Pantana phyllostachysae Chao is a leaf-eating pest that poses a significant threat to bamboo forest health. Current research mainly focuses on statically identifying damage using remote sensing images. However, the mechanism behind the damage's traceability remains unclear, making it difficult to pinpoint early infestation sources accurately. Additionally, our understanding of the pest's spreading laws is limited. This study leverages Sentinel-2A/B images from February to November 2021 to investigate P. phyllostachysae infestation traceability through the dynamic age algorithm and indicator analysis method. The results shed light on the distribution of early pest sources over the study period. By analyzing both the overall pest infestation “cluster” and its center of gravity, we dissect P. phyllostachysae infestation characteristics and paths monthly throughout the study period. Our findings reveal three zones with strong spreading momentum, three with slow spreading momentum, and two transitional zones during the February-November period, aligning with P. phyllostachysae occurrence patterns. However, the direction of P. phyllostachysae spreading varies, likely due to a combination of meteorological, topographical, vegetative biochemical, and human activity factors. This study introduces innovative approaches for identifying early pest source points and understand their spreading laws, contributing to more effective pest prevention and control in forest ecosystems.