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The implementation of temporal dynamic variables improves the accuracy of spatial accessibility measurements. However, in previous studies, the temporal dynamics were partially incorporated, and a few snapshots were subjectively selected to demonstrate temporal changes of spatial accessibility, which may not represent the entire variation. In this study, we proposed a conceptual framework to leverage spatial accessibility temporal fluctuation, facilitating decision-making. Not only was the full implementation of time-dependent inputs, but the framework also employed the Gaussian two-step floating catchment area (G2SFCA) method and measured hourly spatial accessibility over 24 hours. Then, a temporal clustering with K-means and hierarchical clustering methods was performed, detecting a few distinctive temporal changes. Lastly, the significance of dynamic accessibility measurement and temporal clustering was validated using Pearson's correlations. We took electric vehicle (EV) charging stations in Seoul, South Korea, as a case study. The results presented that neglecting temporal dynamics could fail to predict accessibility during the daytime. Additionally, temporal clustering summarized the 24-hour changes of accessibility into five temporal phases and showed the need for additional resources for insufficient accessibility locations in the afternoon. Consequently, our framework elicited the temporal changes of accessibility measures and identified a specific space and time for supplementary infrastructure. [ABSTRACT FROM AUTHOR]