Beyond the picturesque: analysing the information content of airborne remotely sensed data for understanding prehistoric sites.
Start date: 17 August 2009
The term 'British prehistory' may conjure images of outstanding sites like Stonehenge, however the majority of prehistoric sites, particularly those in areas of intensive agricultural production are represented only by ephemeral remains which can be difficult to identify. Where earthworks exist they are often degraded by agricultural activity. Commonly features have no upstanding remains and are identified only when changes in soil moisture and vegetation become visible on aerial photography in more extreme environmental conditions. In order to improve our detection of these important remains, this research proposes to use a multi-sensor approach to airborne survey of historic landscapes. Although aerial imaging for identifying archaeological sites has been practised for more than a century in Britain, the use of airborne digital remote sensing has enjoyed a recent resurgence with the increasing availability of lidar data to historic environment professionals. The use of lidar elevation data to identify sites of archaeological interest within the landscape is now well attested (Bewley et al., 2005; Devereux et al., 2005; Challis & Howard, 2007) and 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 (Challis, 2005a; Challis, 2005b; Oxford Archaeology North, 2008).
These important recent studies using lidar data can be added to the more established work on multispectral data both in the UK and elsewhere (Donoghue & Shennan, 1988; Powlesland et al., 2006; Winterbottom & Dawson , 2005; Traviglia, 2006). 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 information content from digital remotely sensed datasets is in its infancy in the UK. Early studies of lidar intensity in combination with elevation have illustrated the potential of these data but have also highlighted caveats to their use (Paul Cripps pers comm; (Challis et al., 2008). 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 and rarely have multiple remotely sensed datasets been used in combination for a single site.
This research proposes that through systematic processing and analysis of lidar elevation and intensity data in combination with hyperspectral imaging, it is hypothesised that ephemeral, prehistoric feature recognition rates will be substantially improved. In addition, it is hoped that by analysing the full spectral content of the datasets, it will be possible to make clearer inferences about features based on their associated geophysical and vegetation properties. The poster will present some methods and results from the initial year of the project along with directions for future research.