Characterizing rural England using GIS

This paper draws on experiences gained during the production of a spatial dataset characterizing rural England in terms of both socio-economic and environmental features. The base units of analysis are lower level Super Output Areas (SOAs) that are relatively consistent in terms of population size and allow the release of socio-economic data unavailable at smaller output area levels. Other advantages include boundary stability over time and the ability to nest SOAs within key administrative boundaries. SOAs are, however, specifically designed for social census data. Environmental data are more often collected in 1km or 100km grid squares or at points. This paper concerns the challenges arising from the integration of data from the social and natural sciences. Problems of boundary intersections, scale effects, geographic and statistical errors, data holes and the implications of the Modifiable Areal Unit Problem (MAUP) for the resulting dataset are discussed in detail and the importance of metadata for the rural typologies is outlined