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Title: Characterizing Volunteered Geographic Information using Fuzzy Clustering
Authors: De Sabbata, S.
Tate, N.
Jarvis, C.
First Published: 27-Sep-2016
Presented at: 9th International Conference on Geographic Information Science (GIScience 2016) Montreal , Quebec, Canada
Start Date: 27-Sep-2016
End Date: 30-Sep-2016
Citation: 9th International Conference on Geographic Information Science (GIScience 2016)
Abstract: This paper demonstrates the use of fuzzy clustering to characterize Volunteered Geographic Information (VGI). We argue that classifying small areas based on variables related to the amount, type, and currency of VGI can provide a more nuanced understanding of the content. We present a classification of 2011 UK Census Output Areas in Leicestershire (UK) based on content of OpenStreetMap, using a fuzzy c-means clustering algorithm, and we compare the resulting classification with a ‘standard’ socio-economic geodemographic classification.
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Creative Commons “Attribution Non-Commercial No Derivatives” licence CC BY-NC-ND, further details of which can be found via the following link: Archived with reference to SHERPA/RoMEO and publisher website.
Description: The 2011 UK Census Output Area (OA) boundaries and attributes were obtained via the UK Data Service, retrieved from SN:5819. Figure 1 and 2 use map tiles by Stamen Design, under CC BY 3.0.
Appears in Collections:Conference Papers & Presentations, Dept. of Geography

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