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USE OF TEMPORAL KNOWLEDGE IN DETECTING UNPLANNED DEVELOPMENTS IN URBAN AREAS

By Faith Karanja and Peter Lohmann

Abstract

Knowledge based classification incorporates knowledge derived from ancillary data and spectral information. A method that employs object, structural and spectral information from two remotely sensed data at different epochs to generate two classes namely developed and reserved (non-developed) for each epoch within an expert classification environment has been described. This information is then combined with a plan of future land use as temporal knowledge to predict areas designated for development. Further, the temporal knowledge was perturbed to replicate a scenario in a developing country where mushrooming of unplanned structures is prevalent. The outputs of these predicted land uses are then compared with the actual situation as shown by the epoch 2 image to detect unusual phenomena. These phenomena imply that, all that is planned is not necessarily implemented and this is in part due to problems associated with budgetary allocation and unpredictability of some factors resulting from the complexity and inconsistency of the real world. This information is a useful backdrop for strategic and reaction planning in the event where unusual phenomena have occured e.g. informal and illegal structures in developing countries.

Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.196.4959
Provided by: CiteSeerX
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