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　Sentinel2A/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.