Simulating retail demand at the individual level: stage 1 demand synthesis

Social and demographic data about the composition of small geographic areas is readily available in many countries. For example, in the UK the Census of Population and Households generates counts for output areas that typically comprise only around 125 households. These data may be characterised as providing a picture of the night-time populations of different neighbourhoods which has been widely used in planning the delivery of services such as education (Singleton et al., 2011) and health care (Burke 2010; Wennberg and Gittelsohn, 1973), and for strategic planning of land use (Shultz and King, 2001) or transportation (Waddell, 2002).
However for many purposes the location of populations through the day-time may be of much greater significance. With regard to planning for emergencies whether natural such as flood risks a more common issue in recent years in the UK, or man-made such as terrorist attacks like the London bombings in 2005 or the more recent riots in 2011, the actual location and distribution of people throughout the day and night is of greater use than a simple static residential population. Of even greater use is a simulation that can estimate the evacuation patterns likely to be observed, such as parents picking children up from schools before leaving a potentially dangerous area. A similar argument can be made for services such as policing and retail provision where routine large shifts in population distributions throughout the day and night impact on the level and type of service provision required.
The work reported below outlines the first steps taken to integrate two approaches to simulating the population throughout the day and night. The first of these is characterized as mapping the population at different locations through the day. The second is referred to as tracking and seeks to follow the spatial movements of individuals in the population as they go about there daily routines. The research demonstrates for a case study of the city of Leeds how a more complete picture emerges from the combination of these two approaches and discusses both the potential and limitations of these models and there combined output. First both of the individual approaches are described followed by a description of the combined approach to tracking and mapping the population.