The invention discloses a mountain torrent
debris flow dynamic and static segmentation and directional monitoring method and
system, and the method comprises the steps: firstly carrying out the dynamic boundary filtering and improved RANSAC plane extraction of an original
point cloud, constructing a stable
terrain reference, and achieving the self-adaptive updating through a multi-frame fusion and time decay mechanism; then, KDTree is adopted to realize preliminary classification of dynamic and static point clouds, and in combination with
DBSCAN clustering and small cluster filtering strategies, sensor
noise interferences such as raindrops and boulders are effectively eliminated; for a dynamic fluid
point cloud, a curvature sensing non-uniform
voxel downsampling method is introduced, fluid edge features are retained, and the data volume is compressed. And a main flow direction is further extracted through PCA
principal component analysis, and a
natural coordinate system is constructed to adapt to the channel
terrain. The
system realizes resource optimization and emergency sensitive detection based on a Streamz
stream processing structure and an event triggering mechanism. The whole process supports low-power-consumption embedded deployment, has real-time performance, robustness and geometric fidelity, and is suitable for automatic
debris flow monitoring and early warning in a complex mountainous area environment.