Tree　shade　is　an　important　resources　for　mitigating　the　effects　of　extreme　heat　in　urban　areas.　Quantifying　the　extent　of　tree　shade　resources　can　assist　in　the　prediction　and　risk　assessment　of　high　temperatures　in　cities.　Among　the　existing　methods　for　estimating　tree　shade　resources,　the　measured　method　is　time-consuming　and　ineffective,　while　the　image　identification　method　is　difficult　to　accurately　respond　to　the　spatial　and　temporal　changes　of　tree　shade.　In　this　paper,　a　method　was　proposed　for　simulating　and　quantifying　tree　shade　based　on　a　three-dimensional(3D)　scene.　We　simulated　the　urban　street　scene　by　employing　3D　reconstruction　technology,　distinguished　different　geographic　entity　models,　utilising　the　sun＇s　geometric　position　parameter　and　construct　the　corresponding　lighting　environment,　and　the　shade　in　3D　scene　was　simulated　according　to　the　principle　of　linear　propagation　of　light　and　shadow.　The　formation　of　tree　shade　is　determined　through　the　use　of　a　ray　intersection　algorithm,　which　allows　for　the　differentiation　of　sun　rays　within　a　3D　model　of　the　shading　situation.　This　process　enables　the　generation　and　classification　of　tree　shade,　which　can　then　be　distinguished　from　shadows　cast　by　their　features.　The　attributes　of　tree　shade　(e.g.,　shade　area　and　shade　coverage　duration　facilitates)can　be　quantified　and　visualized　in　the　3D　scene　for　intuitive　representation.　A　comparison　and　verification　of　the　shadows　taken　by　the　Unmanned　Aerial　Vehicle(UAV).　The　results　of　relative　error　range　from　3.35%　to　13.27%,　with　an　average　relative　error　of　9.29%.　This　method　is　potential　for　the　estimation　of　shade　tree　resources.　In　addition,　a　case　of　shade　resources　of　trees　in　an　urban　street　scene　was　simulated　and　quantified,　taking　into　account　their　spatial　orientation,　species　and　life　cycle.　The　method　enables　the　simulation　of　the　spatial　and　temporal　distribution　of　shadow　resources　for　real　and　virtual　scenarios　(both　future　and　planned)　at　any　given　moment.　It　can　be　classified　and　counted,　thereby　providing　the　potential　service　for　urban　planning　and　management,　as　well　as　fundamental　data　for　the　analysis　of　the　cooling　effects　of　urban　trees.　©　2024　Science　Press.　All　rights　reserved.