Scientia Agricultura Sinica ›› 2019, Vol. 52 ›› Issue (24): 4493-4504.doi: 10.3864/j.issn.0578-1752.2019.24.005

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Real-Time Estimation of Citrus Canopy Volume Based on Laser Scanner and Irregular Triangular Prism Module Method

Peng LI1,Ming ZHANG1,2,XiangSheng DAI3,Teng WANG1,YongQiang ZHENG1,ShiLai YI1,Qiang LÜ1()   

  1. 1 Citrus Research Institute, Southwest University, Chongqing 400712
    2 College of Engineering and Technology, Southwest University, Chongqing 400716
    3 Jinggang Honey Pomelo Research Institute, Jinggangshan Agricultural Science and Technology Park, Ji’an 343016, Jiangxi
  • Received:2019-04-23 Accepted:2019-07-03 Online:2019-12-16 Published:2020-01-15
  • Contact: Qiang Lü E-mail:qlu@swu.edu.cn

Abstract:

【Objective】Accurate measurement of volume and structure of fruit tree canopy can provide important reference for variable application of pesticide and fertilizer, as well as yield estimation. In order to accurately measure the canopy volume, a scanning platform based on laser sensor (LMS111-10100, SICK) was built. Aiming at the problem of irregular canopy shape, the poor accuracy of the existing real-time measurement methods of canopy volume and difficult to measure and estimate the canopy volume, a new estimation method based on irregular triangular prism modules was proposed in this work. 【Method】Five spherical landscape trees with regular canopy and ten citrus trees with irregular canopy were scanned by the laser sensor at the speeds of 0.5, 1.0 and 1.5 m·s -1, respectively. The canopy volume was measured by two methods: cuboid module method (CMM) and irregular triangular prism module method (ITPMM), and the error analysis was conducted based on manual measurement. 【Result】 The results showed that the error ranges of CMM for measuring landscape trees at the different speeds of 0.5, 1.0 and 1.5 m·s -1were 4.17%-6.59%, 4.56%-7.42% and 4.17%-9.86%, respectively, while the error ranges of the ITPMM for measuring landscape trees were 2.37%-4.63%, 3.18%-5.00% and 4.10%-5.73%, respectively. The distance range of the relative error of the two methods for measuring citrus trees was -0.28%-4.22%%, and the average difference was 1.78%. The error ranges of CMM for measuring citrus trees at the different speeds of 0.5, 1.0 and 1.5 m·s -1 were 11.63%-31.02%, 11.88%-33.23% and 13.28%-33.30%, respectively. The error ranges by ITPMM for measuring citrus trees were 3.25%-6.69%, 4.50%-8.31% and 5.66%-11.55%, respectively. The distance range of the relative error of the two methods for measuring citrus trees was 6.43%-26.20%, and the average difference was 13.04%. 【Conclusion】 The research showed that the estimation error of the ITPMM was significantly smaller than the CMM. For the same target, when the speed was 0.5 m·s -1, both of the estimation accuracy for the two methods were the highest. As the sensor speed increased, laser scanning points on the canopy decreased. So, the relative error of volume estimation increased with increase of advance speed of the laser sensor. When scanning the regular target, the accuracy difference between the two methods was small; when scanning the irregular target, the error of the CMM was larger. The processing time of a frame laser data by the CMM was 2.86 ms, and the processing time by the ITPMM was 4.73 ms, which were less than the scanning period of 20 ms of the laser sensor. The data processing time could match the acquirement of real-time collection and processing of laser data.

Key words: canopy volume, laser scanning, irregular triangular prism module method, real-time detection, trunk recognition

Fig. 1

Technology roadmap"

Fig. 2

Schematic diagram of scanning tree by laser sensor 1: Servo motor; 2: Sliding guide; 3: Supporting frames; 4: Laser sensor; 5: Laptop; 6: Motor driver"

Fig. 3

Schematic diagram of citrus tree trunk recognition"

Fig. 4

Schematic diagram of the cuboid module method"

Fig. 5

Schematic diagram of the principle of the triangular prism module method"

Fig. 6

Schematic diagram of manual measurement of canopy volume"

Fig. 7

Color images, laser point cloud images and depth images of landscape tree and citrus tree (a) Landscape tree; (b) Citrus tree; (c) Laser point cloud image of landscape tree; (d) Laser point cloud image of citrus tree; (e) Depth image of landscape tree; (f) Depth image of citrus tree"

Table 1

Estimation results of canopy volume of landscape trees using two methods"

植株序号
No.
速度
Speed (m·s-1)
测量体积
Measured volume (m3)
长方体分割法
Cuboid module method
不规则三棱柱分割法
Irregular triangular prism module method
相对误差差值
The distance range of the relative errors
计算体积
Estimated volume (m3)
相对误差
Relative error
计算体积
Estimated volume (m3)
相对误差
Relative error
1 0.50 3.052 2.897 5.08% 2.971 2.65% 2.42%
1.00 2.878 5.70% 2.955 3.18% 2.52%
1.50 2.873 5.87% 2.927 4.10% 1.77%
2 0.50 3.247 3.033 6.59% 3.170 2.37% 4.22%
1.00 3.006 7.42% 3.113 4.13% 3.30%
1.50 2.927 9.86% 3.061 5.73% 4.13%
3 0.50 5.075 4.837 4.69% 4.917 3.11% 1.58%
1.00 4.777 5.87% 4.906 3.33% 2.54%
1.50 4.813 5.16% 4.839 4.65% 0.51%
4 0.50 3.740 3.533 5.53% 3.567 4.63% 0.91%
1.00 3.531 5.59% 3.553 5.00% 0.59%
1.50 3.529 5.64% 3.574 4.44% 1.20%
5 0.50 2.852 2.733 4.17% 2.755 3.40% 0.77%
1.00 2.722 4.56% 2.737 4.03% 0.53%
1.50 2.733 4.17% 2.725 4.45% -0.28%

Fig. 8

Relative error histogram of canopy volume measurement of spherical landscape trees by two methods at different advance speeds of laser sensor"

Table 2

Estimation results of citrus canopy volumes using two methods"

植株序号
No.
速度
Speed (m·s-1)
测量体积
Measured volume (m3)
长方体分割法
Cuboid module method
不规则三棱柱分割法
Irregular triangular prism module method
相对误差差值
The distance range of the relative errors
计算体积
Estimated volume (m3)
相对误差
Relative error
计算体积
Estimated volume (m3)
相对误差
Relative error
1 0.50 3.082 2.569 16.65% 2.918 5.32% 11.32%
1.00 2.513 18.46% 2.826 8.31% 10.16%
1.50 2.466 19.99% 2.771 10.09% 9.90%
2 0.50 7.351 5.071 31.02% 6.997 4.82% 26.20%
1.00 4.908 33.23% 6.797 7.54% 25.70%
1.50 4.903 33.30% 6.502 11.55% 21.75%
3 0.50 2.490 2.172 12.77% 2.409 3.25% 9.52%
1.00 2.168 12.93% 2.378 4.50% 8.43%
1.50 2.141 14.02% 2.349 5.66% 8.35%
4 0.50 2.425 2.143 11.63% 2.313 4.62% 7.01%
1.00 2.137 11.88% 2.293 5.44% 6.43%
1.50 2.103 13.28% 2.269 6.43% 6.85%
5 0.50 4.148 3.212 22.57% 3.922 5.45% 17.12%
1.00 3.029 26.98% 3.823 7.84% 19.14%
1.50 3.085 25.63% 3.795 8.51% 17.12%
6 0.50 2.483 2.035 18.04% 2.317 6.69% 11.36%
1.00 2.035 18.04% 2.310 6.97% 11.08%
1.50 2.025 18.45% 2.240 9.79% 8.66%
7 0.50 3.776 3.113 17.56% 3.552 5.93% 11.63%
1.00 3.069 18.72% 3.475 7.97% 10.75%
1.50 2.988 20.87% 3.357 11.10% 9.77%
8 0.50 5.321 3.836 27.91% 4.994 6.15% 21.76%
1.00 3.771 29.13% 4.931 7.33% 21.80%
1.50 3.750 29.52% 4.919 7.55% 21.97%
9 0.50 4.252 3.572 15.99% 4.007 5.76% 10.23%
1.00 3.577 15.87% 3.967 6.70% 9.17%
1.50 3.446 18.96% 3.846 9.55% 9.41%
10 0.50 3.647 3.115 14.59% 3.497 4.11% 10.47%
1.00 3.045 16.51% 3.379 7.35% 9.16%
1.50 2.993 17.93% 3.319 8.99% 8.94%

Fig. 9

Relative error histogram of canopy volume measurement of citrus trees by two methods at different advance velocities of laser sensor"

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