Research Outputs (Geography, Archaeology and Environmental Studies)

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    Investigation of Inter-analyst Variability in Stone-walled Structure Classification
    (2013-07-01) Hunt, Tamsin
    For many years stone-walled structures have been classified into different groups using aerial photography. The development of technology such as Google Earth and Geographic Information Systems has resulted in an increase in such classifications. What must be considered, however, is to what extent the results differ depending on the person analysing the structures. A study has been conducted by three different analysts, classifying the stone-walled structures south of the Suikerbosrand Game Reserve. A statistical and visual comparison of the three sets of analyses using Google Earth, QGIS and CrimeStat. These methods showed that variability is obvious between the sets of classifications. It is then important to consider what causes the variability in the classifications and how it can be remedied. This is important as variability in the classifications of stone-walled structures will have an effect on the larger interpretations of the sites and the people affiliated with them.
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    A study of inter-analyst variability in the classification of stone-walled structures in southern Gauteng, South Africa
    (2013-04-18) MacRoberts, Rebecca
    The study of stone-walled structures within the last 1000 years in southern Africa can help archaeologists to understand how the landscape was peopled. Google Earth and GIS can make data capture easier, but when diferent analysts are involved, there can be significant variability in their results. By comparing data classified by three researchers in the same study area, it was possible to quantify inter-analyst variability and to query where and why it occured. The quality of Google Earth imagery had much influence in introducing inter-analyst variability. Subjective decisions on classification also introduced high amounts of variability. With more intensive training on classification and better imagery, inter-analyst variability can be reduced.