Photogrammetric re-discovery of the hidden long-term landscapes of western Thessaly, central Greece

This paper introduces a novel workflow for the reconstruction of nowadays disappeared cultural landscapes based on the extraction of morphological information from historic aerial photographs. This methodology has been applied for the first time for the detection, classification and characterisation of upstanding, flattened and buried archaeological sites and various off-site ancient landscape features in the plain of Karditsa, western Thessaly. Although Thessaly has been the focus of prehistoric, and especially Neolithic, research in Greece, since the beginning of the 20th century, western Thessaly has not received as much archaeological attention and its archaeological record remains rather scanty. Moreover, an extensive land reclamation project implemented in the western Thessalian plain during the early 1970s resulted in the flattening of habitation tells and funerary sites of all periods. Thus, recognition of archaeological sites and relict landscape features becomes extremely difficult, whereas standard landscape analysis and application of mainstream Remote Sensing (RS) techniques based on multispectral satellite images are problematic. Digital photogrammetric reconstruction techniques and the subsequent GIS-based treatment of the results allowed overcoming these challenging limitations: the combined use of pre-1970s aerial photographs with later imagery provided a powerful means to reconstruct the landscape before the land reclamation process, using a workflow designed to highlight photogrammetry-derived topographic differences and multi-temporal imagery analysis. Hundreds of previously unknown mounded archaeological sites, as well as other ancient landscape traits such as roads, city grids and field systems were detected. More importantly, invaluable insights into the type and character of these archaeological features were gained, which would have been impossible to obtain by conventional RS techniques. (C) 2015 Elsevier Ltd. All rights reserved.