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      An open source delineation and hierarchical classification of UK retail agglomerations

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      1 , 2 , 3 , , 2 , 3
      Scientific Data
      Nature Publishing Group UK
      Geography, Business, Databases, Economics

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          Abstract

          Town centres and high streets typically form the social and commercial cores of UK cities and towns, yet, there is no uniform definition of what a town centre or high street is. In this study the spatial delineations of retail agglomerations are generated using open-source data for England, Wales, Scotland and Northern Ireland. The extent and boundaries of these physical retail areas are identified based on the density and connectivity patterns of individual retail units over space. A high resolution hexagonal grid is superimposed over spatial clusters of retail points and a network-based algorithm used to identify mutually exclusive tracts. Agglomerations are then pruned and fine-tuned according to a series of heuristic rules. Our retail agglomerations represent local commerce areas with shopping amenities and are assigned to a hierarchical classification ranking from the largest Regional Centres, Major Town Centres and Town Centres, down to Small Local Centres and Retail Parks. The classification into one of eleven hierarchies is based on a combination of relative rank in the local area and absolute size of retail units within the area. These retail agglomeration boundaries, hierarchical classification and lookups form an open-source spatial data product available for wide use and research implementation.

          Abstract

          Measurement(s) Retail Environment
          Technology Type(s) Processed Data
          Factor Type(s) Retail unit locations
          Sample Characteristic - Environment usage of an environment for retail activity
          Sample Characteristic - Location United Kingdom

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                Author and article information

                Contributors
                L.Dolega@liverpool.ac.uk
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                3 September 2022
                3 September 2022
                2022
                : 9
                : 541
                Affiliations
                [1 ]GRID grid.11835.3e, ISNI 0000 0004 1936 9262, University of Sheffield – Department of Urban Studies and Planning, ; Sheffield, United Kingdom
                [2 ]GRID grid.10025.36, ISNI 0000 0004 1936 8470, Geographic Data Science Lab, , University of Liverpool – Department of Geography and Planning, ; Liverpool, United Kingdom
                [3 ]Consumer Data Research Centre (CDRC), Liverpool, United Kingdom
                Article
                1556
                10.1038/s41597-022-01556-3
                9440905
                36057644
                c455163a-4083-4020-bc26-b495b3cf121f
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 December 2021
                : 29 June 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000269, RCUK | Economic and Social Research Council (ESRC);
                Award ID: ES/L011840/1
                Award ID: ES/L011891/1
                Award ID: ES/L011840/1
                Award ID: ES/L011891/1
                Award ID: ES/L011840/1
                Award ID: ES/L011891/1
                Award Recipient :
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                © The Author(s) 2022

                geography,business,databases,economics
                geography, business, databases, economics

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