Contact

Send us your feedback

Thank you for your feedback. An email has been sent to the ESRC support team.

An error occured whilst sending your feedback. Please review the problems below.

Our Research Catalogue contains grants and outputs data up to the end of April 2014. Records will no longer be updated after this date.

Developing Spatial Data for the Classification of Rural Areas

  • Start date: 01 October 2004
  • End date: 30 September 2005

This study aims to work towards the production of a spatial typology of rural areas that takes account of both the natural and the socio-economic environment. The rationale is that rural areas are highly diverse in terms of their ecology and in their socio-economic characteristics and it is the interaction of social, economic and environmental conditions that governs land use patterns and the potential for sustainable development.

We plan to use the Super Output Areas (SOA) of the 2001 Census as our spatial building blocks and will use the ONS 2004 definitions of rurality. Socio-economic aspects of rural conditions will be captured using information about demographic patterns, housing, economic activity, travel, dimensions of area deprivation, public health and neighbourhood characteristics. To these will be added environmental data on current land use, protected areas, biodiversity and sources, and levels of pollution of air, water and soils. Spatial analysis will be used to indicate the positions of rural communities in relation to environmental goods and 'bads' and to develop measures of access to services such as GP surgeries, shops, schools, post offices and hospitals.

The proposed study is wholly reliant on an interdisciplinary approach. The very nature of its objective demands an interdisciplinary conceptualisation of rural areas, not solely as landscapes and habitats, nor simply as places where people live and work, nor just as an economic resource. It also presents some tricky methodological challenges. Environmental and socio-economic data are collected by different methods and at different levels of resolution. One of our first tasks is to derive methods for mapping gridded environmental data on to areas that are designed for the analysis of social characteristics.

  • Outputs (6)