No / Brochs are monumental Iron Age (c.400–200 BC) drystone towers or roundhouses. They are only found in Scotland, particularly the Atlantic north and west. Whilst the structural layout of brochs has long been debated, few measured surveys have been conducted. Three significant broch sites form the tentative World Heritage site of “Mousa, Old Scatness and Jarlshof: the Zenith of Iron Age Shetland” (UNESCO in Mousa, Old Scatness and Jarlshof: the zenith of Iron Age Shetland, UNESCO (2019) Mousa, Old Scatness and Jarlshof: the zenith of Iron Age Shetland. http://whc.unesco.org/en/tentativelists/5677. Accessed 9 Aug 2019). All three sites have undergone new surveys as part of a collaborative doctoral partnership research project. This chapter presents a diachronic perspective using digital documentation techniques to detect stone displacement and weathering at the site of Old Scatness using historic imagery, including photographs from the Old Scatness excavations (1995–2006) and regular condition monitoring undertaken by Shetland Amenity Trust to undertake retrospective digital structure-from-motion (SfM) photogrammetry. Whilst point clouds and 3D meshes were successfully generated from low-resolution digital images, analogue film transparencies without metadata could not produce accurate geospatial data without manually trying to extant reference data. It was possible to detect displacements in stonework over time by comparing two meshes together and measuring the distances between vertex point pairs. The reliability and accuracy of these results were dependent on how well pairs of meshes could be aligned.

Yes / Speed optimization of liner vessels has significant economic and environmental impact for reducing fuel cost and Green House Gas (GHG) emission as the shipping over maritime logistics takes more than 70% of world transportation. While slow steaming is widely used as best practices for liner shipping companies, they are also under the pressure to maintain service level agreement (SLA) with their cargo clients. Thus, deciding optimal speed that minimizes fuel consumption while maintaining SLA is managerial decision problem. Studies in the literature use theoretical fuel consumption functions in their speed optimization models but these functions have limitations due to weather conditions in voyages. This paper uses weather archive data to estimate the real fuel consumption function for speed optimization problems. In particular, Copernicus data set is used as the source of big data and data mining technique is applied to identify the impact of weather conditions based on a given voyage route. Particle swarm optimization, a metaheuristic optimization method, is applied to find Pareto optimal solutions that minimize fuel consumption and maximize SLA. The usefulness of the proposed approach is verified through the real data obtained from a liner company and real world implications are discussed.