Abstract
Spatial cluster analysis is crucial for understanding localized patterns in geospatial data, with wide-ranging applications for scientific discovery and decision-making. However, the dynamic nature of spatial clusters and the diverse range of clustering methods available can make analysis and interpretation challenging. We introduce ClusterRadar, a web-based tool designed to streamline this process by uniquely prioritizing longitudinal analysis and multi-method comparison of spatial clusters. It empowers users to easily perform clustering with multiple methods, directly compare results, and visualize spatiotemporal patterns through a novel design of linked interactive visualizations. ClusterRadar aims to maximize utility to a broad user base by supporting various geospatial formats and executing entirely within the browser to ensure data privacy. ClusterRadar is available at https://episphere.github.io/ClusterRadar.
| Original language | English |
|---|---|
| Article number | e0322393 |
| Number of pages | 23 |
| Journal | PLoS One |
| Volume | 20 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 27 May 2025 |
Keywords
- ClusterRadar
- web-tool
- spatial clusters
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Dive into the research topics of 'ClusterRadar: an interactive web-tool for the multi-method exploration of spatial clusters over time'. Together they form a unique fingerprint.Student theses
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Interactive visualization of data-driven methods for the exploration of spatiotemporal public health data
Mason, L. (Author), Almeida, J. (Supervisor), Hicks, B. (Supervisor) & Orr, N. (Supervisor), Jul 2025Student thesis: Doctoral Thesis › Thesis with Publications
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