This article presents results of a case study within a project that seeks to develop heavily automated analysis of digital topographic data to extract archaeological information and to expedite large area mapping. Drawing on developments in computer vision and machine learning, this has the potential to fundamentally recast the capacity of archaeological prospection to cover large areas and deal with mass data, breaking a dependency on human resource. Without such developments, the potential of the vast amount of archaeological information embedded in large topographic and image‐based datasets cannot be realized. The purpose of the case study reported on here is to assess existing developments in a Norwegian study against digital topographic data for the island of Arran, Scotland, examining the transferability of the approach and providing a proof of concept in a Scottish context. For Arran, three monument classes were assessed – prehistoric roundhouses, shieling huts of medieval or post‐medieval date, and small clearance cairns. These present different challenges to detection, with preliminary results ranging from a manageable mix of false positives and true identifications to the chaotic. The influence of variable morphology and the occurrence of other, largely natural, objects of confusion in the landscape is discussed, highlighting the potential improvements in automated detection routines offered by adding anthropogenic and natural false positives to additional confusion classes.

The increasing availability of multi-dimensional remote-sensing data covering large geographical areas is generating a new wave of landscape-scale research that promises to be as revolutionary as the application of aerial photographic survey during the twentieth century. Data are becoming available to historic environment professionals at higher resolution, greater frequency of acquisition and lower cost than ever before. To take advantage of this explosion of data, however, a paradigm change is needed in the methods used routinely to evaluate aerial imagery and interpret archaeological evidence. Central to this is a fuller engagement with computer-aided methods of feature detection as a viable way to analyse airborne and satellite data. Embracing the new generation of vast datasets requires reassessment of established workflows and greater understanding of the different types of information that may be generated using computer-aided methods.

Historic Environment Scotland (HES) is the lead public body which investigates, promotes and cares for the historic environment in Scotland. It undertakes a range of archaeological airborne work from detailed documentation of individual sites to extensive national programmes of prospection. In undertaking this work HES draws on a variety of aerial platforms to collect imagery, including light aircraft and unmanned aerial vehicles (UAV—used throughout this paper as an umbrella term). In all cases, the archaeological questions at hand are the key driver for choice of methodology and platforms, recognising that different types of survey and documentation demand different responses. Differing strands of aerial work will be briefly described, followed by short case studies that illustrate the range of our activities, concluding with thoughts on the context of UAV work for archaeological applications.

This article reviews the potential of archives of historic aerial photographs for European archaeology. Their roles in primary site discovery, in monitoring condition and material change, and in understanding landscape development with particular reference to the implementation of the European Landscape Convention are discussed. The major sources are briefly described and their characteristics outlined. The impacts that differing national and regional research traditions and heritage policy have on the use of these archival collections is discussed in the framework of issues of variable accessibility and approaches to ensuring appropriate uses, including identifying limitations.

While the National Record of the Historic Environment (NRHE) in Scotland contains valuable information on more than 170,000 archaeological monuments, it is clear that this dataset is conditioned by the disposition of past survey and changing parameters of data collection strategies over many decades. This highlights the importance of creating systematic datasets, in which the standards to which they were created are explicit, and against which the reliability of our knowledge of the material remains of the past can be assessed. This paper describes issues of data structure and reliability, then discussing the methodologies under development for expediting the progress of national-scale mapping with specific reference to the Isle of Arran. Preliminary outcomes of a recent archaeological mapping project of the island, which has been used to develop protocols for rapid large area mapping, are outlined. The primary sources for the survey were airborne laser scanning derivatives and orthophotographs, supplemented by field observation, and the project has more than doubled the number of known monuments of Arran. The survey procedures are described, followed by a discussion of the utility of ‘general purpose’ remote sensed datasets, focusing on the assessment of strengths and weaknesses for rapid mapping of large areas.