The Postcode Context Classification provides a national measure of urban spatial structure from high-resolution satellite imagery derived by cutting-edge convolutional neural network (CNN) techniques. By harnessing the power of the European Space Agency’s Copernicus Sentinel 2 satellites, combined with georeferenced postcodes, this data product offers unparalleled insights into the built environment across Great Britain.

Theses data presents a new method of measuring local context that could be flexibly applied within different settings to meet several definitions of neighbourhood. While the method is implemented within the context of Great Britain, given the global coverage of satellite imagery, the approach can also be applied to any location in the world. The limits of the technique are centred around the resolution of the satellite data used and the interaction between the geography of the input data and the learned structure.

Content

This data are open to access, available below as ‘Data: Cluster Labels’. Detailed descriptions of the clusters are available through the pen portraits. A FAQ sheet is also provided. For detailed description of the columns contained within the data, see the Variable Dictionary; and for an overview of the characteristics of the data, see the Data Summary. These files can be downloaded from the bottom of this page.

Quality, Representation and Bias

The source data was subject to intense cleaning to prepare for classification. These techniques may introduce biases. Please see the published paper in the 'Related Content' section for full details.