ClusterRadar: An interactive web-tool for the multi-method exploration of spatial clusters over time
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.
Authors
- Jonas S. Almeida (ORCID: https://orcid.org/0000-0002-7883-7922)
- Blánaid Hicks (ORCID: https://orcid.org/0000-0002-5730-9469)
- Lee Mason (ORCID: https://orcid.org/0000-0002-7814-099X)
Institutions
- Queen's University Belfast (GB)
- Department of Health and Human Services (US)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1371/journal.pone.0322393
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Cancer Institute