AbstractTemperate river floodplains present something of a paradox, whereby potentially rich archaeological and palaeoenvironmental archives are difficult to locate and analyse. This is because the deposition of thick, fine-grained alluvial sediments conceals archaeological resources. It also, renders conventional forms of archaeological prospection ineffective and other forms of investigation (e.g. site stripping/excavation) to be costly, requiring a targeted approach. Despite this, when cultural and environmental materials are encountered, they can be extremely well-preserved due to anoxic conditions caused by high water tables. These challenges are further exacerbated by increasing threats from infrastructure development, aggregate extraction or increases in the frequency and intensity of flooding due to climate change. To mitigate this, archaeologists have developed predictive and subsurface mapping techniques to improve our understanding, and determine the significance of, deeply buried deposits through geoarchaeological deposit modelling. This is normally achieved through a combination of existing and bespoke geotechnical borehole logs and other archaeological investigations, as well as geological and topographic map data. However, the integration of remote sensing datasets has significant potential to aid these investigations, but this has not previously been systematically evaluated.
The emergence of lightweight Unmanned Aerial System (UAS) mounted sensors and advancements in spaceborne capabilities of multi- and hyperspectral imagery and Synthetic Aperture Radar (SAR) present substantial opportunities for geoarchaeological research. This study provides a thorough examination of these contemporary remote sensing technologies to reconstruct and map archaeological resources within river floodplains. It has captured and analysed a large volume of remote sensing data within the alluvial valleys of the Rivers Lugg and Wye in Herefordshire, UK. The results have demonstrated that these methods have a high capacity to identify alluvial landforms and archaeological deposits. Through a series of quantitative assessments, it was also shown that the use of complementary remote sensing data can enable a significant enhancement to standard approaches to deposit modelling. Consequently, the inclusion of these datasets can enable an improved understanding of subsurface complexity across alluvial environments and provide a more reliable and detailed representation of archaeological resources. This ultimately facilitates more effective design and implementation of archaeological investigation, evaluation, or mitigation strategies, ahead of development. Given that these datasets can be low cost and cover large areas, their wider application within geoarchaeological research can facilitate a significant improvement to the understanding of temperate river systems at a previously unachievable scale.
|Date of Award
|Chris Carey (Supervisor), Matthew Brolly (Supervisor) & Niall Burnside (Supervisor)