City Research Online

Gridded-glyphmaps for supporting Geographic Multicriteria Decision Analysis

Laksono, D. ORCID: 0000-0002-8503-5274, Slingsby, A. ORCID: 0000-0003-3941-553X & Jianu, R. ORCID: 0000-0002-5834-2658 (2024). Gridded-glyphmaps for supporting Geographic Multicriteria Decision Analysis. In: Tominski, C., Waldner, M. & Wang, B. (Eds.), EuroVisShort2024. 26th EG Conference on Visualization, 27-31 May 2024, Odense, Denmark. doi: 10.2312/evs.20241062


Integrating human intuition into data-driven decisions is challenging. Multicriteria Decision Analysis (MCDA) provides a structured framework for evaluating multiple criteria but often fails to capture the nuanced preferences of decision-makers. Geovisualisation tools can help understand data, but representing intricate relationships within MCDA models, especially with multivariate data, remains difficult. This study proposes a solution by combining MCDA and geovisualisation strengths using gridded-glyphmaps. This approach enables interactive exploration of multivariate geospatial data, allowing decision-makers to adjust parameter weights in real-time and dynamically assess decision alternatives. We demonstrate this approach's effectiveness through decarbonisation planning scenarios in Cambridge, UK. Our glyphs represent multiple variables' interplay, allowing for flexible criteria weight refinement. Discretising the data into grids reveals patterns and relationships missed by traditional representations like choropleth maps. Our approach demonstrates how gridded-glyphmap visualisation within an MCDA model fosters insights and transparency in decarbonisation planning scenarios.

Publication Type: Conference or Workshop Item (Paper)
Publisher Keywords: Human-centered computing, Visualization techniques, Geographic visualization, Information systems, Decision support systems
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology
School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > giCentre
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Available under License Creative Commons: Attribution International Public License 4.0.

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