As China’s urban landscape evolves, the frequency and complexity of fire incidents have increased, causing severe secondary disasters and widespread damage. Fire-induced disaster chains present cumulative and unpredictable risks, exacerbated by environmental, structural, and human factors. We construct a fire propagation model based on disaster chain theory, integrating hazard-causing elements, vulnerable assets, and disaster-inducing environments. Using data from 75 government-reported fire incidents and on the basis of complex network theory, we identified key risks and analyzed their fire propagation capabilities using comprehensive degree, clustering coefficient, and eigenvector centrality. Thirty-nine interconnected risks were identified, and their effect on fire propagation was assessed. Several risks, despite high propagation potential, had minimal influence, while others with strong connectivity required extensive monitoring. The role of sensor networks in early detection and control was emphasized, and simulation results supported targeted risk management strategies. The results of this study emphasize the need for data-driven fire control, optimizing sensor deployment, and prevention strategies to mitigate the cascading effects of fire disasters.