Inversion of subtropical forest stand characteristics by integrating very high resolution imagery acquired from UAV and LiDAR point-cloud

doi:10.17521/cjpe.2015.0066

Abstract

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

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[J]. Chin J Plan Ecolo, 2015, 39(7): 694-703.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2015.0066

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

Figures/Tables 9

References 26

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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)