Visualisation techniques to support public interpretation of future climate change and land-use choices: a case study from N-E Scotland

ABSTRACT Mitigating and adapting to climate change includes a requirement to evaluate the role of future land uses in delivering robust integrated responses that are sensitive to local landscape contexts. In practice, this emphasises the need for community engagement, planning and inclusive decision-making. Community engagement may be potentially facilitated by the use of spatially explicit quantitative scenarios of land-use change in combination with interactive visualisation. This requires a coherent framework to integrate spatial data modelling, analytical capabilities and visualisation tools in a format that will also engage diverse public audiences. These challenges were explored with a case study of virtual landscapes from N-E Scotland that was used to test preferences for scenarios of future land use. Visualisations employed texture-based rendering rather than full photo-realistic rendering to facilitate interactivity and this provided additional scope for audiences to explore multiple future scenarios compared to the present landscape. Interactive voting in a virtual landscape theatre suggested preferences for visual diversity, good stewardship and perceived naturalness that should be considered in developing planned responses to change. Further investigation of preferences was conducted using interactive 3D features located within the landscape. Study findings are reviewed against objectives for inclusive engagement in the Digital Earth agenda and used to make further recommendations on the use of scenarios and visualisation tools. In particular, technical advances in user engagement need to be developed in conjunction with emerging good practice that addresses ethical, behavioural and inclusion issues so that the content is presented in as transparent and unbiased format as possible.

[1]  Sophie A. Nicholson-Cole,et al.  Barriers perceived to engaging with climate change among the UK public and their policy implications , 2007 .

[2]  Pete Smith,et al.  A coherent set of future land use change scenarios for Europe , 2006 .

[3]  J. Edmonds,et al.  A new scenario framework for climate change research: background, process, and future directions , 2013, Climatic Change.

[4]  G. Fry,et al.  The ecology of visual landscapes: Exploring the conceptual common ground of visual and ecological landscape indicators , 2009 .

[5]  R. Nicholls,et al.  A Regional, Multi-Sectoral And Integrated Assessment Of The Impacts Of Climate And Socio-Economic Change In The Uk , 2005 .

[6]  Steve Cinderby,et al.  How to reach the ‘hard-to-reach’: the development of Participatory Geographic Information Systems (P-GIS) for inclusive urban design in UK cities , 2010 .

[7]  Alan Richardson,et al.  Use of a Three-Dimensional Virtual Environment to Teach Drug-Receptor Interactions , 2013, American Journal of Pharmaceutical Education.

[8]  Ahindra Ghosh,et al.  Ecosystems and Human Well-Being , 2013 .

[9]  A. McMichael,et al.  Ecosystems and Human well-being , 2003 .

[10]  S. Sheppard.  Landscape visualisation and climate change: the potential for influencing perceptions and behaviour , 2005 .

[11]  G. Tress,et al.  Scenario visualisation for participatory landscape planning—a study from Denmark , 2003 .

[12]  Stuart Watt,et al.  Virtual Reality for Mutual Understanding in Landscape Planning , 2007 .

[13]  Ton C M de Nijs,et al.  Constructing land-use maps of the Netherlands in 2030. , 2004, Journal of environmental management.

[14]  E. Wilson,et al.  The biophilia hypothesis , 1993 .

[15]  I. Brown,et al.  Scenario analysis for regional decision-making on sustainable multifunctional land uses , 2014, Regional Environmental Change.

[16]  Michael F. Goodchild,et al.  The use cases of digital earth , 2008, Int. J. Digit. Earth.

[17]  Simon Buckingham Shum,et al.  The Roots of Computer Supported Argument Visualization , 2003, Visualizing Argumentation.

[18]  Huadong Guo,et al.  Next-generation Digital Earth , 2012, Proceedings of the National Academy of Sciences.

[19]  Jürgen Döllner,et al.  Abstract representations for interactive visualization of virtual 3D city models , 2009, Comput. Environ. Urban Syst..

[20]  J. Falk,et al.  Evolutionary Influence on Human Landscape Preference , 2010 .

[21]  L. Poggio,et al.  Exploring path-dependencies and spatial variability in landscape scale scenarios for ecosystem services assessments , 2012 .

[22]  Simon Jude,et al.  Investigating the Potential Role of Visualization Techniques in Participatory Coastal Management , 2008 .

[23]  Mike Walkden,et al.  Dynamic simulation and visualisation of coastal erosion , 2006, Comput. Environ. Urban Syst..

[24]  M. Déjeant-Pons.  The European Landscape Convention , 2006 .

[25]  Alison Shaw,et al.  Planning for climate change in a flood‐prone community: municipal barriers to policy action and the use of visualizations as decision‐support tools , 2010 .

[26]  Eckart Lange.  99 volumes later: We can visualise. Now what? , 2011 .

[27]  Chen Wang,et al.  Urban flood risk analysis for determining optimal flood protection levels based on digital terrain model and flood spreading model , 2010, The Visual Computer.

[28]  H. Huntington.  Creating a Climate for Change: Communicating Climate Change and Facilitating Social Change , 2007 .

[29]  A. Spence,et al.  The Psychological Distance of Climate Change , 2012, Risk analysis : an official publication of the Society for Risk Analysis.

[30]  G. Fry,et al.  Indicators of perceived naturalness as drivers of landscape preference. , 2009, Journal of environmental management.

[31]  M. Hilferink,et al.  Affective appraisal of 3D land use visualization , 2010, Comput. Environ. Urban Syst..

[32]  Aleksandra Dulic,et al.  Visual Climate Change Communication: From Iconography to Locally Framed 3D Visualization , 2014 .

[33]  J. Hertin,et al.  Socio-economic futures in climate change impact assessment: using scenarios as ‘learning machines’ , 2002 .

[34]  R. Kaplan,et al.  The Experience of Nature , 2022, Why Conserve Nature?.

[35]  J. Coffey,et al.  Visualising coastal seabed characteristics: Using VRML models to present three dimensional spacial data via the web , 2007 .

[36]  Andrew A. Lovett,et al.  Developing scenarios and visualisations to illustrate potential policy and climatic influences on future agricultural landscapes , 2006 .

[37]  Stewart J. Cohen,et al.  Future visioning of local climate change: A framework for community engagement and planning with scenarios and visualisation , 2011 .

[38]  Angela Wilkinson,et al.  Challenges to scenario-guided adaptive action on food security under climate change , 2014 .

[39]  S. Sheppard.  Visualizing Climate Change: A Guide to Visual Communication of Climate Change and Developing Local Solutions , 2012 .

[40]  José Miguel Salles Dias,et al.  Accurate Infrared Tracking System for Immersive Virtual Environments , 2011, Int. J. Creative Interfaces Comput. Graph..

[41]  I. Knez,et al.  Cultural ecosystem services provided by landscapes: Assessment of heritage values and identity , 2012 .

[42]  Nicholas Frank Pidgeon,et al.  Framing and Communicating Climate Change: The Effects of Distance and Outcome Frame Manipulations , 2010 .

[43]  Suraje Dessai,et al.  Negotiating future climates for public policy: a critical assessment of the development of climate scenarios for the UK , 2008 .

[44]  Chen Wang,et al.  Use of 3D Visualisation Tools for Representing Urban Greenspace Spatial Planning , 2015, 2015 2nd International Conference on Information Science and Control Engineering.

[45]  Petr Cizek,et al.  The ethics of Google Earth: crossing thresholds from spatial data to landscape visualisation. , 2009, Journal of environmental management.

[46]  P. Verburg,et al.  Downscaling of land use change scenarios to assess the dynamics of European landscapes , 2006 .

[47]  Huadong Guo,et al.  Digital Earth 2020: towards the vision for the next decade , 2012, Int. J. Digit. Earth.

[48]  Sophie A. Nicholson-Cole.  Representing climate change futures: a critique on the use of images for visual communication , 2005, Comput. Environ. Urban Syst..

[49]  Paula A. Harrison,et al.  Identifying robust response options to manage environmental change using an Ecosystem Approach: A stress-testing case study for the UK , 2015 .

[50]  J. N. Perry,et al.  Simulation scenarios of spatio-temporal arrangement of crops at the landscape scale , 2010, Environ. Model. Softw..

[51]  Ian D. Bishop,et al.  Visual assessment of off-shore wind turbines: The influence of distance, contrast, movement and social variables , 2007 .

[52]  R. Gifford,et al.  Personally Relevant Climate Change , 2013 .

[53]  Chen Wang,et al.  Automatic Reconstruction Of 3D Environment Using Real Terrain Data And Satellite Images , 2012, Intell. Autom. Soft Comput..

[54]  Keywan Riahi,et al.  A new scenario framework for climate change research: the concept of shared socioeconomic pathways , 2013, Climatic Change.

[55]  Esther Eidinow,et al.  Evolving practices in environmental scenarios: a new scenario typology , 2008 .

[56]  P. M. Schmitz,et al.  Research, part of a Special Feature on Landscape Scenarios and Multifunctionality - Making Land Use Assessment Operational Evaluating Today's Landscape Multifunctionality and Providing an Alternative Future: A Normative Scenario Approach , 2010 .

[57]  Frederick Steiner,et al.  The ecological imperative for environmental design and planning , 2013, Frontiers in Ecology and the Environment.

[58]  Stewart J. Cohen,et al.  Making local futures tangible - synthesizing, downscaling, and visualizing climate change scenarios for participatory capacity building. , 2009 .

[59]  Helena Rua,et al.  Living the past: 3D models, virtual reality and game engines as tools for supporting archaeology and the reconstruction of cultural heritage – the case-study of the Roman villa of Casal de Freiria , 2011 .