103LandscapeArchitectureAcademicJournal园林／2024年／第41卷／第02期AbstractThetraditionalmeasurementmethodofvegetationindicatorsconsumesalotofmanpower,materialresourcesandtime,andignorestheecologicalbenefitsofdifferentvegetationtypesandstructures.Thepointclouddatacaneffectivelyevaluatethe3Dvegetationparametersofurbangreenspace,butduetotheinfluenceofdataaccuracy,algorithmsoftwareandotherfactors,theaccuracyoftheresultsofthismethodhasanerrorof10%to20%.Inthispaper,takingTangfengSouthRoadinTangshanCityasanexample,threetypicalsampleplots(50m×50m)wereselectedtocollectUAVremotesensingimagesandhandheldlidardata,andathree-dimensionalvegetationparametersystemwasconstructedfromthesingletreescaleandthesampleplotscale.CorrectioncoefficientswereproposedforeightparametersintheUAVpointclouddata,includingthenumberofindividualtrees,thetotalcrownwidtharea,thegreenamountofthetreelayer,thegreenamountoftheshrublayer,theaveragethree-dimensionalgreendensity,thecanopydensity,thegaprateandtheleafarea,andthefiveparametersofthehandheldlidardata,includingtheaveragetreeheight,theaveragecrowndiameter,theaveragecrownwidtharea,thegreencontentofthearborlayerandtheaveragethree-dimensionalgreendensity,inordertoimprovetheaccuracyoftheresultsandprovidehelpforthefollow-upresearch.Final-ly,thispaperdiscussesthepossibleapplicationdirectionsofUAVphotogrammetrytechnologyandlidartechnologyinthefuture.KeywordsUnmannedAirVehicle,UAV;photogrammetry;LightDetectionandRanging,LiDAR;datafusion;three-dimensionalvegetationparameters园林，2024，41（02）：103-110.文章编号：1000-0283(2024)02-0103-08DOI:10.12193/j.laing.2024.02.0103.013中图分类号：TU986文献标志码：A收稿日期：2023-11-07修回日期：2023-12-04摘要传统植被指标的测量方式需要消耗大量的人力、物力与时间，且忽视了不同植被类型和结构的生态效益影响。基于点云数据能够有效评估城市绿地三维植被参数，但受制于数据精度、算法软件等因素影响，该方法结果精度存在10%～20%的误差。以唐山市唐丰南路为例，选取了三处典型样地（50m×50m），进行无人机遥感影像和手持激光雷达数据采集，从单木...
