GEDI与ICESat-2星载激光雷达数据反演树高研究

孔得伦; 邢艳秋

doi:10.12302/j.issn.1000-2006.202309009

孔得伦, 邢艳秋

南京林业大学学报（自然科学版） ›› 2025, Vol. 49 ›› Issue (2) : 175-184.

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南京林业大学学报（自然科学版） ›› 2025, Vol. 49 ›› Issue (2) : 175-184. DOI: 10.12302/j.issn.1000-2006.202309009

研究论文

GEDI与ICESat-2星载激光雷达数据反演树高研究

孔得伦 ,
邢艳秋 ^*

作者信息 +

Inversion of tree height from GEDI and ICESat-2 spaceborne lidar

KONG Delun ,
XING Yanqiu ^*

Author information +

文章历史 +

摘要

【目的】全球生态系统动力学调查(GEDI)多波束激光雷达与冰、云和陆地高程卫星二代(ICESat-2) 光子云使用不同激光雷达技术,导致两个任务之间的树高提取值存在差异。比较两种星载激光雷达数据在不同情况下有效反演树高的能力,为空间连续大区域高分辨率森林树高制图提供理论基础。【方法】通过对GEDI L2A字段信息进行定位和筛选,并进行地形高程精度验证,对比6种算法组反演树高;对ICESat-2数据去噪并提出基于坡度变化的光子云分类算法,建立地面光子线和冠层顶线反演树高,利用实测数据和机载激光雷达数据,验证并比较GEDI和ICESat-2在研究区内反演树高的精度。最后,定量分析GEDI和ICESat-2数据在不同地形坡度、植被覆盖度和森林类型情况下反演树高的差异。【结果】针对GEDI L2A产品数据,通过比较6组GEDI L2A算法中最优算法的反演精度为:R²=0.94,均方根误差(RMSE)为2.31 m,绝对平均误差(MAE)为1.27 m。针对ICESat-2 数据,通过使用50 m窗口计算,基于坡度变化的光子云分类算法提取树高与机载树高的R²=0.81,RMSE为3.68 m,MAE为2.45 m。植被覆盖度相对于地形坡度和森林类型对两种星载激光雷达反演树高产生更大的影响。【结论】对于较为平缓且森林类型以针叶林为主的较密集区域,其GEDI数据相比于ICESat-2数据表现出更优的评价精度。

Abstract

【Objective】Global ecosystem dynamics investigation (GEDI) multibeam lidar and ice, cloud and land elevation satellite-2 (ICESat-2) photon clouds use different lidar technologies, resulting in differences in tree height extraction values between the two tasks. The purpose of this study is to compare the ability of two spaceborne lidar data to effectively invert forest height under different conditions. 【Method】By locating and filtering the GEDI L2A field information, and verifying the terrain elevation accuracy, the tree height of six algorithm groups was compared. The ICESat-2 data was denoised, a photonic cloud classification algorithm based on slope change was proposed, the ground photon line and the canopy top line inversion forest height were established, and the accuracy of GEDI and ICESat-2 in the study area was verified and compared by using the measured data and airborne lidar data. Finally, the differences of GEDI and ICESat-2 data in different terrain slopes, vegetation coverage and forest types were quantitatively analyzed. 【Result】According to the GEDI L2A product data, by comparing the optimal algorithms in GEDI L2A algorithm group from a1 to a6, the inversion accuracy of a4 was better: R²=0.94, root mean square error was 2.31 m, and mean absolute error was 1.27 m. For ICESat-2 data, R²=0.81, the root mean square error was 3.68 m, and the mean absolute error was 2.45 m, calculated using a 50 m window. Vegetation coverage had a greater impact on the tree height of the two spaceborne lidars compared to the terrain slope and forest type. 【Conclusion】Compared with ICESat-2 data, GEDI data showed a better evaluation accuracy standard for the more gentle and densely populated areas with coniferous forest types.

导出引用

孔得伦, 邢艳秋. GEDI与ICESat-2星载激光雷达数据反演树高研究[J]. 南京林业大学学报（自然科学版）. 2025, 49(2): 175-184 https://doi.org/10.12302/j.issn.1000-2006.202309009

KONG Delun, XING Yanqiu. Inversion of tree height from GEDI and ICESat-2 spaceborne lidar[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2025, 49(2): 175-184 https://doi.org/10.12302/j.issn.1000-2006.202309009

中图分类号： S771.8

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