Sampling past landscapes: Methodological inquiries into the bias problems of recording archaeological surface assemblages

For our understanding of the past, archaeological field survey is an essential fieldwork method. It is a form of prospection that aims to catalogue archaeological remains in a specified research area. Many modern landscape archaeological investigations build on these datasets to be able to understand socio-economic, demographic, and political developments for specific historical periods on regional scales. However, the reliability of archaeological field survey has been the subject of debate since the advent of this fieldwork technique. The main issue here is to what degree the collected samples actually result in a representative picture of the archaeological surface record, and the past human activity that led to its formation. One of the important methodological discussions concerning the reliability of archaeological field survey revolves around a range of bias problems in the formation of the datasets. With this thesis, some of the major, and interrelated, research biases in the formation of datasets in archaeological field survey are assessed. Based on these investigations it may be concluded that archaeological field survey can improve its robustness in collecting reliable samples of the surface record, as well as develop approaches to specific research biases, such as ground visibility. This eventually should allow for an improved perspective on the archaeological surface record, and will increase the representativity of the collected data which eventually permits the attestation of a more detailed, rich and varied typology of archaeological remains