Exploring　the　spatial　distribution　of　tourist　attractions　and　comprehending　the　spatio-temporal　behaviors　of　tourists　within　tourist　attractions　can　provide　local　planning　agencies,　destination　marketing　organizations,　and　government　departments　with　essential　evidence　for　decision-making　processes.　This　study　examines　the　spatio-temporal　behavior　patterns　of　tourists　in　the　Kushan　Scenic　Area　by　analyzing　GPS　trajectory　data　acquired　from　social　media　platforms.　The　investigation　primarily　utilizes　three　research　methodologies:　grid　analysis,　Markov　chain,　and　K-means　clustering.　The　grid　analysis　results　reveal　three　spatial　distribution　patterns　within　the　scenic　area,　while　the　outcomes　from　the　Markov　chain　and　K-means　clustering　delineate　six　tourist　movement　patterns,　along　with　three　choices　regarding　travel　time.　This　finding　holds　significant　practical　implications　for　enhancing　the　attractiveness　of　scenic　areas,　optimizing　spatial　layout,　and　improving　tourists’　experiences.　©　2024　by　the　authors.