Background: Urban activity rhythms vary throughout the day and across different types of days. Mismatches between the timing of population presence and the temporal availability of services may affect temporal accessibility and the efficient use of urban spaces.

Objective: This study aimed to test a quantitative framework for identifying and comparing daily urban activity rhythms, examining their variation across day types, and prioritizing spatiotemporal interventions in three selected areas of Tehran: Tajrish, Enghelab–Valiasr, and Naziabad.

Research Method: A multi-source spatial scenario dataset comprising 12 urban nodes, three day types, and six time periods was used to evaluate the proposed framework. In total, 324 fifteen-minute observations were analyzed, including 216 primary observations and 108 supplementary observations from three reference stations. The analyses included the Urban Activity Intensity Index, temporal balance, evening–night activity share, Friedman and Wilcoxon tests, Spearman correlation, hierarchical clustering, temporal service-gap analysis, and an intervention-priority model.

Findings: Mean activity intensity was higher in Enghelab–Valiasr than in Tajrish and Naziabad. Day type had no statistically significant effect on overall activity intensity, whereas temporal balance and evening–night activity share differed significantly between working days and Fridays. The selected three-cluster solution showed acceptable separation and identified three activity-rhythm types: evening commercial–leisure, residential–nighttime, and bimodal transport-oriented patterns. Sensitivity analysis under alternative policy-weighting scenarios further showed that some intervention rankings varied according to the adopted policy orientation.

Conclusion:The proposed framework integrates urban activity rhythms, temporal service supply, and intervention priorities within a unified spatiotemporal analytical structure. The findings also indicate that intervention priorities should be differentiated according to node function, temporal demand, and policy orientation.