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树木遮挡下的机载Lidar点云建筑物轮廓提取.docx

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树木遮挡下的机载Lidar点云建筑物轮廓提取 Title:ExtractionofBuildingOutlinesfromAirborneLiDARPointCloudsunderTreeCanopyCover Abstract: Theaccurateextractionofbuildingoutlinesisofgreatsignificanceinurbanplanning,3Dmodeling,andresourcemanagement.However,thepresenceoftreecanopycoverposesaconsiderablechallengetothistask.Inthispaper,weproposeamethodutilizingairborneLiDARpointcloudsforextractingbuildingoutlinesundertreecanopycover.Themethodcombinespointcloudsegmentation,digitalsurfacemodelgeneration,andedgedetectionalgorithmstoaccuratelydelineatethebuildingboundaries.Experimentalresultsdemonstratetheeffectivenessandreliabilityoftheproposedapproachinextractingaccuratebuildingoutlineseveninchallengingconditions. 1.Introduction: Accuratebuildingoutlinesareessentialfornumerousapplications,includingurbandevelopment,disastermanagement,andinfrastructureplanning.Traditionalmethods,suchasmanualdigitizationandphotogrammetry,havelimitationsinextractingbuildingoutlinesduetoocclusionscausedbytreecanopycover.Withthedevelopmentofremotesensingtechnology,airborneLiDARhasemergedasapromisingtoolforcapturinghigh-resolution3DinformationoftheEarth'ssurface,includingbuildings.ThispaperaimstopresentamethodforeffectivelyextractingbuildingoutlinesfromairborneLiDARpointcloudsundertreecanopycover. 2.Methodology: 2.1DataAcquisition: AirborneLiDARdata,whichincludesLiDARpointcloudsandcorrespondingintensityvalues,iscollectedusingalaserscannermountedonanaircraft.Thedatasetshouldhavesufficientpointdensity,pointcloudquality,andcoveragetoensureaccurateextraction. 2.2Preprocessing: Datapreprocessingstepsinvolvefilteringoutvegetationpoints,noiseremoval,andgroundfilteringtoobtaincleanandreliablepointclouds.TechniquessuchasNormalVectorAnalysis(NVA)andCanopyHeightModel(CHM)canbeemployedtoidentifyandremovevegetationpoints. 2.3PointCloudSegmentation: Toseparatepointsbelongingtobuildingsfromotherobjects,apointcloudsegmentationalgorithm,suchasregiongrowingorvoxel-basedclustering,isapplied.Thealgorithmgroupsadjacentpointswithsimilarcha