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Archaeological remote sensing: visualisation and analysis of grass-dominated environments using airborne laser scanning and digital spectral data.

Bennett, R., 2011. Archaeological remote sensing: visualisation and analysis of grass-dominated environments using airborne laser scanning and digital spectral data. Doctoral Thesis (Doctoral). Bournemouth University.

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The use of airborne remote sensing data for archaeological prospection is not a novel concept, but it is one that has been brought to the forefront of current work in the discipline of landscape archaeology by the increasing availability and application of airborne laser scanning data (ALS). It is considered that ALS, coupled with imaging of the non-visible wavelengths using digital spectral sensors has the potential to revolutionise the field of archaeological remote sensing, overcoming some of the issues identified with the most common current technique of oblique aerial photography. However, as with many methods borrowed from geographic or environmental sciences, archaeologists have yet to understand or utilise the full potential of these sensors for deriving archaeological feature information. This thesis presents the work undertaken between 2008-11 at Bournemouth University that aimed to assess the full information content of airborne laser scanned and digital spectral data systematically with respect to identifying archaeological remains in non-alluvial environments. A range of techniques were evaluated for two study areas on Salisbury Plain, Wiltshire (Everleigh and Upavon) to establish how the information from these sensors can best be extracted and utilised. For the Everleigh Study Area archive airborne data were analysed with respect to the existing transcription from archive aerial photographs recorded by English Heritage's National Mapping Programme. At Upavon, spectral and airborne laser scanned data were collected by the NERC Airborne Research and Survey Facility to the specifications of the project in conjunction with a series of ground-based measures designed to shed light on the contemporary environmental factors influencing feature detectability. Through the study of visual and semi-automatic methods for detection of archaeological features, this research has provided a quantitative and comparative assessment of airborne remote sensing data for archaeological prospection, the first time that this has been achieved in the UK. In addition the study has provided a proof of concept for the use of the remote sensing techniques trialled in temperate grassland environments, a novel application in a field previously dominated by examples from alluvial and Mediterranean landscapes. In comparison to the baseline record of the Wiltshire HER, ALS was shown to be the most effective technique, detecting 76% of all previously know features and 72% of all the total number of features recorded in the study. Combining the spectral data from both January and May raised this total to 83% recovery of all previously known features, illustrating the value of multi-sensor survey. It has also been possible to clarify the strengths and weaknesses of a wide range of visualisation techniques through detailed comparative analysis and to show that some techniques in particular local relief modelling (ALS) and single band mapping (digital spectral data) are more suited to the aims of archaeological prospection than others, including common techniques such as shaded relief modelling (ALS) and True Colour Composites (digital spectral data). In total the use of “non-standard” or previously underused visualisation techniques was shown to improve feature detection by up to 18% for a single sensor type. Investigation of multiple archive spectral acquisitions highlighted seasonal differences in detectability of features that had not been previously observed in these data, with the January spectral data allowing the detection of 7% more features than the May acquisition. A clearer picture of spectral sensitivity of archaeological features was also gained for this environment with the best performing spectral band lying in the NIR for both datasets (706-717nm) and allowing detection c.68% of all the features visible across all the wavelengths. Finally, significant progress has been made in the testing of methods for combining data from different airborne sensors and analysing airborne data with respect to ground observations, showing that Brovey sharpening can be used to combine ALS and spectral data with up to 87% recovery of the features predicted by transcription from the contributing source data. This thesis concludes that the airborne remote sensing techniques studied have quantifiable benefit for detection of archaeological features at a landscape scale especially when used in conjunction with one another. The caveat to this is that appropriate use of the sensors from deployment, to processing, analysis and interpretation of features must be underpinned by a detailed understanding of how and why archaeological features might be represented in the data collected. This research goes some way towards achieving this, especially for grass-dominated environments but it is only with repeated, comparative analyses of these airborne data in conjunction with environmental observations that archaeologists will be able to advance knowledge in this field and thus put airborne remote sensing data to most effective use.

Item Type:Thesis (Doctoral)
Additional Information:If you feel that this work infringes your copyright please contact the BURO Manager.
Group:Faculty of Science & Technology
ID Code:20459
Deposited On:01 Oct 2012 14:26
Last Modified:09 Aug 2022 16:03


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