Estimation of Volume based on Fusion Point Cloud of Terrestrial and UAV LiDAR

Table 1. Taper Equation
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Table 1. Taper Equation
提出者公式
Kozak $d^{2} = D^{2} (a_{1} + a_{2} (\frac{h}{H}) + a_{3} {(\frac{h}{H})}^{2})$
Ormerod $d = D {(\frac{H - h}{H - 1.3})}^{a_{1}}$
曾伟生 $d = D {(\frac{H - h}{H - 1.3})}^{k_{1}}$
严若海 $d = a_{1} D {(\frac{H - h}{H - 1.3})}^{k_{2}}$

Table 2. Parameters of the taper equations for Cunninghamia lanceolata
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Table 2. Parameters of the taper equations for Cunninghamia lanceolata
方程提出者方程参数
$a_{1}$ $a_{2}$ $a_{3}$ $a_{4}$ $a_{5}$ $a_{6}$ $a_{7}$ $a_{8}$
Kozak 1.195 -1.394 0.28
Ormerod 0.449
曾伟生 6.250 -13.175 7.829 -0.222
严若海 1.021 3.448 -29.649 122.836 -239.885 221.266 -77.435 -0.226

Table 3. Parameters of the taper equations for Eucalyptus
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Table 3. Parameters of the taper equations for Eucalyptus
方程提出者方程参数
$a_{1}$ $a_{2}$ $a_{3}$ $a_{4}$ $a_{5}$ $a_{6}$ $a_{7}$ $a_{8}$
Kozak 1.048 -1.093 0.12
Ormerod 0.471
曾伟生 3.054 -4.782 2.382 -0.243
严若海 1.01 2.336 -11.652 35.493 -57.906 50.204 -18.065 -0.255

Table 4. Accuracy of taper equations for Cunninghamia lanceolata
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Table 4. Accuracy of taper equations for Cunninghamia lanceolata
方程提出者 $R^{2}$ $R M S E$ /cm $M A E$ /cm $B i a s$ /cm
Kozak 0.88 1.47 1.00 0.20
Ormerod 0.90 1.36 0.15 -0.14
曾伟生 0.92 1.23 0.33 -0.01
严若海 0.93 1.23 0.03 0.43

Table 5. Accuracy of taper equations for Eucalyptus
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Table 5. Accuracy of taper equations for Eucalyptus
方程提出者 $R^{2}$ $R M S E$ /cm $M A E$ /cm $B i a s$ /cm
Kozak 0.87 1.64 0.40 -0.05
Ormerod 0.86 1.71 0.12 0.07
曾伟生 0.92 1.22 0.23 -0.06
严若海 0.92 1.27 0.10 -0.01

Table 6. Volume calculation accuracy of different types of point cloud
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Table 6. Volume calculation accuracy of different types of point cloud
点云类型 $R^{2}$ $R M S E$ /m³
杉木桉树杉木桉树
融合点云 0.96 0.93 0.07 0.07
地基点云 0.94 0.90 0.08 0.08

Table 7. Volume calculation accuracy of different types of plots
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Table 7. Volume calculation accuracy of different types of plots
样地类型 $R^{2}$ $R M S E$ /m³
融合点云地基点云融合点云地基点云
简单样地 0.96 0.95 0.06 0.06
中等样地 0.95 0.93 0.07 0.08
复杂样地 0.92 0.90 0.06 0.07

Table 8. Significance test results of the volume
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Table 8. Significance test results of the volume
材积类型 P值
总体 0.82
杉木 0.98
桉树 0.77
简单样地 0.79
中等样地 0.90
复杂样地 0.65

Table 9. Volume calculation accuracy of fusion point cloud
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Table 9. Volume calculation accuracy of fusion point cloud
样地类型 $R^{2}$ $R M S E$ /m³
杉木桉树杉木桉树
简单样地 0.95 0.94 0.06 0.06
中等样地 0.95 0.95 0.08 0.07
复杂样地 0.75 0.90 0.01 0.07

Table 10. Calculation result of volume

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Table 10. Calculation result of volume

样地号	样地蓄积量/m³		林分蓄积量/（m³/hm²）
样地号	二元材积模型	区分求积	二元材积模型	区分求积
S06	3.28	3.32	82.08	83.03
S09	4.51	4.85	112.79	121.13
AS3	8.66	9.13	216.57	228.20
S07	2.44	2.48	60.97	62.02
AS5	3.56	3.60	88.90	89.94
S03	9.69	10.75	242.37	268.76
S111	6.51	7.10	162.76	177.49
S04	11.75	11.32	293.75	283.00
A02	14.58	16.70	364.53	417.53
AS7	4.84	4.37	120.99	109.29
A21	4.68	4.48	116.91	112.12
AS4	5.73	6.07	143.13	151.75
A06	6.16	5.47	154.05	136.74
AS2	15.80	17.77	394.90	444.23
AS1	14.97	14.53	374.20	363.18

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Junfeng ZHU, Qingwang LIU, Ximin CUI, Wenbo ZHANG. Estimation of Volume based on Fusion Point Cloud of Terrestrial and UAV LiDAR[J]. Remote Sensing Technology and Application, 2024, 39(1): 45

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