The　scarcity　of　convenient　bicycle　lanes　that　transcend　geographical　barriers　hinders　the　establishment　of　a　seamless　and　comprehensive　bicycle　network　within　urban　areas,　consequently　reducing　people＇s　willingness　to　use　bicycles　for　transportation　and　posing　a　significant　challenge　to　promoting　sustainable　development　in　urban　transportation　in　China.　A　method　is　proposed　to　identify　geographical　barriers　that　impede　bicycle　travel.　By　focusing　on　the　area　within　Beijing＇s　Fifth　Ring　Road　as　a　case　study,　the　study　leverages　mobile　signaling　and　shared　bicycle　data　to　extract　potential　bicycle　travel　patterns.　Community　detection　algorithm　is　employed　to　divide　the　area　into　zones　and　identify　travel　boundaries.　A　total　of　24　travel　boundaries　were　identified,　with　11　of　them　deemed　as　high-priority　geographical　barriers.　The　potential　carbon　emissions　reduction　was　quantified　and　recommendations　for　infrastructure　enhancement　were　provided.　This　method　offers　a　cost-effective　and　efficient　means　to　analyze　weaknesses　in　bicycle　infrastructure.　The　findings　of　this　research　can　contribute　to　the　enhancement　of　urban　bicycle　networks　and　facilitate　the　sustainable　development　of　urban　transportation.　©　2025