基于星载激光雷达数据的光子云去噪与树高提取

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关键词：ICESat-2；ATLO3；光子云去噪；光子云分类；树高；密度聚类；坡度自适应；森林遥感 中图分类号：S758.1 文献标识码：A DOI： 10.7525/j.issn.1006-8023.2026.01.001

Photon Cloud Denoising and Forest Height Extraction Based on Satellite-Borne Laser Radar Data

WANG Fangxin，XING Yanqiu*，LI Yuanxin，TANG Jie，WANGDejun （College of Mechanical and Electrical Engineering，NortheastForestry University，Harbin ，China）

Abstract：Treeheight isakeyparameterfor assessing forestcarbon storage，andsatelite-borne laserradartechnology providesan efective means forlarge-scale monitoring.Thenew generationof ice，cloud and land elevationsatellite-2 （ICESat-2）equipped with theadvanced topographic laser altimeter system（ATLAS）generates alotof noise inthe process of receiving signals，and the terain is akey factor affecting the denoising results.To address this problem，a ground slopeadaptive densityclustering denoising algorithm is proposed to complete thephoton clouddata denoising.Iterative median filtering and dynamic residual threshold method areused to clasify photon clouds and then extract tree height.The canopy height model（CHM）obtainedfrom airborne laser radardata isused asverification data.The reliability of extracting tree height from ICESat-2/ATLAS global geolocated photon data（ATLO3）is analyzed and evaluated from threeaspects：strong and weak beams，slope，and vegetation coverage.The results show that，1）Therecalrate （204号 （R） ，precision rate （ P ）and harmonic mean （ F ）of the proposed denoising algorithm are better than those of the differential progressve gaussian adaptive denoising algorithm（DRAGANN）.2） The accuracy of extracting treeheight from nighttime strong beam data is the best，with a mean absolute error（MAE）of 2.49 m and a root mean square error （RMSE）of 3.O3 m.3）As the slope increases，the accuracy of tree height extraction gradually decreases，and the RMSE increases from 2.25m to 6.52 m.4）As the vegetationcoverage increases，，theaccuracyof tree height extraction gradually decreases，and the RMSE increases from 3. 06m to 4.53m . The results show that it is feasible to extract tree height using ATLO3 photon cloud data，which can provide efective data supportfor studying forest growth conditions in forest areas.

Keywords： ICESat-2；ATLO3；photon cloud denoising；photon cloud clasification； forest height；density clustering; slope adaptivity; forest remote sensing

0 引言

森林是陆地生态系统中重要组成部分，具备碳汇功能，可缓解气候变化，应对全球变暖带来的一系列相关问题[]。（剩余13663字）