Excavation and piling works related to seafront development in Oslo's historic harbour area need to mitigate the risk of damaging buried archaeological objects. In the Bjørvika harbour in Oslo, Norway, electrical resistivity tomography was performed to detect structures with potential archaeological value. A 2.5 dataset consisting of four equally spaced parallel lines was collected, trimmed, and systematically processed with both 2D and 3D inversion routines. The results were in good agreement with known underground features, and for the present dataset, an iteratively reweighted least squares 2D inversion was clearly preferable over a 3D inversion. This conclusion is based on differences in model resolution, data processing costs, and the value of the final product for engineering decision-making.agreeing well with rectangular wooden quay or wharf structures later excavated (Bazin et al. 2012;Pfaffhuber et al. 2012).The present 2.5D dataset allows for both 2D and 3D inversions, and was acquired by the Norwegian Geotechnical Institute on behalf of HAV Eiendom on a harbour property intended for an energy central unit and a beach-service building.The inversion algorithm and parameters should be carefully chosen according to the data and problem at hand. A popular approach is the standard smoothness-constrained least squares (SCLS) inversion (also known as the Occam inversion presented by Constable et al. (1987)), which creates a ground model fitting the data with minimum complexity. However, in case the data are especially noisy and/or the real resistivity distribution features large contrasts and blocky or layered structures, the smoothness-constrained inversion tends to smear out real boundaries and adjusts the model for outliers and erroneous data. In such cases, the iteratively reweighted least squares (IRLS) inversion (Farquharson and Oldenburg 1998;Loke, Acworth and Dahlin 2003) has proven to be more appropriate.We aim to analyse the engineering usability of two different implementations of the IRLS inversion algorithm by comparing how well the results fit with the ground truth and to determine whether 3D processing gives enough additional information on satisfying quality for the additional cost and effort.
Maria Pilar-Reis: Las termas y balnea romanos de Lusitania. Mérida: Librería Museo Nacional de Arte Romano, José Ramón Mélida [2005]. 205 S. 82 Abb. 4° (Studia Lusitana. 1.).
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