Cadastres from the 19th century are a complex as well as rich source for historians and archaeologists, the study of which presents great challenges. For archaeological and historical remote sensing, we have trained several Deep Learning models, CNNs, and Vision Transformers to extract large-scale data from this knowledge representation. We present the principle results of our work here and demonstrate our browser-based tool that allows researchers and public stakeholders to quickly identify spots that featured buildings in the 19th century Franciscean cadastre. The tool not only supports scholars and fellow researchers in building a better understanding of the settlement history of the region of Styria; it also helps public administration and fellow citizens to swiftly identify areas of heightened sensibility with regard to the cultural heritage of the region.
Göderle et al. (Fri,) studied this question.