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.\n\nArchaeological 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.\n\nWithout 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).\n\nThe project is timely considering the recent development of high spatial and spectral resolution ground, air and satellite sensors.\nThe project involves 4 stages:\n1 Identifying appropriate candidate sites and sampling methodology\n2 Field measurements and collecting and analysing field samples from sites under different conditions\n3 Physical modelling, feedback, knowledge articulation\n4 Evaluation\nSites 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).\n\nTo 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.\n\nModels 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.\n\nIn summary, this project will impact on and develop:\n1 Baseline understanding and knowledge about AR contrast processes and preservation dynamics:\n a. leading to better management and curation\n b. providing data to model environmental impact on ARs\n c. enhancing the understanding of the resource base\n2 The identification of suitable sensors and conditions for their use (and feedback to improve sensor design)\n3 Data fusion techniques (physical models, multi-sensor data and domain knowledge) to improve AR identification\n4 An Interdisciplinary network between remote sensing, soil science, computing and heritage professionals\n5 Techniques for researchers to access data archives more effectively\n\nWe believe that the results will have national impact and have the potential for transfer throughout the world.

In Europe, the total value of sewer assets amounts to 2 trillion Euros. The US Environmental Protection Agency estimates that water collection systems in the USA have a total replacement value between $1 and $2 trillion. Similar figures can be assigned to other types of buried pipe assets which supply clean water and gas. In China alone 40,000 km of new sewer pipes are laid every year. However, little is known about the condition of these pipes despite the pressure on water and gas supply utility companies to ensure that they operate continuously, safely and efficiently. In order to do this properly, the utility operator must identify the initial signs of failure and then respond to the onset of failure rapidly enough to avoid loss of potable water supply, wastewater flooding or gas escape. This is attempted through targeted inspection which is typically carried out through man-entry or with CCTV approaches, although more sophisticated (e.g. tethered) devices have been developed and are used selectively. Nevertheless, and in spite of the fact that the UK is a world leader in this research area, these approaches are slow and labour intensive, analysis is subjective, and their deployment disrupts traffic. Moreover, because these inspections are necessarily infrequent and only cover a small proportion of the pipe network, serious degradation is often missed and pipe failures occur unexpectedly, requiring emergency repairs that greatly disrupt life of the road and adjacent buried utility infrastructure. This Programme Grant proposes a radical change in terms of buried pipe sensing in order to address the issues of pipe inspection and rehabilitation. It builds upon recent advances in sensors, nano- and micro-electronics research, communication and robotic autonomous systems and aims to develop a completely new pervasive robotics sensing technology platform which is autonomous and covers the entire pipe network. These robots will be able to travel, cooperate and interrogate the pipes from the inside, detect the onset of any defects continuously, navigate to and zoom on sub-millimetre scale defects to examine them in detail, communicate and guide any maintenance equipment to repair the infrastructure at an early sign of deterioration. By being tiny, they do not present a danger of being stuck, blocking the pipe if damaged or run out of power. By being abundant, they introduce a high level of redundancy in the inspection system, so that routine inspection can continue after a loss of a proportion of the sensors in the swarm. By making use of the propagation of sonic waves and other types of sensing these robots can monitor any changes in the condition of the pipe walls, joints, valves and lateral connections; they can detect the early development and growth of sub-millimetre scale operational or structural faults and pipe corrosion. An important benefit of this sensing philosophy is that it mimics nature, i.e. the individual sensors are small, cheap and unsophisticated, but a swarm of them is highly capable and precise. This innovation will be the first of its kind to deploy swarms of miniaturised robots in buried pipes together with other emerging in-pipe sensor, navigation and communication solutions with long-term autonomy. Linked to the related previous work, iBUILD (EP/K012398), ICIF (EP/K012347) and ATU's Decision Support System (EP/K021699), this Programme Grant will create the technology that has flexibility to adapt to different systems of governance globally. This work will be done in collaboration with a number of industry partners who will help to develop a new set of requirements for the new pervasive robotic sensing platform to work in clean water, wastewater and gas pipes. They will support the formation and operation of the new research Centre of Autonomous Sensing for Buried Infrastructure in the UK and ensure that the results of this research have strong practical outcomes.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

The project aims to create a prototype multi-sensor device, and undertake fundamental enabling research, for the location of underground utilities by combining novel ground penetrating radar, acoustics and low frequency active and passive electromagnetic field (termed quasi-static field) approaches. The multi-sensor device is to employ simultaneously surface-down and in-pipe capabilities in an attempt to achieve the heretofore impossible aim of detecting every utility without local proving excavations. For example, in the case of ground penetrating radar (GPR), which has a severely limited penetration depth in saturated clay soils when deployed traditionally from the surface, locating the GPR transmitter within a deeply-buried pipe (e.g. a sewer) while the receiver is deployed on the surface has the advantage that the signal only needs to travel through the soil one way, thereby overcoming the severe signal attenuation and depth estimation problems of the traditional surface-down technique (which relies on two-way travel through complex surface structures as well as the soil). The quasi-static field solutions employ both the 50Hz leakage current from high voltage cables as well as the earth's electromagnetic field to illuminate the underground infrastructure. The MTU feasibility study showed that these technologies have considerable potential, especially in detecting difficult-to-find pot-ended cables, optical fibre cables, service connections and other shallow, small diameter services. The third essential technology in the multi-sensor device is acoustics, which works best in saturated clays where GPR is traditionally problematic. Acoustic technology can be deployed to locate services that have traditionally been difficult to discern (such as plastic pipes) by feeding a weak acoustic signal into the pipe wall or its contents from a remote location. The combination of these technologies, together with intelligent data fusion that optimises the combined output, in a multi-sensor device is entirely novel and aims to achieve a 100% location success rate without disturbing the ground (heretofore an impossible task and the 'holy grail' internationally).The above technologies are augmented by detailed research into models of signal transmission and attenuation in soils to enable the technologies to be intelligently attuned to different ground conditions, thereby producing a step-change improvement in the results. These findings will be combined with existing shallow surface soil and made ground 3D maps via collaboration with the British Geological Society (BGS) to prove the concept of creating UK-wide geophysical property maps for the different technologies. This would allow the users of the device to make educated choices of the most suitable operating parameters for the specific ground conditions in any location, as well as providing essential parameters for interpretation of the resulting data and removing uncertainties inherent in the locating accuracy of such technologies. Finally, we will also explore knowledge-guided interpretation, using information obtained from integrated utility databases being generated in the DTI(BERR)-funded project VISTA.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.