The role of geovisualisation to support decision-making in major engineering projects

Abstract

Within large engineering consultancies, multi-disciplinary projects are common, incorporating large volumes of varied and volatile high-dimensional data usually geospatial in nature, and often exhibiting uncertainty. Attached to such projects are Environmental Impact Assessments (EIAs), which are legally embedded in engineering practice as an EU directive and use a combination of data types, sourced from numerous disciplines. These provide information for stakeholders, including planners, local authorities, and the public, in projects which affect neighbourhoods, districts, and landscapes. Contemporary geovisualisations can incorporate and help users of the outputs from a variety of analyses and models, including EIAs, enhancing decision-making processes inherent in all engineering projects. This research project considers three main themes: cognition (decision making), visualisation and EIAs. Although discrete, these all contribute to decision making in an engineering consultancy for large development projects. A major aim is to understand how users interact with spatial data, in terms of considering the role of spatial data in decision making within the industrial practice and assess methods of visualising this data effectively. This requires investigation of user interaction with such visual, graphical, and map-based representations. Synthetic decision-making scenarios were created, which examined participants' use of geospatial data on a web map for three different environmental impact-based scenarios. Embedded within each scenario was a series of tasks for the participants to complete. Eye-tracking was used as the main method for data collection within this project, which is supported by information about the participant which will help segment up the data during analysis. Eye-tracking was chosen as a major research methodology because by analysing eye movements within realistic decision making scenarios, we can gain an objective insight into the behaviour of that participant and what information they use to come to a decision. This information can then be used to personalise and improve outputs within EIAs in the form of tailored geovisualisations. The study itself took place in-situ, which is both a novel and key element to this research. The research found that participants' preferences should be considered when designing tools to facilitate decision making. By looking at participants' map usage, layer-usage, decision making and interactions we were able to gain a greater understanding of participants’ requirements for decision support tools. The quantitative analysis looked at key eye-tracking metrics, segmenting the map, and looking at the different map elements ii (legend and map). Participants interacted with elements in different amounts depending on which task was being completed. We also concluded that the choice of basemap does not impact the decision being made, where possible the user should have the option of a variety of different basemaps to suit their preference. The qualitative analysis examined the participants’ use of different layers, establishing that participants interacted less with existing data on the map than the optional layers which were available to be used to help aid decision making. This research utilises eye-tracking to understand how decision support tools can be improved and altered. In turn, this allows for consideration of the role in spatial data and how it is presented when individuals are making decisions on large multidisciplinary engineering projects. Observations from this research are relevant for cartography, for Atkins, for online interactive mapping practices, and for the geospatial industry in general.