In recent years the development of spatial referencing techniques in com puter-based information systems has enormously increased the opportuni ties that exist for the treatment and presentation of both point and interaction data. The extent of this increase has drawn attention to the need for special aggregation and clustering procedures to be developed which enable data to be grouped in an efficient way for analytical pur poses with a minimum loss of detail. In the case of interaction data, economy of representation is particularly important as the analysis is further complicated by the two-way directionality that is inherent in each data set. Procedural rules of this kind are needed not only for descriptive analy sis and spatial accounting but also for hypothesis testing and the develop ment of operational models of spatial interaction. Yet the importance of spatial representation in this kind of research has only recently been fully understood. The first generation of urban development models that were developed in Europe and North America during the 1960's often treated matters of zoning system specification very casually, even though in some cases this imposed severe limits on the interpretation of their findings and it was not until the Centre for Environmental Studies/Cheshire project (Barras et al. , 1971) that a serious attempt was made to put forward general principles which could be used as guidelines in future work.

A comprehensive core text from the expert in the field introducing students to the main issues of spatial systems modelling and analysis.

Research on spatial cognition is a rapidly evolving interdisciplinary enterprise for the study of spatial representations and cognitive spatial processes, be they real or abstract, human or machine. Spatial cognition brings together a variety of - search methodologies: empirical investigations on human and animal orientation and navigation; studies of communicating spatial knowledge using language and graphical or other pictorial means; the development of formal models for r- resenting and processing spatial knowledge; and computer implementations to solve spatial problems, to simulate human or animal orientation and navigation behavior, or to reproduce spatial communication patterns. These approaches can interact in interesting and useful ways: Results from empirical studies call for formal explanations both of the underlying memory structures and of the processes operating upon them; we can develop and - plement operational computer models obeying the relationships between objects and events described by the formal models; we can empirically test the computer models under a variety of conditions, and we can compare the results to the - sults from the human or animal experiments. A disagreement between these results can provide useful indications towards the re nement of the models.

This book considers how people talk about their environment, find their way in new surroundings, and plan routes. Part I explores the empirical insights gained from research in the cognitive underpinnings of spatial representation in language. Part II proposes solutions for capturing such insights formally, and in Part III authors discuss how theory is put into practice through spatial assistance systems. These three perspectives stem from research disciplines which deal with the spatial domain in different ways, and which often remain separate. In this book they are combined so as to highlight both the state of the art in the field and the benefit of building bridges between methodologies and disciplines. Finding our way and planning routes is relevant to us all; this book ultimately helps improve our everyday lives.

Coping with spatial expressions in a plausible manner is a crucial problem in a number of research fields, specifically cognitive science, artificial intelligence, psychology, and linguistics. This volume contains a set of theoretical analyses as well as accounts of applications which deal with the problems of representing and processing spatial expressions. These include dialogue understanding using mental images; interfaces to CAD and multi-media systems, such as natural language querying of photographic databases; speech-driven design and assembly; machine translation systems; spatial queries for Geographic Information Systems; and systems which generate spatial descriptions on the basis of maps, cognitive maps, or other spatial representations, such as intelligent vehicle navigation systems. Though there have been many different approaches to the representation and processing of spatial expressions, most existing computational characterizations have so far been restricted to particularly narrow problem domains, usually specific spatial contexts determined by overall system goals. To date, artificial intelligence research in this field has rarely taken advantage of language and spatial cognition studies carried out by the cognitive science community. One of the fundamental aims of this book is to bring together research from both disciplines in the belief that artificial intelligence has much to gain from an appreciation of cognitive theories.