The　increasing　availability　of　urban　trajectory　data　from　the　GPS-enabled　devices　has　provided　scholars　with　opportunities　to　study　urban　dynamics　at　a　finer　spatiotemporal　scale.　Yet　given　the　multi-dimensionality　of　urban　trajectory　dynamics,　current　research　faces　challenges　of　systematically　uncovering　spatiotemporal　and　societal　implications　of　human　movement　patterns.　Particularly,　a　data-driven　policy-making　process　may　need　to　use　data　from　various　sources　with　varying　resolutions,　analyze　data　at　different　levels,　and　compare　the　results　with　different　scenarios.　As　such,　a　synthesis　of　varying　spatiotemporal　and　network　methods　is　needed　to　provide　researchers　and　planning　specialists　a　foundation　for　studying　complex　social　and　spatial　processes.　In　this　paper,　we　propose　a　framework　that　combines　various　spatiotemporal　and　network　analysis　units.　By　customizing　the　combination　of　analysis　units,　the　researcher　can　employ　trajectory　data　to　evaluate　urban　built　environment　dynamically　and　comparatively.　Two　case　studies　of　Chinese　cities　are　carried　out　to　evaluate　the　usefulness　of　proposed　conceptual　framework.　Our　results　suggest　that　the　proposed　framework　can　comprehensively　quantify　the　variation　of　urban　trajectory　across　various　scales　and　dimensions.