Abstract

In historical urban centres, the superimposition of excavation and deposition activities over time has resulted in an irregular spatial distribution of anthropogenic deposits, which may reach considerable thicknesses. The detection of those thicknesses requires extensive investigations. Broad borehole and geophysical campaigns cost time and money, consequently at the urban-planning level, it is usual to shift to an estimation of thicknesses, which may be performed through map-algebra operations, that is, by subtracting from the modelled ground surface the elevation of the anthropogenic-deposit basal surface. The latter is implemented through the interpolation of point elevation data, which are generally provided by borehole logs. Despite the development of advanced spatial interpolation methodologies, previous modelling results in the literature show that if the process is affected by insufficient input data, it produces imprecise interpolation outputs. This paper reports an interdisciplinary methodology aiming at enhancing elevation datasets, in order to obtain more accurate digital elevation models. The increase in number and spatial distribution of input points is achieved through past-landscape analyses mainly based on elevation data given by borehole logs, available archaeological reports and historical topographic maps, these being generally available for historical urban centres. The methodology was tested in an urban sector of Rome, where significant activities have been performed for millennia particularly during the Roman Age. A reliable model of the basal surface of the anthrostrata led to a better estimation of the spatial distribution of such deposits and, in addition, revealed the original topographic surface, as modified by human activities.

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