Informing Decisions for a Resilience Coast - IDRiC
Lead Research Organisation:
Cranfield University
Department Name: School of Water, Energy and Environment
Abstract
The coastline of Norfolk and Suffolk coastline has continually changed since the last ice-age. It is also an extensively studied coast and it is rich in data and information. However until now there has been no focussed effort to understand the range and depth of the data available and nor how to utilise the data to provide the evidence to enable better risk-based decisions to be made on the long-term future for a resilient coast. This exciting opportunity will for the first time give unparalleled access to data bases in a range of risk management authorities. This together with other publicly available data will enable the candidate to undertake new interpretation of information, challenge or support current policies and provide evidence to enable better informed decisions to be taken in future. The non-academic partners to this project do not have preconceived ideas as to the out puts of this work only the recognition that they are currently weak in their understanding of both what actual relevant information is available and when combined and interpreted what new insight about the coast can be gained. This work can potentially have a significant impact on local businesses and communities, so whilst an enquiring mind and technical expertise is essential the candidate will need to be proactive in communicating ideas and findings. They will also need to recognise that this is not just an academic exercise part of the success of the project will be measured on what legacy there is, can the risk management authorities continue to utilise the new techniques once the studentship has been completed. Access will be available to the technical experts along the coast, those who have insights into other issues, policy makers and senior management. In addition if real benefits of this work are identified and can be transferable to other local authorities and coastal risk managers then this work will be actively promoted through other local authorities, Environment Agency, etc.
Organisations
People |
ORCID iD |
| Simon Jude (Primary Supervisor) | |
| Alexander Rumson (Student) |
Publications
Rumson A
(2017)
Coastal risk adaptation: the potential role of accessible geospatial Big Data
in Marine Policy
Rumson A
(2018)
Opening up the coast
in Ocean & Coastal Management
Rumson AG
(2019)
Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk.
in The Science of the total environment
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| NE/M009009/1 | 05/10/2015 | 31/12/2022 | |||
| 1654515 | Studentship | NE/M009009/1 | 05/10/2015 | 04/10/2018 | Alexander Rumson |
| Description | Findings in relation to the 5 key objectives: Objective 1: Identify and analyse challenges and knowledge gaps in relation to data-driven approaches to coastal risk evaluation. Through an evaluation of the benefits modern Big Data techniques offer to coastal management, the need was identified to include high resolution data in wide-scale coastal risk analyses. Big Data was revealed to enables Decision Support Systems to access and analyse multiple data themes relevant to coastal management. This can provide possibilities for realisation of patterns/interactions in environmental and societal factors. In line with this geospatial Big Data analysis was revealed to hold the potential to transform of coastal planning. Objective 2: Evaluate how Open Source data can be utilised within holistic coastal risk evaluations. We revealed how the application of Open Source data within coastal management permits 'triple bottom line' holistic risk evaluations in coastal regions. A conceptual framework was developed for coastal risk evaluations using Open Data. An East Anglian case study reveals insight creation through combing data sources. Freely available data now exists which is shown to address the main themes of coastal management. Combing such data through the proposed framework, provides opportunities for evidence-based coastal policy creation, reducing subjectivity within decision making processes. Objective 3: Evaluate the application of point cloud based geomorphological change detection to analyse coastal trends, in doing so generate fresh insight on the nature of recent morphological impacts across the region of East Anglia. An evaluation of Geomorphological change detection methods highlights how differing data types and methodologies are available which are suited to varying kinds of coastal change detection applications, depending on context. A methodological approach was developed drawing on high spatial/temporal resolution point cloud data to accurately reveal and quantify coastal change, at a regional scale, over multiple epochs. A Triangulated Irregular Network, TIN-based differencing method, was utilised to obtain spatio-temporal patterns through analysis of Open Source coastal point cloud data. This method generated volumetric change estimates, permitting wide-scale change modelling. Irregular patterns of change were found across the case study region. Prominent hazard events, such as the 2013 East Coast Storm Surge, were shown to result in higher levels of erosion in some but not all of the 14 case study sites focussed on. The results generated could form a valuable input to future analysis of coastal processes, through which it may be possible to reveal causation of changes. Objective 4: Investigate the potential for innovations in the use of data to be utilised within coastal flood risk evaluations for the insurance industry, allowing insurance to act as a soft adaptation mechanism, distributing and communicating risk. Research focusing on the potential role of insurance as a method of soft adaptation to coastal hazards, revealed that data-driven insurance is capable of redistributing and mitigating coastal flood risk. This function of insurance was deemed dependent on risk-based policy pricing, founded on accurate information. Through a series of interviews conducted with insurance industry practitioners, within the London insurance market, scope was exposed for adoption of emerging data technologies. Data innovations were shown to hold the potential to allow insurance to operate an evidence-based risk advisory service. Of the various data sources evaluated, Satellite-derived data emerged as a key source which holds untapped potential to enhance insurance risk analyses. Additionally, Big Data technologies are revealed capable of allowing the fusion of vast empirical datasets with claims data to generate insight. There were many challenges exposed throughout the research, these relate to requirements for structured data capture, data availability, an overreliance on expert opinion, and access to insurance industry datasets. Nevertheless, solutions are advanced which address these issues. Implementation and adoption of the data innovations outlined within this research could work to improve risk rating, and risk awareness, which could discourage developments in high risk areas, and incentivise sustainable practices, leading to flood resilient outcomes on the coast. Objective 5: Explore how coastal practitioners can incorporate important missing aspects of coastal resilience in their decision-making process at a regional scale, through a data-driven approach. Through analysis of past coastal resilience assessments, a resilience assessment framework based on an extensive listing of metrics was created. This involved a staged resilience assessment methodology based on the use of risk and resilience variables contained within 254 metrics. It was found possible to base 75% of the proposed assessment metrics on empirical evidence derived through utilisation of emerging data sources and analytical methods. As a result, the proposed approach is less reliant on value-based judgements, so could increase objectivity in coastal planning processes. The research demonstrates how the proposed methodology could be utilised to address the requirements, supplied by a coastal management authority, for the case study area focussed on. The approach is revealed capable of enhancing sustainable coastal decision-making through basing coastal resilience assessments on empirical evidence. |
| Exploitation Route | The outputs generated through my research are being utilised by coastal authorities in England to improve the way that data is utilised within coastal management decision making practices. The Environment Agency have been provided with outputs and coastal authorities including the partner organisation. Outputs relating to work completed with the insurance industry have been provided to Lloyd's. This is also being drawn on by Coastal Partnership East within specific projects focusing on insurance and coastal resilience. |
| Sectors | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Environment,Government, Democracy and Justice |
| URL | https://www.intel.co.uk/content/www/uk/en/it-management/cloud-analytic-hub/it-leads-the-way.html |
| Description | Through engaging with industry and practitioner communities my work has been used within current policy evaluations and coastal management planning. This has been instigated by the industrial partner, Coastal Partnership East. For example my work has been drawn on within the current Shoreline Management Plan refresh being conducted by the Environment Agency and by the Environment Agency's Geomatics department, in relation to use of the point cloud data they are collecting to model geomorphological change in coastal areas. I have utilised a software project, which I was granted an academic license for, in a novel way, as such this has provided benefits to the user community, and in addition to publication of this work within an academic journal, the company Teledyne Caris are supporting the work's publication within a Trade Journal. Outputs from my work have been provided to the Lloyd's insurance market, and have also been provided to companies such as startup technology companies such as Sensonomic and Tcarta. |
| Sector | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Environment |
| Impact Types | Societal,Economic,Policy & public services |