CAPABLE was a joint research project led by the Centre for Transport Studies involving CASA, the Bartlett School of Planning and the Department of Psychology.
Funded by the Engineering and Physical Sciences Research Council (EPSRC), the project studied children's behaviour and perceptions in an effort to understand how children currently use the local environment and what can be done to make it easier and safer for them to move about on foot. The main objectives were:
- To understand the nature and structure of routes, spaces and networks as used and perceived by children
- To assess the extent to which the local environment meets the needs of children and their activities
- To develop a better understanding of the impact of the local environment on children's behaviour and spatial understanding
- To develop, calibrate and apply models of children's spatial movements, and
- To estimate the potential for increased incidence of walking and other modes of movement such as cycling, skateboards, and rollerblades to see how adequate the provision is for them.
There were three main strands to the project: data collection on children's behaviour and perceptions, using a variety of remote and direct sensing devices such as GPS and energy monitors; the analysis of the impact of the local environment on children's behaviour, perception and learning, through local studies of the physical arrangement of space and the social networks that children engage in; and visualizing and simulating childrens’ spatial movement patterns.
- Yi Gong
- Kay Kitazawa
Mark Birkin, Nick Malleson, Andy Hudson-Smith, Steven Gray, Richard Milton (2011) Calibration of a Spatial Simulation Model with Volunteered Geographical Information, International Journal of Geographical Information Science. (forthcoming: Special issue on data-intensive geospatial computing)
SurveyMapper website: http://www.surveymapper.com/
CASA has contributed the following to the NeISS project:
- To create a real-time, polling tool that the public can use and feed data back into mathematical models to improve outputs.
- To crowd-source data and build a public community around survey creation and answering.
- To create a real-time tool to harvest data from social media networks which can be geospatially analysed.
- The SurveyMapper and Tweet-o-Meter websites