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Application of semi-automated settlement detection for an integrated topographic map information system update in South Africa


L. Ngcofe
T. Rambau
M. McCalachan
F. Hantibi
N. Mudau

Abstract

Complete, accurate and up-to-date topographic data is of vast importance as it is widely required by different government agencies, non-governmental organisations, the private sector as well as the general public for urban mapping, rural development and environmental management, to mention but a few applications. Efficient semi-automatic methods for detecting settlements as change area indicators are required in order to achieve a sustainable up-to-date topographic database. This study reviewed the capability of geographic object based image analysis (GEOBIA) as a semi-automated method for settlement detection using 2012 SPOT 5imagery in the KwaZulu-Natal Province, South Africa.


The application of GEOBIA provide the ability to segment imagery into areas resembling features of interest. For this study GEOBIA settlement detection provided 70.7% overall accuracy while the existing semi-automated South African global human settlement layer (SA_GHSL) had 60% overall accuracy. These results presents an opportunity to apply GEOBIA semi-automated method to target areas of new settlement development more efficiently and with consistent repeatable manner. Thus assisting topographic update analyst to be drawn to more areas of new settlement development at an enhanced efficient rate. However the spectral variability of roof tops which are prominent identifiable feature by remote sensing for settlement areas prove to be the most challenging obstacle towards semi-automated settlement detection.


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eISSN: 2225-8531