DETECTING ASH MIDDENS USING REMOTE SENSING TECHNIQUES: THE CASE OF SOUTHERN GAUTENG, SOUTH AFRICA
Date
2022-12
Authors
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Publisher
South African Archaeological Bulletin
Abstract
South Africa is home to thousands of architectural remnants such as stone-walled structures and ash middens from the Late Iron Age (AD 1300–1800). Ash middens reflect the political and economic lifeways of Iron Age communities. However, the process of identifying and mapping ash middens with traditional survey techniques can be time-consuming and difficult due to dense vegetation. This report aims to assess the performance of two supervised classification techniques, Maximum Likelihood Classification (MLC) and Support Vector Machine (SVM), in detecting ash middens on two multispectral satellite images – GeoEye1 and SPOT5 – in Gauteng, South Africa. The objective is to also assess the ability of the sensors in capturing the spectral signatures of the ash middens. The high reflectance of ash middens relative to other land-cover classes indicates that they have distinct spectral signatures. GeoEye1 is better than SPOT5 in the detection of ash middens because its high spectral and spatial resolution allows for more detailed and accurate mapping. SVM, although advanced, is not a significantly better classification technique for detecting ash middens compared to MLC. This report presents a promising avenue for detecting archaeological ash middens in this part of the world using remote sensing techniques.
Description
Keywords
ash middens || classification || GeoEye1 || SPOT5 || stonewalled structures.