GC-Analyzer – Analyzing Spatiotemporal Correlations for Demand-Driven Services: Using an Interactive GeoVisual Analytics Approach in Decision-Making

Understanding spatiotemporal relationships is essential for effective urban decision-making. In this context, interactive geovisualizations offer the promising potential to support precise, rational-analytical decision processes. This paper examines a refined version of our GeoVisual Analytics tool called GC-Analyzer for analyzing spatiotemporal relationships in urban environments. We report the results of a case study where the tool was utilized in planning parking garages in a city and discuss the benefits of an interactive, geovisual analysis approach. We compare the GC-Analyzer approach with a conventional tabular representation of spatiotemporal correlations in a controlled usability study with expert users, evaluating two real-world analysis scenarios. Findings reveal that the GC-Analyzer provides substantial added value in spatiotemporal analysis, particularly enhancing users’ comprehension of complex correlations. Notably, decision-making with the GC-Analyzer was more analytical and objective, fostering a deeper understanding of spatiotemporal relationships than the tabular representations typically used for correlation results.