Town Centre Statistics Through the Internet

April 28-2

Defining and delineating the central areas of towns for statistical monitoring using continuous surface representations

The increasing availability of very high spatial resolution data using the unit postcode as its geo-reference is making possible new kinds of urban analysis andmodelling. However, at this resolution the granularity of the data used to representurban functions makes it difficult to apply traditional analytical and modellingmethods. An alternative suggested here is to use kernel density estimation totransform these data from point or area 'objects' into continuous surfaces of spatialdensities. The use of this transformation is illustrated by a study in which we attemptto develop a robust, generally applicable methodology for identifying the centralareas of UK towns for the purpose of statistical reporting and comparison.Continuous density transformations from unit post code data relating to a series ofindicators of town centredness created using ArcView are normalised and thensummed to give a composite ?Index of Town Centredness?. Selection of key contourson these index surfaces enables town centres to be delineated. The work results froma study on behalf of DETR

Local movement: agent-based models of pedestrian flows

Modelling movement within the built environment has hitherto been focused on rather coarse spatial scales where the emphasis has been upon simulating flows of traffic between origins and destinations. Models of pedestrian movement have been sporadic, based largely on finding statistical relationships between volumes and the accessibility of streets, with no sustained efforts at improving such theories. The development of object-orientated computing and agent-based models which have followed in this wake, promise to change this picture radically. It is now possible to develop models simulating the geometric motion of individual agents in small-scale environments using theories of traffic flow to underpin their logic. In this paper, we outline such a model which we adapt to simulate flows of pedestrians between fixed points of entry - gateways - into complex environments such as city centres, and points of attraction based on the location of retail and leisure facilities which represent the focus of such movements. The model simulates the movement of each individual in terms of five components; these are based on motion in the direction of the most attractive locations, forward movement, the avoidance of local geometric obstacles, thresholds which constrain congestion, and movement which is influenced by those already moving towards various locations. The model has elements which enable walkers to self-organise as well as learn from their geometric experiences so far. We first outline the structure of the model, present a computable form, and illustrate how it can be programmed as a variant of cellular automata. We illustrate it using three examples: its application to an idealised mall where we show how two key components - local navigation of obstacles and movement towards points of global locational attraction - can be parameterised, an application to the more complex town centre of Wolverhampton (in the UK West Midlands) where the paths of individual walkers are used to explore the veracity of the model, and finally it application to the Tate Gallery complex in central London where the focus is on calibrating the model by letting individual agents learn from their experience of walking within the environment

"So go downtown": simulating pedestrian movement in town centres

Pedestrian movement models have been developed since the 1970s. A review of the literature shows that such models have been developed to explain and predict macro, meso, and micro movement patterns. However, recent developments in modelling techniques, and especially advances in agent-based simulation, open up the possibility of developing integrative and complex models which use existing models as 'building blocks'. In this paper we describe such integrative, modular approach to simulating pedestrian movement behaviour. The STREETS model, developed by using Swarm and GIS, is an agent-based model that focuses on the simulation of the behavioural aspects of pedestrian movement. The modular structure of the simulation is described in detail. This is followed by a discussion of the lessons learned from the development of STREETS, especially the advantages of adopting a modular approach and other aspects of using the agent-based paradigm for modelling

STREETS: an agent-based pedestrian model.

8-11 Septembe

Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows

The spatial arrangement of urban hubs and centers and how individuals interact with these centers is a crucial problem with many applications ranging from urban planning to epidemiology. We utilize here in an unprecedented manner the large scale, real-time 'Oyster' card database of individual person movements in the London subway to reveal the structure and organization of the city. We show that patterns of intraurban movement are strongly heterogeneous in terms of volume, but not in terms of distance travelled, and that there is a polycentric structure composed of large flows organized around a limited number of activity centers. For smaller flows, the pattern of connections becomes richer and more complex and is not strictly hierarchical since it mixes different levels consisting of different orders of magnitude. This new understanding can shed light on the impact of new urban projects on the evolution of the polycentric configuration of a city and the dense structure of its centers and it provides an initial approach to modeling flows in an urban system

Exploring area-based vulnerability to gambling-related harm: Developing the gambling-related harm risk index

No abstract available