Urban emergencies in Osogbo have exhibited complex spatial, temporal, and statistical patt- -atterns that demand adaptive resilience strategies. Using data from 2015–2025, this study employed spatial mapping, seasonal cat- -egorization, and advanced statistical analyses to examine fire incidents and medical/accident emergencies. Results revealed that emergenci- -es cluster in densely populated corridors and vary seasonally, with fire incidents peaking in hot dry months and medical emergencies dominating rainy and warm dry seasons Statis- -tical calculations reinforced these findings: Pearson correlation indicated a strong inverse relationship between fire and medical emergencies (r = -0.63); regression analysis confirmed predictive strength (R2 = 0.4, p < 0.04); Chi- square and ANOVA tests validated significant seasonal associations (X 2 = 132.5, p < 0.05; (F (17.4) >15.62)). Collectively, these findings underscore a shift in urban vulnerability from fire hazards toward health and accident emergencies, driven by climatic variability and urban growth Policy implicat- -ions emphasize strengthening healthcare infrastructure,implementing seasonally adap- -tive preparedness, and targeting high risk urban corridors. The study concludes that Osogbo‟s resilience depends on integrating statistical evidence with spatio-temporal insi- -ghts to guide proactive, climate sensitive emergency management.