Comber, Alexis and Brunsdon, Chris and Farmer, Carson J. Q.
(2012)
Community detection in spatial networks: Inferring land use from a planar graph
of land cover objects.
International Journal of Applied Earth Observation and Geoinformation, 18.
pp. 274-282.
ISSN 0303-2434
Abstract
This paper applies three algorithms for detecting communities within networks. It applies them to a
network of land cover objects, identified in an OBIA, in order to identify areas of homogenous land use.
Previous research on land cover to land use transformations has identified the need for rules and knowledge
to merge land cover objects. This research shows that Walktrap, Spinglass and Fastgreedy algorithms
are able to identify land use communities but with different spatial properties. Community detection algorithms,
arising from graph theory and networks science, offer methods for merging sub-objects based
on the properties of the network. The use of an explicitly geographical network also identifies some
limitations to network partitioning methods such as Spinglass that introduce a degree of randomness in
their search for community structure. The results show such algorithms may not be suitable for analysing
geographic networks whose structure reflects topological relationships between objects. The discussion
identifies a number of areas for further work, including the evaluation of different null statistical models
for determining the modularity of geographic networks. The findings of this research also have implications
for the many activities that are considering social networks, which increasingly have a geographical
component.
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