Objectives The dynamic spread of forest fires can be regarded as a dynamic obstacle system, and its nonlinear diffusion behavior poses a challenge to the safety and timeliness of emergency rescue paths. The existing path planning methods are difficult to achieve temporal matching between the evolution process of the fire scene and path decision-making, resulting in obstacle avoidance failure or suboptimal route costs.

Methods Focused on the spatiotemporal obstacle avoidance problem of emergency rescue paths in the dynamic spread environment of forest fires, a dynamic obstacle field is constructed firstly through a forest fire spread prediction model. Then, based on this field and a static obstacle field, a map algebra dynamic euclidean space shortest path with obstacles algorithm is proposed to generate a dynamic obstacle avoidance Euclidean distance field and its corresponding source-point field. Finally, path extraction is implemented based on the obstacle avoidance distance field and source-point field. The timing matching between the planned path and the fire spread was achieved, and the optimal safe path was calculated in dynamic fire obstacle scenarios, while extreme-risk areas were delineated.

Results Using the“3·30”Xichang forest fire as a prototype, dynamic obstacles were constructed in the fire scene. Multi-scenario comparative experiments evaluated varied travel speeds and time safety thresholds, including cases with complex multi-ignition scenarios featuring artificially superimposed dynamic obstacles. The results show that the planned shortest path effectively avoided the fire-affected zones, with extreme-risk areas delineated through the dynamic obstacle avoidance distance field, while maintaining safety-timeliness trade-off balance. Critically, setting context-appropriate time safety thresholds can significantly mitigate fire exposure risks without compromising rescue path costs.

Conclusions This proposed method provides a highly interpretable and robust solution for emergency rescue in dynamic obstacle environments, achieving fire path timing matching through distance field with optimal safety threshold calibration, which has significant application value in forest fire command systems.