Urban　rail　transit　is　an　essential　part　of　the　urban　public　transportation　system.　The　reasonable　spatial　data　visualization　of　urban　rail　transit　stations　can　provide　a　more　intuitive　way　for　the　majority　of　travelers　to　arrange　travel　plans　and　find　destinations.　The　map　service　of　rail　transit　stations　generated　by　data　visualization　has　gradually　become　indispensable　information　guidance　in　the　rail　transit　system.　The　existing　map　service　icons　block　each　other　when　the　scale　changes,　and　new　stations　cannot　be　displayed　dynamically　when　users　drag　the　map.　This　paper　uses　filtering　and　sorting　methods　to　dynamically　query　and　visualize　the　relatively　more　important　transportation　stations　within　the　users＇　visible　range,　so　as　to　solve　the　above　problems　and　provide　people　with　better　transportation　services.　Our　method　introduces　three　constraints:　spatial　diversity,　time-sharing　passenger　flow　analysis　and　whether　it　is　a　transit　station,　and　calculates　the　scores　of　constraint　relationships　of　feature　objects　to　evaluate　stations.　On　the　basis　of　the　skyline　query,　the　scores　of　feature　objects　are　combined　and　sorted　to　obtain　an　ordered　object　set　of　the　most　interesting　k　points(top-k　POIs),　and　the　rail　transit　stations　are　dynamically　retrieved　and　visualized.　Before　sorting　POIs,　we　filter　out　POIs　that　need　to　be　fitted,　so　that　only　the　k　most　representative　POIs　in　the　currently　visible　range　are　displayed.　When　the　map　scale　changes,　the　displayed　POIs　are　updated.　Finally,　through　the　statistics　of　efficiency　calculation　of　this　method　under　different　scales　and　centers,　combined　with　users＇　evaluations,　it　was　proved　that　our　method　could　better　display　critical　information　and　improve　user　experience.