Historic aerial images are invaluable sources of aid to archaeological research. Often collected with large-format photogrammetric quality cameras, these images are potential archives of multidimensional data that can be used to recover information about historic landscapes that have been lost to modern development. However, a lack of camera information for many historic images coupled with physical degradation of their media has often made it difficult to compute geometrically rigorous 3D content from such imagery. While advances in photogrammetry and computer vision over the last two decades have made possible the extraction of accurate and detailed 3D topographical data from high-quality digital images emanating from uncalibrated or unknown cameras, the target source material for these algorithms is normally digital content and thus not negatively affected by the passage of time. In this paper, we present refinements to a computer vision-based workflow for the extraction of 3D data from historic aerial imagery, using readily available software, specific image preprocessing techniques and in-field measurement observations to mitigate some shortcomings of archival imagery and improve extraction of historical digital elevation models (hDEMs) for use in landscape archaeological research. We apply the developed method to a series of historic image sets and modern topographic data covering a period of over 70 years in western Sicily (Italy) and evaluate the outcome. The resulting series of hDEMs form a temporal data stack which is compared with modern high-resolution terrain data using a geomorphic change detection approach, providing a quantification of landscape change through time in extent and depth, and the impact of this change on archaeological resources.

For future landscapes to be sustainable, significant changes in land-use and management practices will be needed. This article argues that landscape archaeology can make distinctive contributions to sustainability in two ways: firstly, by researching what were and were not sustainable ways of life in the past, and secondly by using this knowledge to explain how landscapes of the past differed to those in the present, and in doing so to disrupt the invented connections between past societies, tradition, heritage and conservation. The article draws on three case-studies in China, the Mediterranean and the UK to suggest that archaeological knowledge could be used to help stakeholders imagine future landscapes which are better and more sustainable than those of today. To succeed archaeologists will need to make deeper commitments to transdisciplinary work.

Agricultural terraces provide farmers in hilly landscapes with effective ways to increase the area available for crops. They mitigate the risks of soil erosion and promote crop productivity by slowing surface water runoff and retaining moisture. As in other parts of the world, terraces have been constructed and used in the Mediterranean for millennia. The availability of terraced agriculture had important socio-economic, ecological, and environmental implications for past societies. However, the chronology of construction, use, and abandonment of terraces in different regions remains uncertain. A more robust set of chronological data will allow better assessment of whether terrace agriculture was a resilient strategy in the face of past economic or ecological instability and, in turn, inform how terraces could be used to address future agricultural and environmental challenges. In this paper, we review the application of luminescence dating to terrace sediments, the key challenges involved, and the currently published data which include over 250 luminescence ages. We also discuss the use of a multidisciplinary approach involving other geoarchaeological tools (e.g., use of GIS analyses, field-based luminescence readers, and micromorphology) to enhance the ways that past terrace systems can be understood. Terrace systems are inextricably linked to sustainable land use across the Mediterranean. Luminescence dating methods, therefore, have a crucial role to play in understanding the complexities of past and future landscape change.

Aerial reconnaissance continues to be a vital tool for landscape-oriented archaeological research. Although a variety of remote sensing platforms operate within the earth’s atmosphere, the majority of aerial archaeological information is still derived from oblique photographs collected during observer-directed reconnaissance flights, a prospection approach which has dominated archaeological aerial survey for the past century. The resulting highly biased imagery is generally catalogued in sub-optimal (spatial) databases, if at all, after which a small selection of images is orthorectified and interpreted. For decades, this has been the standard approach. Although many innovations, including digital cameras, inertial units, photogrammetry and computer vision algorithms, geographic(al) information systems and computing power have emerged, their potential has not yet been fully exploited in order to re-invent and highly optimise this crucial branch of landscape archaeology. The authors argue that a fundamental change is needed to transform the way aerial archaeologists approach data acquisition and image processing. By addressing the very core concepts of geographically biased aerial archaeological photographs and proposing new imaging technologies, data handling methods and processing procedures, this paper gives a personal opinion on how the methodological components of aerial archaeology, and specifically aerial archaeological photography, should evolve during the next decade if developing a more reliable record of our past is to be our central aim. In this paper, a possible practical solution is illustrated by outlining a turnkey aerial prospection system for total coverage survey together with a semi-automated back-end pipeline that takes care of photograph correction and image enhancement as well as the management and interpretative mapping of the resulting data products. In this way, the proposed system addresses one of many bias issues in archaeological research: the bias we impart to the visual record as a result of selective coverage. While the total coverage approach outlined here may not altogether eliminate survey bias, it can vastly increase the amount of useful information captured during a single reconnaissance flight while mitigating the discriminating effects of observer-based, on-the-fly target selection. Furthermore, the information contained in this paper should make it clear that with current technology it is feasible to do so. This can radically alter the basis for aerial prospection and move landscape archaeology forward, beyond the inherently biased patterns that are currently created by airborne archaeological prospection.