基于谱聚类的星载激光雷达（GEDI）乔灌波形分离方法

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中图分类号：S771 文献标志码：A

【结论】本文提出一种基于谱聚类的乔灌波形分离方法，本方法无需数据标注和高程阈值预设，可为全球尺度森林垂直结构解析及碳储量动态监测提供可靠的技术支撑。

Research on waveform separation of trees and shrubs in spaceborne LiDAR GEDI based on spectral clustering

RENPeng，XINGYanqiu，WANGDejun，TANGJie，LIYuanxin （，Harbin5oo0，，Cina）

Abstract：【Objective】ToadresstheissuethatspaceboeLiDARwaveforsaredifcult todirectlyuseforparameteriversionof asinglevegetationtype，thisstudyaimstoproposeandvalidateanautomaticseparationmethodfortreeandhrublidarwaveforms， inordertoobtainindependent waveformdatafortresandshrubs.【Method】BasedonthedatafromthespaceborneLiDAR（Global ecosystemdynamicsinvestigation，GEDI），thisstudyperformed GausiandecompositionontheGEDIL1Bfielddataafteroving groundwaveforms.Theobtained Gausian echoes werethenclustered usingspectral clustering methodstoseparatelyotainarbor echoesandshrubechoes.Basedontheprincipleofechosimulationcombinedwithgroundmeasurements，astandardizedreference datasetofarborandshrub waveforms wassimulatedtoverifyandevaluate theclusteringaccuracy.【Result】Intheareas withslopes of [0∘，15∘） ，[15°， 30∘， ，and ⩾30∘ ，the correlation coefficients between the tree waveform separation results and the simulation results were0.89，0.deaseleo betwenthesbavefoepatioltsdtulatisultse828，dpeielyitota errorsof 0.024，0.044，and 0.077，respectively.In the areaswith canopy densities of[0， 30% ） [30% ， 60% ，and [60% ， 100% ，the correlationoecietstenthtreavfoepaatioltsdtesulatioultsre9.8ad.8sptiely withrootmeansquareerrosofO055，0042，and0.O17respectivelyTheorelationcoficientsbetweentheshbwavform separationrsultsdthlatiosultse.，.8ndspecelyioteaareesofd 0.053，respectively.In the areaswith shrub coverages of[0， 30% [30% 60% ，and 60% 100% ]，thecorrelationcoefficients between thetreewaveatisultsdtlatisultse.882ndOespctielyitota 0.028，0.029nd，spctielyeelaioocintseentbaefoseatiosutsdelaion resultswere0.dsieiaeoodiely【 paperproposesatre-shrub waveformseparationmethodbasedonspectralclusteringwhicheliminatestheneedfordataaotation andelevtionthesholdpresetingTismethodcanprovideeliabletechicalsupprtfoanalyingtheverticalstructureofforstsand monitoring carbon stock dynamics at the global scale.

Keywords： GEDIL1B;spectral clustering;arbor and shrub waveform; echo simulation; Waveform separation

森林作为全球最大的碳汇，对全球气候变化具有举足轻重的长远影响[1-2]。（剩余16861字）