This paper presents the first results of the geoarchaeological study of an unusual hilltop wetland, located within the protohistoric proto‐urban site of Corent in the French Massif Central. This small depression offers an exceptionally local sedimentary record that provided valuable data on long‐term human–environment interactions, as well as proto‐urbanization of the first millennium B.C.E. Field survey revealed a major archaeological discovery: a large ensemble of 114 Iron Age storage pits excavated in clayey deposits. The geoarchaeological analysis of stratigraphic logs and cross‐sections completed by geophysical survey and radiocarbon dating allowed us to refine the chronology of these structures. Here, we suggest these structures are probably contemporary with the Hallstatt occupation of the site (600–425 B.C.E.), consistent with the emergence at Corent of a short‐lived proto‐urban environment during this period. These investigations also allowed us to characterize the main evolution phases of the basin and the diversity of human impacts from first disturbance in the Early Neolithic to its final destruction in the Roman period. These findings highlight the nonlinear nature of the socio‐environmental interactions and the definitive shift to an “anthroposystem” as a consequence of major disturbance in the first Iron Age, centuries before the development of urban settlements in the oppida period.
ALS-derived raster visualization techniques have become common in recent years, opening up new possibilities for subtle landform detection in earth sciences and archaeology, but they have also introduced confusion for users. As a consequence, the choice between these visualization techniques is still mostly supported by empirical knowledge. Some attempts have been made to compare these techniques, but there is still a lack of analytical data. This work proposes a new method, based on gradient modelling and spatial statistics, to analytically assess the efficacy of these visualization techniques. A selected panel of outstanding visualization techniques was assessed first by a classic non-analytical approach, and secondly by the proposed new analytical approach. The comparison of results showed that the latter provided more detailed and objective data, not always consistent with previous empirical knowledge. These data allowed us to characterize with precision the terrain for which each visualization technique performs best. A combination of visualization techniques based on DEM manipulation (Slope and Local Relief Model) appeared to be the best choice for normal terrain morphometry, occasionally supported by illumination techniques such as Sky-View Factor or Negative Openness as a function of terrain characteristics.
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