Cranfield University


CranfieldUniversityLogoCranfield University’s capability in risk analytics, mitigation and Big Data is invested within its new School for Energy, Environment and Agrifood. The Institute for Environment, Heath, Risks and Futures (IEHRF) [Pollard] hosts the pan-government Environmental Risks and Futures Partnership providing futures and horizon scanning for Defra, Scottish and Welsh Governments, DECC, DfT, NE, FC, EA, SEPA, MMO, FSA and NERC. IEHRF has revised the Government’s ‘Guidelines for Environmental Risk Assessment and Management[1], underpinning the reporting power of the Climate Change Act, 2008, analysing climate change risk assessments of 100 key infrastructure operators, public bodies and regulators. IEHRF [Weeks; Jude; Pollard], in collaboration with CU’s Complex Systems Research Centre [Varga] is developing risk modelling tools as part of a £3.4m EPSRC/ESRC-funded International Centre for Infrastructure Futures [EP/K012347/1]. Further contributions include network analysis for exotic disease incursions[2] and EPSRC-funded research [EP/E017975/1] applying agent-based simulation to complex brokering of evidence in regulatory decision-making[3],[4]. The NERC RESPONSE project [NE/J016330/1] [Jude; Pollard] and the NERC Marine Renewable Energy Knowledge Exchange Programme (MREKEP) are exploring risk and uncertainty in the marine sector [Gill, Jude, Prpich] highlighting the challenges of risk based decision-making with emerging forms of infrastructure. A NERC/CEFAS CASE studentship investigated complex forms of cumulative risk in the marine environment [Gill, Jude]. Recent research includes remote measuring Afghan illicit opium production[5] [Waine], national drought assessments on vegetation in semi-arid climates, and recently won BBSRC/TSB work to develop ‘agri-informatic’ tools to reduce crop wastage and field losses [Simmons; Hallett; Corstanje].

CU operate the Defra ‘Land Information System’ (LandIS)[6], whose national datasets underpin risk assessment and decision support[7] [Hallett; Farewell]. BGS [Lawley] and CU have complementary national and international geohazard assessments, assessing ground movement, instability, and ground earthing potential[8]. The NERC-sponsored Soil Observatory [NEC04981] draws together substantive national and international ‘Big Data’ from a range of DREAM partners [CU, BGS, CEH, James Hutton, and Defra], utilising distributed data models providing ‘just in time’ mapping of environmental phenomena using ‘Web Feature Services’ (WFS)[9]. A key UKSO strength is its combination and juxtaposition of legacy environmental observations with contemporary ‘Volunteered Geographic Information’ (VGI), the basis for representing environmental change[10].

CU has extensive expertise in data visualisation, applying virtual reality (VR) in choice experiments (i) to value landscape and coastal change[11], overcoming limitations associated with traditional textual approaches[12]; and (ii) with civil engineers communicating cliff erosion models; the latter emphasising end-user demands for communicating risk and uncertainty information[13]. CU collaborated with EPSRC [EP/G022682/1], co-funded by Defra, ESRC and NERC, to develop novel visualisation techniques to facilitate strategic risk appraisal of difficult-to-compare risks[14]. Recent NERC investment [NE/L012774/1; Hallett; Corstanje; Jude] includes a VR suite and 3D projection system allowing handling of large quantities of complex spatio-temporal data, facilitating decision-making and perception research, particularly in relation to scenario-driven environmental futures involving novel and emergent risks. DREAM partners are pioneering crowd-sourced informatics, producing mobile apps for environmental monitoring, exploiting mobile technology for ground-based environmental sensing, e.g. JHI’s apps for monitoring soil characteristics in Scotland[15] and BGS’ delivery and crowd-sourced collection of geological and soil-related data via the iGeology and mySoil apps[16]. This includes rolling-out technologies for citizen science based environmental monitoring, through development, trialling and evaluation of devices and crowd sourcing (e.g. air pollutant deposition in terrestrial environments across the UK (UKEAP). CU have developed European-level data specifications for soil, used to develop next-generation Internet-based implementation of the ‘Soils and Terrain’ (Soter) data model in the form of ‘SoTerML’[17].

[1] Defra (2011) Guidelines for Environmental Risk Assessment: Green Leaves III. Defra, 84pp. Authors, Gormley, Á., Pollard, S. and Rocks, S.

[2] Delgado, J., Pollard, S., Snary, E., Black, E., Prpich, G. and Longhurst, P. (2013) A systems approach to the policy-level risk assessment of exotic animal diseases: network model and application to classical swine fever, Risk Analysis 33: 1454–72.

[3] Davies, G., Kendall, G., Soane, E., Charnley, F. and Pollard, S. (2010) Regulators as “agents”: power and personality in risk regulation and a role for agent‐based simulation. J. Risk Research, 13(8): 961–982.

[4] Davies, G., Kendall, G., Soane, E., Li, J., Rocks, S., Jude, S. and Pollard, S. (2014) Regulators as agents: modelling personality and power as evidence is brokered to support decisions on environmental risk. Sci. Tot Env. 466-467: 74–83.

[5] Taylor, J., Waine, T., Juniper, G.., Simms, D., and Brewer, T. (2010). Survey and monitoring of opium poppy and wheat in Afghanistan: 2003-2009. Remote Sens. Lett. 1: 179-185.

[6] Keay, C., Hallett, S., Farewell, T., Rayner, A. and Jones, R. (2009) Moving the National Soil Database for England and Wales (LandIS) towards INSPIRE Compliance, Int. J. Spatial Data Infrastructures Res., vol4, pp134-155.

[7] Pritchard, O., Hallett, S., and Farewell, T. (2014) Soil impacts on UK infrastructure: Current and future climate. Engineering Sustainability, ICE. Doi esu1300035.3d (in press).

[8] Busby, J., Entwisle, D., Hobbs, P., Jackson, P., Johnson, N., Lawley, R., Linley, K., Mayr, T., Palmer, R., Raines, M., Reeves, H., Tucker, S., and Zawadzka, J. (2012) A GIS for the planning of electrical earthing. Quar. J. Eng. Geol. Hydrog. 45: 379-390

[9] Lawley, R., Emmett, B. and Robinson, D. (2014) Soil observatory lets researchers dig deep. Nature, 509, p427.

[10] Shelley, W., Lawley, R., and Robinson, D. (2013) Crowd-sourced soil data for Europe. Nature, 496 (7445). 300.

[11] Jude, S. (2008) Investigating the Potential Role of Visualization Techniques in Participatory Coastal Management. Coastal Management. 36: 331–349.

[12] Bateman, I., Day, B., Jones, A. and Jude, S. (2009) Reducing gain–loss asymmetry: A virtual reality choice experiment valuing land use change. J. Environ. Econ. Mgt. 58: 106–118.

[13] Brown, I., Jude, S., Koukoulas, S., Nicholls, R., Dickson, M. and Walkden, M. (2006) Dynamic simulation and visualisation of coastal erosion. Comp., Environ. Urban Syst. 30: 840–860.

[14] Prpich, G., Dagonneau, J., Rocks, S., Lickorish, F. and Pollard, S. (2013) Strategic analysis of environmental policy risk-heat maps, risk futures and the character of environmental harm. Sci. Total Environ. 463-464: 442-445.

[15] Aitkenhead, M.J., Coull, M.C., Donnelly, D., Hastings, E.J. (2014) Innovations in environmental monitoring using mobile technology – a review., Int. J. Interactive Mobile Technologies, 8: 50-58.

[16] Shelley, W., Lawley, R., and Robinson, D. (2013) Crowd-sourced soil data for Europe. Nature, 496: 7445, p300.

[17] Pourabdollah, A., Leibovici, D., Simms, D., Tempel, P., Hallett, S. and Jackson, M. (2012) Towards a standard for soil and terrain data exchange: SoTerML (2012) Computers and Geosciences, 45, pp270-283.