Browsing by Author "Rumson, Alexander G."
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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 Coastal management and adaptation: an integrated data-driven approach(2019-03) Rumson, Alexander G.; Hallett, Stephen; Brewer, Timothy R.Coastal regions are some of the most exposed to environmental hazards, yet the coast is the preferred settlement site for a high percentage of the global population, and most major global cities are located on or near the coast. This research adopts a predominantly anthropocentric approach to the analysis of coastal risk and resilience. This centres on the pervasive hazards of coastal flooding and erosion. Coastal management decision-making practices are shown to be reliant on access to current and accurate information. However, constraints have been imposed on information flows between scientists, policy makers and practitioners, due to a lack of awareness and utilisation of available data sources. This research seeks to tackle this issue in evaluating how innovations in the use of data and analytics can be applied to further the application of science within decision-making processes related to coastal risk adaptation. In achieving this aim a range of research methodologies have been employed and the progression of topics covered mark a shift from themes of risk to resilience. The work focuses on a case study region of East Anglia, UK, benefiting from the input of a partner organisation, responsible for the region’s coasts: Coastal Partnership East. An initial review revealed how data can be utilised effectively within coastal decision-making practices, highlighting scope for application of advanced Big Data techniques to the analysis of coastal datasets. The process of risk evaluation has been examined in detail, and the range of possibilities afforded by open source coastal datasets were revealed. Subsequently, open source coastal terrain and bathymetric, point cloud datasets were identified for 14 sites within the case study area. These were then utilised within a practical application of a geomorphological change detection (GCD) method. This revealed how analysis of high spatial and temporal resolution point cloud data can accurately reveal and quantify physical coastal impacts. Additionally, the research reveals how data innovations can facilitate adaptation through insurance; more specifically how the use of empirical evidence in pricing of coastal flood insurance can result in both communication and distribution of risk. The various strands of knowledge generated throughout this study reveal how an extensive range of data types, sources, and advanced forms of analysis, can together allow coastal resilience assessments to be founded on empirical evidence. This research serves to demonstrate how the application of advanced data-driven analytical processes can reduce levels of uncertainty and subjectivity inherent within current coastal environmental management practices. Adoption of methods presented within this research could further the possibilities for sustainable and resilient management of the incredibly valuable environmental resource which is the coast.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 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.Item Open Access Mapping the deep ocean with multiple AUVs. Ocean Infinity’s Seabed Exploration Project(Gitc. BV., 2018-04-30) Rumson, Alexander G.Ocean Infinity's seabed mapping campaign commenced in the summer of 2017. The Ocean Infinity team is made up of individuals from multiple disciplines, who have gained vast experience with deep-sea exploration operations in the past. Their combined knowledge and insight led to the idea to undertake deep-sea mapping operations using up to eight autonomous underwater vehicles (AUVs), paired with eight unmanned surface vessels (USVs). This novel concept is explained in more detail in this article.Item Open Access Opening up the coast(Elsevier, 2018-04-25) Rumson, Alexander G.; Hallett, Stephen H.Coastal zones attract human settlement, business and industry, and are instrumental to the functioning of societies both in coastal states and the wider global community. However, the oceans and coasts are under growing pressure as human practices change, populations rise and climate change impacts increase. In managing coastal regions, high quality data forms the basis of rational decision-making. Large volumes of ‘triple bottom line’ data exists representing a wide variety of environmental, social, and economic themes in coastal regions. Such data is especially crucial to development of environmental risk evaluations for the coast. The momentum driving the Open Source data movement across the world is accelerating and consequently, huge quantities of data are becoming freely available to the public. This presents a valuable opportunity for coastal managers, policy makers and land planners, who need to evaluate the full implications of their choices. Decision-makers frequently need to draw on many disparate datasets. However, this can be complicated by many factors, including a lack of awareness of the full range of datasets available. This paper seeks to explore this area, taking the UK as an example, to reveal how currently available open data sources relate to coastal management decision-making. Environmental risk management is a cross-cutting theme, relevant to all areas of coastal management. As such, this topic is discussed and addressed within a case study focusing on the vulnerable coastal region of East Anglia. In collation and analysis of coastal data Geographical Information Systems (GIS) can play an important role, in line with this GIS approaches were utilised within the case study. The case study led to development of a conceptual framework which can be applied to future coastal risk assessments, using Open Source data. The UK is currently at the forefront of the Open Source data movement and as such it is used as an example within this paper, however the issues addressed have international relevance, and the UK perspective is used to illustrate wider opportunities, resulting from freely available data sources, extending to management of coastal regions globally.Item Open Access The role of data within Coastal Resilience Assessments: an East Anglia, UK, case Study(Elsevier, 2019-10-07) Rumson, Alexander G.; Payo Garcia, Andres; Hallett, Stephen H.Embracing the concept of resilience within coastal management marks a step change in thinking, building on the inputs of more traditional risk assessments, and further accounting for capacities to respond, recover and implement contingency measures. Nevertheless, many past resilience assessments have been theoretical and have failed to address the requirements of practitioners. Assessment methods can also be subjective, relying on opinion-based judgements, and can lack empirical validation. Scope exists to address these challenges through drawing on rapidly emerging sources of data and smart analytics. This, alongside the careful selection of the metrics used in assessment of resilience, can facilitate more robust assessment methods. This work sets out to establish a set of core metrics, and data sources suitable for inclusion within a data-driven coastal resilience assessment. A case study region of East Anglia, UK, is focused on, and data types and sources associated with a set of proven assessment metrics were identified. Virtually all risk-specific metrics could be satisfied using available or derived data sources. However, a high percentage of the resilience-specific metrics would still require human input. This indicates that assessment of resilience is inherently more subjective than assessment of risk. Yet resilience assessments incorporate both risk and resilience specific variables. As such it was possible to link 75% of our selected metrics to empirical sources. Through taking a case study approach and discussing a set of requirements outlined by a coastal authority, this paper reveals scope for the incorporation of rapidly progressing data collection, dissemination, and analytical methods, within dynamic coastal resilience assessments. This could facilitate more sustainable evidence-based management of coastal regions.