Auswirkungen von Rapid Climate Changes und menschlicher Aktivität auf die holozäne hydro-sedimentäre Dynamik Mitteleuropas (Modellregion lössbedecktes Weiße Elster-Einzugsgebiet)
Zusammenfassung der Projektergebnisse
The primary result of the sub-project is the creation of a rich data set with structed data on the respective sites, their location, dating, discovery, inventory and documentation. It comprises a total of 2585 sites distributed over an area of 3026 km2. These are distributed over the pre- and protohistoric epochs as follows: 70 Palaeolithic, 55 Mesolithic, 1365 Neolithic, 364 Bronze Age, 232 Pre-Roman Iron Age, 102 Roman Iron Age and 397 sites of unknown date (potential burial mounds etc.). The use of the local area files proved to be extremely valuable, because 1349 out of 2585 sites have not been cited in the archaeological literature so far. This data set offers a firm basis for futher investigations on different periods and timescales. Furthermore, as a first substantive result a detailed archaeological study on Neolithic site distribution patterns and settlement dynamics in the catchment of the Weiße has been competed by the end of the funding period. The paper includes the application of innovative methods such as machine learning and site exploitation territories. Further studies on other aspects are finished or in preparation. A final interdisciplinary synthesis has not yet been realized since the working status of the other sub-projects by the end of the funding period of the archaeological projects was not advanced enough. We will come back on these questions.
Projektbezogene Publikationen (Auswahl)
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Holocene floodplain evolution in a central European loess landscape – geoarchaeological investigations of the lower Pleiße valley in NW Saxony. E&Amp;G Quaternary Science Journal, 68(2), 95–105.
Tinapp, Christian; Heinrich, Susann; Herbig, Christoph; Schneider, Birgit; Stäuble, Harald; Miera, Jan & von Suchodoletz, Hans
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Large-scale investigations of Neolithic settlement dynamics in Central Germany based on machine learning analysis: A case study from the Weiße Elster river catchment. PLOS ONE, 17(4), e0265835.
Miera, Jan Johannes; Schmidt, Karsten; von Suchodoletz, Hans; Ulrich, Mathias; Werther, Lukas; Zielhofer, Christoph; Ettel, Peter & Veit, Ulrich
