on interpolating where an object could be, or might be, when it is between two known points. This idea of prism is a derivative spatio-temporal construct which has a further dimension of vagueness and uncertainty attached to it. Such properties require both identification and representation. This paper explores two issues. The first is the nature of uncertainty and error in an actual or interpolated lifeline data models related to typical kinds of analysis of movement and activity within a digital representation of its embedding geography. The second examines the nature of any prism of opportunity that is inferred from partial lifeline data and then deployed in accessibility studies. Specifically it discusses how issues of spatio-temporal uncertainty in the derivation of