  Geo-tagged tweets can potentially help with sensing the interaction of people
with their surrounding environment. Based on this hypothesis, this paper makes
use of geotagged tweets in order to ascertain various land uses with a broader
goal to help with urban/city planning. The proposed method utilises supervised
learning to reveal spatial land use within cities with the help of Twitter
activity signatures. Specifically, the technique involves using tweets from
three cities of Australia namely Brisbane, Melbourne and Sydney. Analytical
results are checked against the zoning data provided by respective city
councils and a good match is observed between the predicted land use and
existing land zoning by the city councils. We show that geo-tagged tweets
contain features that can be useful for land use identification.
