Browsing by Author "Hallett, Stephen H."
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Item Open Access Analysis of cold weather patterns over the period 1991-2012(2013-01-22T00:00:00Z) Farewell, Timothy S.; Hallett, Stephen H.; Truckell, Ian G.Within the context of an observed increase in the numbers of burst pipes associated with colder winters in the Anglian water region, we have analysed temperature data for England and Wales from the period 1991-2012 to identify cold winter periods. To do so, we have calculated the annual accumulated temperature below 1 °C for each MORECS square over the winter period. The resulting data has been mapped for both the whole of England and Wales as well as just for the Anglian Water region. The data shows that the four winters between 2008-2012 were considerably colder than the preceding eleven winters. Additionally, for the winter of 2011-2012, the average temperature for all England of Wales was warmer than the 1991-2011 period average. However locally, in the Anglian Water region, the average temperatures were colder than the 1991-2011 average. The available MORECS data shows that while there are some periods of time with warmer winters (e.g. 1997-2008) and periods with colder winters (1990-1994, 1995-1997 and 2008- 2012), the lengths of these periods are considerably variable. From the MORECS data for the period 1991-2012, there does not appear to be a cyclical or predictable pattern in determining the harshness of the winter period.Item Open Access The application of data innovations to geomorphological impact analyses in coastal areas: An East Anglia, UK, case study(Elsevier, 2019-07-20) Rumson, Alexander G.; Hallett, Stephen H.; Brewer, Timothy R.Rapidly advancing surveying technologies, capable of generating high resolution bathymetric and topographic data, allow precise measurements of geomorphological change and deformation. This permits great accuracy in the characterisation of volumetric change, sediment and debris flows, accumulations and erosion rates. However, such data can be utilised inadequately by coastal practitioners in their assessments of coastal change, due to a lack of awareness of the appropriate analytical techniques and the potential benefits offered by such data-driven approaches. This was found to be the case for the region of East Anglia, UK, which was analysed in this study. This paper evaluates the application of innovative geomorphological change detection (GCD) techniques for analysis of coastal change. The first half of the paper contains an extensive review of GCD methods and data sources used in previous studies. This leads to the selection and recommendation of an appropriate methodology for calculation of volumetric GCD, which has been subsequently applied and evaluated for 14 case study sites in East Anglia. This has involved combining open source point cloud datasets for broad spatial scales, covering an extended temporal period. The results comprise quantitative estimates of volumetric change for selected locations. This allows estimation of the sediment budgets for each stretch of coastline focused upon, revealing fluctuations in their rates of change. These quantitative results were combined with qualitative outputs, such as visual representations of change and we reveal how combining such methods assists identification of patterns and impacts linked to specific events. The study demonstrates how high-resolution point cloud data, which is now readily available, can be used to better inform coastal management practices, revealing trends, impacts and vulnerability in dynamic coastal regions. The results also indicate heterogeneous impacts of events, such as the 2013 East Coast Storm Surge, across the study area of East Anglia.Item Open Access The challenges of implementing evidence-based strategies to inform building and urban design decisions: a view from current practice(Emerald, 2022-08-15) Stanitsa, Avgousta; Hallett, Stephen H.; Jude, SimonPurpose This study aims to raise awareness of the key challenges, opportunities and priorities for evidence-based strategies’ application to inform building and urban design decisions. Design/methodology/approach This study uses deductive qualitative content and manifest analysis, using semi-structured interviews undertaken with building and urban design professionals who represent a UK-based organisation. Findings The challenges associated with the practical implementation of frameworks, potential application areas and perceived areas of concern have been identified. These not only include the need to practically test their use, but also to identify the most appropriate forums for their use. Participant responses indicate the need to further develop engagement strategies for their practical implementation, clearly communicating the benefits and efficiencies to all stakeholders. Research limitations/implications Implications/ limitations of this study come with the fact that some of the respondents may possess inadequate professional experience in properly evaluating all the questions. Additionally, the information gathered is restricted to the UK geographical context, as well as coming from one organisation, because of data accessibility. Practical implications The findings of the study can be adopted by designers in the strategic definition level to overcome the key challenges associated with the use of evidence-based strategies, enhancing their decision-making processes. Originality/value As a theoretical contribution to knowledge, this study enhances the body of knowledge by identifying the challenges associated with the practical implementation of evidence-based strategies to inform building and urban design decisions. In practice, the findings aid urban planners, designers and academics in embedding and adopting strategies that enhance decision-making processes.Item Open Access The challenges of predicting pipe failures in clean water networks: a view from current practice(IWA, 2021-08-09) Barton, Neal A.; Hallett, Stephen H.; Jude, SimonPipe failure models can aid proactive management decisions and help target pipes in need of preventative repair or replacement. Yet, there are several uncertainties and challenges that arise when developing models, resulting in discord between failure predictions and those observed in the field. This paper aims to raise awareness of the main challenges, uncertainties, and potential advances discussed in key themes, supported by a series of semi-structured interviews undertaken with water professionals. The main discussion topics include data management, data limitations, pre-processing difficulties, model scalability and future opportunities and challenges. Improving data quality and quantity is key in improving pipe failure models. Technological advances in the collection of continuous real-time data from ubiquitous smart networks offer opportunities to improve data collection, whilst machine learning and data analytics methods offer a chance to improve future predictions. In some instances, technological approaches may provide better solutions to tackling short term proactive management. Yet, there remains an opportunity for pipe failure models to provide valuable insights for long-term rehabilitation and replacement planning.Item Open Access Coastal risk adaptation: the potential role of accessible geospatial Big Data(Elsevier, 2017-06-03) Rumson, Alexander G.; Hallett, Stephen H.; Brewer, Timothy R.Increasing numbers of people are living in and using coastal areas. Combined with the presence of pervasive coastal threats, such as flooding and erosion, this is having widespread impacts on coastal populations, infrastructure and ecosystems. For the right adaptive strategies to be adopted, and planning decisions to be made, rigorous evaluation of the available options is required. This evaluation hinges on the availability and use of suitable datasets. For knowledge to be derived from coastal datasets, such data needs to be combined and analysed in an effective manner. This paper reviews a wide range of literature relating to data-driven approaches to coastal risk evaluation, revealing how limitations have been imposed on many of these methods, due to restrictions in computing power and access to data. The rapidly emerging field of ‘Big Data’ can help overcome many of these hurdles. ‘Big Data’ involves powerful computer infrastructures, enabling storage, processing and real-time analysis of large volumes and varieties of data, in a fast and reliable manner. Through consideration of examples of how ‘Big Data’ technologies are being applied to fields related to coastal risk, it becomes apparent that geospatial Big Data solutions hold clear potential to improve the process of risk based decision making on the coast. ‘Big Data’ does not provide a stand-alone solution to the issues and gaps outlined in this paper, yet these technological methods hold the potential to optimise data-driven approaches, enabling robust risk profiles to be generated for coastal regions.Item Open Access Contextualising household water consumption patterns in England: a socio-economic and socio-demographic narrative(Elsevier, 2023-02-02) Abu-Bakar, Halidu; Williams, Leon; Hallett, Stephen H.Water utilities strive to achieve a sustainable reduction in per capita consumption (PCC) by optimising their peak demand management strategies. Socioeconomic (SE) and socio-demographic (SD) characteristics have been proven to correlate with PCC. However, the full extent to which these characteristics underpin peak demand and PCC is yet to be fully understood. Previous work used medium resolution smart meter data from 10,000 households to discover and characterise temporal consumption patterns that underpin peak demand, identifying four distinct clusters of households, namely "Evening Peak" (EP), Late Morning Peak (LM), Early Morning Peak (EM) and Multiple Peak (MP). Using survey results, "Acorn household classification", household occupancy and UK population and household attribute data, this study attempts to draw a correlation between the four clusters and known variables of the participating households. Results have revealed a strong correlation between many endogenous attributes (particularly housing, occupancy, age, number of children and household income) and households' consumption patterns underpinning peak demand. Some 56% of families in privately rented housing show EP characteristics compared with 22% owner-occupiers and 9% social renters. EP households with teenage boys have 37% higher per household consumption (PHC) than average, while EM families with teenage girls use 47% more water in early morning showers than average.Item Open Access A critical review of decision support systems for brownfield redevelopment(Elsevier, 2021-04-16) Hammond, Ellis B.; Coulon, Frederic; Hallett, Stephen H.; Thomas, Russell; Hardy, Drew; Kingdon, Andrew; Beriro, Darren J.Over the past two decades, many decision support systems (DSSs) have been developed to support decision makers and facilitate the planning and redevelopment process of brownfields. Existing systems are however often siloed in their approach and do not fully capture the complexity of brownfield sites from a sustainable development point of view. This critical review provides an insight into the development and implementation of DSSs, published and emerging, together with assessment of their strengths, limitations and opportunities for future integration. Brownfields DSS applications include: remediation technology selection; and land use planning; and risk assessment. The results of this review lead the authors to identify four opportunities to improve brownfield DSSs: (i) increased use of qualitative socioeconomic criteria, particularly costs and economic variables, (ii) decision-support during the early stages of brownfield redevelopment, (iii) the integration of predictive modelling methods, and (iv) improvements of user interfaces and modern web-based functionalities.Item Open Access The development and application of spatial information systems for environmental science(Cranfield University, 1998-04) Hallett, Stephen H.; Bullock, P; Godwin, R. J.This thesis shows how advances in IT allow the development of Environmental Information System (EIS) applications contributing to the advancement of environmental science and management. The research presented elucidates and evaluates the applications for EIS within the environmental and natural resource sciences with specific reference to soils. In supporting environmental suitability and risk assessment, the following research objectives were met: 1. Derive and construct new datasets, facilitating the development of EIS applications 2. Using these and other datasets, develop and demonstrate the validity of specific spatial EIS applications within the context of sustainable soil resource management 3. Evaluate, develop and apply emergent technological principles such as the objectoriented paradigm to the development of such EIS applications The research shows that the EIS approach offers environmental researchers and practitioners powerful tools to facilitate the collection and preparation, representation, structure and management, manipulation and presentation of environmental data. Such data can be used to aid disciplinary and interdisciplinary scientific research, such as risk modelling, data quality control and longitudinal studies. Through the interaction of multi-disciplinary datasets and models, the EIS contributes to the development of a holistic, interdisciplinary understanding of pertinent and contemporary environmental issues. EIS applications are constrained by the availability and affordability of technology, as well as by the quality of the data, models and scientific research they are based upon. With the constantly improving capabilities and cost-performance of IT there should be a continual review of methodologies to maximise usage of available technology. A well-developed synergy between environmental science and IT is important and automatic adoption of the most recently emergent information technologies is not always to be recommended for EIS development. The choice of software tools utilised in EIS development must be based upon the requirements for integration with existing systems, reliability, adherence to industry standards, expenditure, staff training needs, experimentation and efficiency. The incorporation of a spatial element within the decision-making process extends a powerful visual dimension to the traditional approaches used to portray environmental systems. The research identifies the emergent 'object paradigm' as significant for EIS development, being effective for describing complex spatial environmental phenomena. An object-oriented approach facilitates the presentation of abstracted, packaged scientific information in a directly accessible form. The EIS offers a powerful strategic tool for supporting decision-making in environmental management. The EIS applications presented supported Soil Quality and Protection, Pollution Control and Impact Assessment, Water Resource and Catchment Management, Soil and Land Management and Environmental Risk Assessment.Item Open Access The development of a novel decision support system for regional land use planning for brownfield land(Elsevier, 2023-11-11) Hammond, Ellis B.; Coulon, Frederic; Hallett, Stephen H.; Thomas, Russell; Dick, Alistair; Hardy, Drew; Dickens, Mark; Washbourn, Emma; Beriro, Darren J.Digital tools, particularly specialised decision support systems (DSSs), can be utilized to assist in the complex process of brownfield redevelopment. Existing brownfield DSSs typically focus on site-specific, late-stage applications, and socioeconomic factors are often overlooked. In this paper, we present a novel DSS aimed at providing support for early-stage, city region-scale brownfield land use planning and redevelopment. The proposed DSS is a prototype WebGIS application that enables land use planners and other brownfield regeneration professionals to examine a region and a set of sites during the initial planning phase for brownfield redevelopment. The DSS includes three bespoke modules comprising: (1) Land Use Potential (residential, commercial, and public open space), (2) risks posed by contamination and geotechnical hazards, (3) data pertinent to brownfield economic viability assessments. We outline a use case for this DSS, developed through comprehensive user-requirements gathering, and subsequently describe the techniques employed to construct the DSS modules and user interface. Finally, we present the results of user testing, wherein case-study stakeholders assessed the DSS. The feedback obtained during user testing aided in the identification of areas for improvement with regard to the functionality, usability, and effectiveness of the DSS in supporting decision-makers. The feedback was utilized to implement iterative improvements to the DSS and to plan future developments for the prototype DSS.Item Open Access Developments in land information systems: examples demonstrating land resource management capabilities and options(Wiley, 2017-10-17) Hallett, Stephen H.; Sakrabani, Ruben; Keay, Caroline; Hannam, Jacqueline A.Land Information Systems (LIS) provide a foundation for supporting decision-making across a broad spectrum of natural resource applications: agronomic, environmental, engineering and public good. Typically, LIS constitute a computerized database repository holding geospatial components, ‘mapping unit’ geometry and related georeferenced materials such as satellite imagery, meteorological observations and predictions and scanned legacy mapping. Coupled with the geospatial data are associated property, semantic and metadata, representing a range of thematic properties and characteristics of the land and environment. This paper provides examples of recent developments of national and regional LIS, presenting applications for land resource capabilities and management. These focus on the ‘Land Information System’ (LandIS) for England and Wales, and the ‘World Soil Survey Archive and Catalogue’ (WOSSAC) and consider Agricultural Land Classification in Wales, an Irish land and soil information system, and a scheme to optimize land suitability for application of palm oil biofertilizers in Malaysia. Land Information Systems support purposeful environmental interpretations, drawing on soil and related thematic data, offering insight into land properties, capabilities and characteristics. The examples highlight the practical transferability and extensibility of technical and methodological approaches across geographical contexts. This assessment identifies the value of legacy-based natural resource inventories that can be interoperated with other contemporary sources of information, such as satellite imagery.Item Open Access Digital tools for brownfield redevelopment: Stakeholder perspectives and opportunities(Elsevier, 2022-10-19) Hammond, Ellis B.; Coulon, Frederic; Hallett, Stephen H.; Thomas, Russell; Hardy, Drew; Beriro, Darren J.Brownfield redevelopment is a complex process often involving a wide range of stakeholders holding differing priorities and opinions. The use of digital systems and products for decision making, modelling, and supporting discussion has been recognised throughout literature and industry. The inclusion of stakeholder preferences is an important consideration in the design and development of impactful digital tools and decision support systems. In this study, we present findings from stakeholder consultation with professionals from the UK brownfield sector with the aim of informing the design of future digital tools and systems. Our research investigates two broad themes; digitalisation and the use of digital tools across the sector; and perceptions of key brownfield challenge areas where digital tools could help better inform decision-makers. The methodology employed for this study comprises the collection of data and information using a combination of interviews and an online questionnaire. The results from these methods were evaluated both qualitatively and quantitatively. Findings reveal a disparity in levels of digital capability between stakeholder groups including between technical stakeholder types, and that cross-discipline communication of important issues may be aided by the development of carefully designed digital tools. To this end, we present seven core principles to guide the design and implementation of future digital tools for the brownfield sector. These principles are that future digital tools should be: (1) Stakeholder driven, (2) Problem centred, (3) Visual, (4) Intuitive, (5) Interactive, (6) Interoperable, and (7) Geospatial data driven.Item Open Access The East African contribution to the formalisation of the soil catena concept(Elsevier, 2019-11-26) Borden, R. Wayne; Baillie, Ian C.; Hallett, Stephen H.The concept of the soil catena was first explicitly formalised by Geoffrey Milne and his colleagues in East Africa in the 1930s. It has been widely adopted and applied in soil survey and continues to be of great value in soil and other field sciences The concept characterises widespread patterns in which distinctive associations of soils and vegetation are consistently located in specific slope positions. The formalisation of the concept in an area well outside the mainstream of soil research appears to have been due to the combination of highly visible recurrent patterns of red slope soils overlooking dark valley clays in East Africa’s extensive savannahs, together with a group of receptive and collaborative soil scientists working in a supportive institutional environment. The concept is often attributed to Geoffrey Milne, the group’s coordinator, but we show that several colleagues and friends also contributed. We summarise some of the early soil catenas characterised by Milne and his colleagues in Uganda, Kenya and Tanganyika Territory (now Tanzania). Even at the beginning, it was appreciated that the catena was not universally applicable and that heterogeneity of parent materials can override catenary patterns. The catena was quickly and widely adopted in soil science, and this diffusion has led to some broadening of the definition, and several types of soil pattern are now designated as catenas. The concept has also spread beyond soil science and is used by ecologists, geomorphologists and hydrologists amongst others. It continues to be a paradigm of great explicative and educational power in soil science and ecology.Item Open Access An empirical water consumer segmentation and the characterisation of consumption patterns underpinning demand peaks(Elsevier, 2021-07-18) Abu-Bakar, Halidu; Williams, Leon; Hallett, Stephen H.Characterising individual households’ consumption patterns reliably and ascertaining the extent to which these patterns change and how they underpin aggregate demand continues to present a challenge. This paper presents an empirical characterisation of household water consumption patterns, based on consumer segmentation, to improve the accuracy of demand forecasting and to develop both proactive and responsive water conservation strategies. Medium resolution smart metre data for 2019 for 10,000 households were analysed using Machine Learning (ML), revealing four household clusters whose significant differences are underpinned by a variety of indicators in their temporal consumption patterns. The clusters, labelled according to the predominant peak demand times of constituent households, are ‘Evening Peaks’ (EP), ‘Late Morning’ (LM), ‘Early Morning’ (EM) and ‘Multiple Peaks’ (EP). Some of the significant findings include the fact that on average households in EM only record one peak event in 24 h, compared with the MP clusters’ four peak events, with 2 in every 5 households in MP having a confirmed internal leak compared with 1 in every 5 for the other three clusters. A total of 31,788 Cubic metres (m3) was consumed, constituting a monthly mean of 2,649m3, equating to a per household consumption (PHC) of ~270 litres per household per day (l/h/d). Results also revealed the clusters’ distributed dominance of hourly demand and the most active clusters in different seasons. The paper concludes that identifying the significant differences characterising consumption patterns and their concomitant impact on network demand will not only serve to enhance demand forecasting and the prediction of geographical consumption hotspots but will also allow the delivery of targeted intervention measures according to households’ shared characteristics.Item Open Access Enhanced visualization of the flat landscape of the Cambridgeshire Fenlands(Wiley, 2015-09-15) Pritchard, Oliver G.; Farewell, Timothy S.; Hallett, Stephen H.The Fenlands of East Anglia, England, represent a subtle landscape, where topographic highs rarely exceed 30 m above sea level. However, the fens represent an almost full sequence of Quaternary deposits which, together with islands of Cretaceous and Jurassic outcrops, make the area of geological importance. This feature discusses the advantages of using 3D visualization coupled with high-resolution topographical data, over traditional 2D techniques, when undertaking an analysis of the landscape. Conclusions suggest that the use of 3D visualization will result in a higher level of engagement, particularly when communicating geological information to a wider public.Item Open Access Forward-looking climatic scenarios of UK clay-related subsidence risk(Cranfield University, 2015-06-01) Hallett, Stephen H.; Farewell, Timothy; Pritchard, Oliver G.An award drawing upon the Cranfield University EPSRC-funded Impact Acceleration Account (IAA) was awarded to staff in the University’s School of Energy, Environment and Agrifood (SEEA) (Hallett, Farewell, Pritchard), to undertake processing of UKCP09 climate projections for the United Kingdom (UK) in support of assessments of future geohazards and societal impact. This report identifies the technical outcomes from this work and presents the resultant climate change cartography and related data. Spatially coherent national data ensembles are generated for the UKCP09 ‘Baseline’ period, for ‘2030’ and ‘2050’. Maps of Potential Soil Moisture Deficit (PSMD) are produced for each to exemplify its application. The findings suggest that the extremes in PSMD observed at the current time in the UK are likely to become the norm by 2030 and 2050. The data produced has a range of potential applications, from geohazard assessments to the built environment and infrastructure, to agri-informatic modelling of agricultural crops, as well as modelling for 'future-proofing' of buildings against predicted climate change by example. It is anticipated that the datasets presented from this IAA will be of benefit to a range of end-user stakeholders. One example is in the insurance, reinsurance and water utility sectors, where modelling of future impacts of climate change are conducted. Recent research has suggested this data will likely prove of use for County Councils and municipal authorities, for example in the allocation of targeted road maintenance funding, particularly on local-authority owned highways. Rail network operators, having faced a number of embankment failures, and track undulations as a result of shrink/swell activity are also likely to benefit from this research. The soil moisture deficit scenarios produced could help such organisations better manage geotechnical assets and vegetation management of susceptible slopes and soils. Cranfield’s School of Energy, Environment and Agrifood (SEEA) manage and operate the Natural Perils Directory (NPD). The NPD is a widely used geohazard thematic dataset portraying vulnerabilities arising from soil-climate responses to long-term climate change. NPD will incorporate directly the datasets produced and described here.Item Open Access From data to decisions: empowering brownfield redevelopment with a novel decision support system(Elsevier, 2023-10-06) Hammond, Ellis B.; Coulon, Frederic; Hallett, Stephen H.; Thomas, Russell; Dick, Alistair; Hardy, Drew; Dickens, Mark; Washbourn, Emma; Beriro, Darren J.This research evaluates a novel decision support system (DSS) for planning brownfield redevelopment. The DSS is implemented within a web-based geographical information system that contains the spatial data informing three modules comprising land use suitability, economic viability, and ground risk. Using multi-criteria decision analysis, an evaluation was conducted on 31,942 ha of post-industrial land and around Liverpool, UK. The representativeness and credibility of the DSS outputs were evaluated through user trials with fifteen land-use planning and development stakeholders from the Liverpool City Region Combined Authority. The DSS was used to explore land use planning scenarios and it could be used to support decision making. Our research reveals that the DSS has the potential to positively inform the identification of brownfield redevelopment opportunities by offering a reliable, carefully curated, and user-driven digital evidence base. This expedites the traditionally manual process of conducting assessments of land suitability and viability. This research has important implications for assessing the impact of current and future planning policy and the potential for the use of digital tools for land use planning and sustainability in the UK and globally.Item Open Access Generalised network architectures for environmental sensing: case studies for a digitally enabled environment(Elsevier, 2022-04-08) Mead, Mohammed Iqbal; Bevilacqua, M.; Loiseaux, C.; Hallett, Stephen H.; Jude, Simon; Emmanouilidis, Christos; Harris, Jim A.; Leinster, Paul; Mutnuri, S.; Tran, Trung Hieu; Williams, LeonA digitally enabled environment is a setting which incorporates sensors coupled with reporting and analytics tools for understanding, observing or managing that environment. Large scale data collection and analysis are a part of the emerging digitally enabled approach for the characterisation and understanding of our environment. It is recognised as offering an effective methodology for addressing a range of complex and interrelated social, economic and environmental concerns. The development and construction of the approach requires advances in analytics control linked with a clear definition of the issues pertaining to the interaction between elements of these systems. This paper presents an analysis of selected issues in the field of analytics control. It also discusses areas of progress, and areas in need of further investigation as sensing networks evolve. Three case studies are described to illustrate these points. The first is a physical analytics test kit developed as a part of the “Reinvent the Toilet Challenge” (RTTC) for process control in a range of environments. The second case study is the Cranfield Urban Observatory that builds on elements of the RTTC and is designed to allow users to develop user interfaces to monitor, characterise and compare a variety of environmental and infrastructure systems plus behaviours (e.g., water distribution, power grids). The third is the Data and Analytics Facility for National Infrastructure, a cloud-based high-performance computing cluster, developed to receive, store and present such data to advanced analytical and visualisation tools.Item Open Access A history of Soil Survey in England and Wales(2012-04-24T00:00:00Z) Hallett, Stephen H.; Deeks, Lynda K.Soil survey activities in England and Wales date back some 350 years, but systematic survey of our soils began only in the 1950s culminating in the activities of the Soil Survey of England and Wales.Item Open Access Improving pipe failure predictions: Factors effecting pipe failure in drinking water networks(Elsevier, 2019-07-29) Barton, Neal A.; Farewell, Timothy S.; Hallett, Stephen H.; Acland, Timothy F.To reduce leakage and improve service levels, water companies are increasingly using statistical models of pipe failure using infrastructure, weather and environmental data. However, these models are often built by environmental data scientists with limited in-field experience of either fixing pipes or recording data about network failures. As infrastructure data can be inconsistent, incomplete and incorrect, this disconnect between model builders and field operatives can lead to logical errors in how datasets are interpreted and used to create predictive models. An improved understanding of pipe failure can facilitate improved selection of model inputs and the modelling approach. To enable data scientists to build more accurate predictive models of pipe failure, this paper summarises typical factors influencing failure for 5 common groups of materials for water pipes: 1) cast and spun iron, 2) ductile iron, 3) steel, 4) asbestos cement, 5) polyvinyl chloride (PVC) and 6) polyethylene (PE) pipes. With an improved understanding of why and how pipes fail, data scientists can avoid misunderstanding and misusing infrastructure and environmental data, and build more accurate models of infrastructure failure.Item Open Access Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk(Elsevier, 2019-01-14) Rumson, Alexander G.; Hallett, Stephen H.Insurance plays a crucial role in human efforts to adapt to environmental hazards. Effective insurance can serve as both a measure to distribute, and a method to communicate risk. In order for insurance to fulfil these roles successfully, policy pricing and cover choices must be risk-based and founded on accurate information. This is reliant on a robust evidence base forming the foundation of policy choices. This paper focuses on the evidence available to insurers and emergent innovation in the use of data. The main risk considered is coastal flooding, for which the insurance sector offers an option for potential adaptation, capable of increasing resilience. However, inadequate supply and analysis of data have been highlighted as factors preventing insurance from fulfilling this role. Research was undertaken to evaluate how data are currently, and could potentially, be used within risk evaluations for the insurance industry. This comprised of 50 interviews with those working and associated with the London insurance market. The research reveals new opportunities, which could facilitate improvements in risk-reflective pricing of policies. These relate to a new generation of data collection techniques and analytics, such as those associated with satellite-derived data, IoT (Internet of Things) sensors, cloud computing, and Big Data solutions. Such technologies present opportunities to reduce moral hazard through basing predictions and pricing of risk on large empirical datasets. The value of insurers' claims data is also revealed, and is shown to have the potential to refine, calibrate, and validate models and methods. The adoption of such data-driven techniques could enable insurers to re-evaluate risk ratings, and in some instances, extend coverage to locations and developments, previously rated as too high a risk to insure. Conversely, other areas may be revealed more vulnerable, which could generate negative impacts for residents in these regions, such as increased premiums. However, the enhanced risk awareness generated, by new technology, data and data analytics, could positively alter future planning, development and investment decisions.
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