Spatial cluster analysis, the detection of localized patterns of similarity in geospatial data, has a wide-range of applications for scientific discovery and practical decision making. One way to detect spatial clusters is by using local indicators of spatial association, such as Local Moran's I or Getis-Ord Gi*. However, different indicators tend to produce substantially different results due to their distinct operational characteristics. Choosing a suitable method or comparing results from multiple methods is a complex task. Furthermore, spatial clusters are dynamic and it is often useful to track their evolution over time, which adds an additional layer of complexity. ClusterRadar is a web-tool designed to address these analytical challenges. The tool allows users to easily perform spatial clustering and analyze the results in an interactive environment, uniquely prioritizing temporal analysis and the comparison of multiple methods. The tool's interactive dashboard presents several visualizations, each offering a distinct perspective of the temporal and methodological aspects of the spatial clustering results. ClusterRadar has several features designed to maximize its utility to a broad user-base, including support for various geospatial formats, and a fully in-browser execution environment to preserve the privacy of sensitive data. Feedback from a varied set of researchers suggests ClusterRadar's potential for enhancing the temporal analysis of spatial clusters.

翻译：空间聚类分析，即检测地理空间数据中局部相似性模式，在科学发现和实际决策中具有广泛应用。检测空间聚类的一种方法是使用局部空间关联指标，例如Local Moran's I或Getis-Ord Gi*。然而，不同指标因其操作特性差异往往产生显著不同的结果。选择合适的方法或比较多种方法的结果是一项复杂任务。此外，空间聚类具有动态性，追踪其随时间演变通常具有重要价值，这进一步增加了分析复杂度。ClusterRadar是一个专为解决这些分析挑战而设计的网络工具。该工具允许用户在交互式环境中轻松执行空间聚类并分析结果，其独特之处在于优先考虑时间分析和多方法比较。工具交互式仪表盘呈现多种可视化视图，每种视图从不同角度展示空间聚类结果的时间和方法维度。ClusterRadar具备多项功能以最大化其广泛用户群体的适用性，包括支持多种地理空间数据格式，以及完全在浏览器中运行的执行环境以保护敏感数据隐私。来自不同领域研究人员的反馈表明，ClusterRadar具有增强空间聚类时间分析的潜力。