The Detection of Archaeological residues using Remote Sensing Techniques (DART)

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This project will increase the knowledge about, and build transferable expertise in, the remote sensing (RS) of archaeological residues (AR). Current archaeological RS techniques have evolved with variable understanding of the physical, chemical, biological and environmental processes involved. Thus current detection strategies do not allow systematic AR assessment leading to sub-optimal heritage management and development control. This project will focus on analysing the physical and environmental factors that influence AR contrast dynamics with the overall aim of improving site and feature detection.Archaeological RS techniques rely on the ability of a sensor to detect the contrast between an AR and its immediate surroundings or matrix. AR detection is influenced by many factors - changes in precipitation, temperature, crop stress/type, soil type and structure and land management techniques. These factors vary seasonally and diurnally, meaning that the ability to detect an AR with a specific sensor changes over time.Without understanding the processes that affect the visibility and detection of ARs (directly and by proxy), prospection techniques will remain somewhat ad-hoc and opportunistic. Enhanced knowledge of ARs is important in the long-term curation of a diminishing heritage and will provide cost savings to operational works (through more effective mitigation). This is important in environments where traditional optical aerial photography has been unresponsive (e.g pasture and clay soils).The project is timely considering the recent development of high spatial and spectral resolution ground, air and satellite sensors.The project involves 4 stages:1 Identifying appropriate candidate sites and sampling methodology2 Field measurements and collecting and analysing field samples from sites under different conditions3 Physical modelling, feedback, knowledge articulation4 EvaluationSites will be chosen on the basis of contrasting ARs, soil and land management conditions etc. Close liaison with curatorial agencies (with excavation data) is necessary to ensure a representative range of AR types is identified. It will be important to include sites with varying environmental conditions and AR types (buried soils, 'negative' features such as ditches, buried masonry and surface materials).To determine contrast factors strategic samples and measurements will be taken on and around the AR at different times of the day and year to ensure that a representative range of conditions is covered. Field measurements will include geophysical and hyperspectral surveys, thermal profiling, soil moisture and spectral reflectance. Laboratory analysis of samples will include geochemistry and particle size.Models will be developed that translate these physical values into spectral, magnetic, electrical and acoustic measures in order to determine contrast parameters. Data fusion and knowledge reasoning techniques will be used to develop management tools to improve the programming of surveys. These tools will be used to deploy sensors, including aerial hyperspectral devices, for evaluation purposes.In summary, this project will impact on and develop:1 Baseline understanding and knowledge about AR contrast processes and preservation dynamics: a. leading to better management and curation b. providing data to model environmental impact on ARs c. enhancing the understanding of the resource base2 The identification of suitable sensors and conditions for their use (and feedback to improve sensor design)3 Data fusion techniques (physical models, multi-sensor data and domain knowledge) to improve AR identification4 An Interdisciplinary network between remote sensing, soil science, computing and heritage professionals5 Techniques for researchers to access data archives more effectivelyWe believe that the results will have national impact and have the potential for transfer throughout the world.