Analysing the information content of airborne remotely sensed data for archaeological prospection

This source preferred by Ross Hill, Andrew Ford and Kate Welham

Authors: Bennett, R., Welham, K., Hill, R.A. and Ford, A.L.J.

Start date: 25 September 2009

The use of aerial photographs for identifying archaeological sites has been practised for more than a century in Britain. In more recent times airborne digital remote sensing techniques (including lidar) have become available to historic environment professionals. The use of lidar elevation data to identify sites of archaeological interest within the landscape is now well attested. The number of applications in the commercial sector within the UK has grown substantially in the last five years with the increased availability of Environment Agency data.

Recent studies using lidar data can be added to the more established work on multispectral data both in the UK and elsewhere. Familiarity with the remotely sensed datasets available and processing techniques has progressed our ability to identify possible sites of archaeological interest within lidar and multispectral data. But what additional information can airborne remotely sensed data offer us about the sites themselves? The possibility of extracting further archaeological information content from digital remotely sensed datasets is in its infancy in the UK. Early studies of lidar intensity in combination with elevation data have illustrated their potential, but have also highlighted caveats to their use. Furthermore, while the commercial sector has driven the majority of research undertaken to date in this field in the UK, applications for academic research have been limited. Rarely have multiple airborne remotely sensed datasets been used in combination for a single site.

This research proposes that through systematic, tailored processing and analysis of lidar elevation and intensity data in combination with multispectral imaging, it will be possible to improve archaeological feature recognition rates compared with current 'standard' methods. In addition, it is hypothesised that by analysing the full content of the combined datasets, and comparing them to ground-based geophysical data for the same area, it will be possible to make clearer inferences both about the features represented and the broader landscape transformation processes affecting them.

Data will initially be analysed for a number of pilot locations in the Salisbury Plain and Avebury areas of Wiltshire, England. This talk will present the progress in the first year of this research, outlining the methodological approach taken and the preliminary results from the pilot studies.

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