集成高分辨率UAV影像与激光雷达点云的亚热带森林林分特征反演

doi:10.17521/cjpe.2015.0066

摘要/Abstract

摘要：

该研究集成高分辨率无人机(UAV)影像和激光雷达(LiDAR)点云数据估算亚热带天然次生林林分基本特征变量。首先, 基于LiDAR点云和反距离加权插值法构建林下高精度数字高程模型(DEM); 然后利用UAV影像对序列构建植被冠层上层三维点云, 并借助DEM进行高度信息归一化, 提取高度和冠层点云密度相关的特征变量; 最后, 构建预测模型并估算Lorey’s高、林分密度、胸高断面积、蓄积量。结果表明: 联合提取的特征变量与Lorey’s高的敏感性最高, 蓄积量次之, 林分密度和胸高断面积最低; 利用UAV灵活快速的手段获取森林冠层信息, 辅以高精度LiDAR数据获取的地形信息, 两者互补实现一种可重复的快速、廉价和灵活的林分特征的反演方式。

关键词: 无人机, 激光雷达, 点云, 林分特征

Abstract: Aims We applied the integrated very high resolution imagery acquired from Unmanned Aerial Vehicles (UAV) and Light Detection and Ranging (LiDAR) point-loud data to estimate the stand characteristics of a naturally- regenerated forest in a subtropical area. Methods The high precision digital elevation model (DEM) of the forest was constructed base on LiDAR point-cloud and the inverse distance weighted interpolation method. The 3D point-cloud of forest canopy layer was constructed from UAV image pairs, with information from DEM height information normalization, for canopy height and density. With the above effort, we developed a prediction model to estimate Lorey’s height, stand density, basal area, and volume. Important findings The quantitative metrics generated from this study appeared very sensitive to Lorey’s height, followed by volume and basal area. Using UAV as a flexible and rapid method for generating forest canopy characteristics, combined with topographic information from high precision LiDAR data, seems a viable, rapid, inexpensive, and flexible method in canopy research.

Key words: LiDAR, point cloud, stand characteristics, UAV

许子乾, 曹林, 阮宏华, 李卫正, 蒋圣. 集成高分辨率UAV影像与激光雷达点云的亚热带森林林分特征反演. 植物生态学报, 2015, 39(7): 694-703. DOI: 10.17521/cjpe.2015.0066

XU Zi-Qian,CAO Lin,RUAN Hong-Hua,LI Wei-Zheng,JIANG Sheng. Inversion of subtropical forest stand characteristics by integrating very high resolution imagery acquired from UAV and LiDAR point-cloud. Chinese Journal of Plant Ecology, 2015, 39(7): 694-703. DOI: 10.17521/cjpe.2015.0066

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2015.0066

https://www.plant-ecology.com/CN/Y2015/V39/I7/694

图/表 9

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树种 Tree species	公式 Formula	备注 Remark
杉木 Cunninghamia lanceolata	V = A × D^B × (E × D + G × lgD)^C	A = 0.000058777042, B = 1.9699831 C = 0.89646157, E = -2.2426 F = 0.2021, G = 6.6922
水杉 Metasequoia glyptostroboides	V = A × D^B × ((E + F × e ⁽^G^×^D⁾)^H)^C	A = 0.000058777042, B = 1.9699831 C = 0.89646157, E = 1.000438 F = -0.00024755, G = -0.07897864 H = 7101.252
侧柏 Platycladus orientalis		A = 0.000091972184, B = 1.8639778 C = 0.83156779, E = 1.000084 F = -0.0000671125, G = -0.1223273 H = 29416.66
林分阔1 Broadleaf 1 (杨 Populus、栎 Quercus)		A = 0.000050479055, B = 1.9085054 C = 0.99076507, E = 0.9236004 F = 0.0502109, G = -0.09686479 H = -37.80742
林分阔2 Broadleaf 2 (刺槐 Robinia pseudoacacia、刺桐Erythrina variegata、柳 Salix、杂 Other)		A = 0.000050479055, B = 1.9085054 C = 0.99076507, E = 6.569053 F = -4.565682, G = -0.03200782 H = 1.697762

树种 Tree species	公式 Formula	备注 Remark
杉木 Cunninghamia lanceolata	V = A × D^B × (E × D + G × lgD)^C	A = 0.000058777042, B = 1.9699831 C = 0.89646157, E = -2.2426 F = 0.2021, G = 6.6922
水杉 Metasequoia glyptostroboides	V = A × D^B × ((E + F × e ⁽^G^×^D⁾)^H)^C	A = 0.000058777042, B = 1.9699831 C = 0.89646157, E = 1.000438 F = -0.00024755, G = -0.07897864 H = 7101.252
侧柏 Platycladus orientalis		A = 0.000091972184, B = 1.8639778 C = 0.83156779, E = 1.000084 F = -0.0000671125, G = -0.1223273 H = 29416.66
林分阔1 Broadleaf 1 (杨 Populus、栎 Quercus)		A = 0.000050479055, B = 1.9085054 C = 0.99076507, E = 0.9236004 F = 0.0502109, G = -0.09686479 H = -37.80742
林分阔2 Broadleaf 2 (刺槐 Robinia pseudoacacia、刺桐Erythrina variegata、柳 Salix、杂 Other)		A = 0.000050479055, B = 1.9085054 C = 0.99076507, E = 6.569053 F = -4.565682, G = -0.03200782 H = 1.697762

样地林分特征 Plot-level characteristics	统计量 Statistics (n = 30)
样地林分特征 Plot-level characteristics	变化范围 Range of variation	平均值 Average
Lorey’s树高 Lorey’s height (m)	7.00-31.65	22.99
林分密度 Stand density (plant·hm^-2)	1 146-3 950	2 560
胸高断面积 Basal area (m²·hm^-2)	2.48-13.23	6.41
蓄积量 Volume (m³·hm^-2)	66.36-488.97	274.36

样地林分特征 Plot-level characteristics	统计量 Statistics (n = 30)
样地林分特征 Plot-level characteristics	变化范围 Range of variation	平均值 Average
Lorey’s树高 Lorey’s height (m)	7.00-31.65	22.99
林分密度 Stand density (plant·hm^-2)	1 146-3 950	2 560
胸高断面积 Basal area (m²·hm^-2)	2.48-13.23	6.41
蓄积量 Volume (m³·hm^-2)	66.36-488.97	274.36

自变量(归一化点云提取参数) Independent variable	因变量(实测参数) Dependent variable
高度分位数 Height percentile (h₁₀, h₂₅, h₃₀, h₄₀, h₆₀, h₇₅, h₈₅, h₉₀)	Lorey’s树高 Lorey’s height (m) 林分密度 Stand density (plant·hm^-2) 胸高断面积 Basal area (m²·hm^-2) 蓄积量 Volume (m³·hm^-2)
点云密度变量 Point cloud density variables (d₁₀, d₂₅, d₃₀, d₄₀, d₆₀, d₇₅, d₈₅, d₉₀)
高度均值 Average height (h_avg) 高度最值 Maximum/minimal height (h_max, h_min)