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Spectroscopy and Spectral Analysis, Volume. 41, Issue 12, 3828(2021)

Inversion of Wheat Tiller Density Based on Visible-Band Images of Drone

Meng-meng DU1、*, Roshanianfard Ali2、2;, Ying-chao LIU3、3;, and [in Chinese]2、2;
Author Affiliations
  • 11. School of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China
  • 22. Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, 56199-11367, Ardabil, Iran
  • 33. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
    Equations (0)
    References (8)
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    Paper Information
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    Figures & Tables(11)
    Study area and positions of ground truths of wheat tiller density(a): Experimental field; (b): Experimental field and positions of ground truths of wheat tiller density;(c) Counting wheat tiller numbers within the zone of “1 meter and 2 rows”

    Fig. 1. Study area and positions of ground truths of wheat tiller density
    (a): Experimental field; (b): Experimental field and positions of ground truths of wheat tiller density;(c) Counting wheat tiller numbers within the zone of “1 meter and 2 rows”

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    Calibrated drone remote sensing images of blue, green and red bands(a): Blue band; (b): Green band; (c): Red band

    Fig. 2. Calibrated drone remote sensing images of blue, green and red bands
    (a): Blue band; (b): Green band; (c): Red band

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    Spectral response characteristics of vegetation and soil in visible light domain

    Fig. 3. Spectral response characteristics of vegetation and soil in visible light domain

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    Training model of BP neural network

    Fig. 4. Training model of BP neural network

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    Vegetation index maps

    Fig. 5. Vegetation index maps

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    Training result of BP neural network model

    Fig. 6. Training result of BP neural network model

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    Map of quantitatively inversed wheat tiller density at field level

    Fig. 7. Map of quantitatively inversed wheat tiller density at field level

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    • Table 1. Experiment equipment

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      Table 1. Experiment equipment

      项目值
      大疆Mini 2
      无人机      		外形尺寸/mm245×289×56
      净重/g249
      最大爬升速度/(m·s-1)5
      最大水平飞行速度/(m·s-1)16
      相机模块视角/(°)83
      传感器类别CMOS
      有效像素3 000×4 000
      等效焦距/mm24
      图片格式JPEG/DNG (RAW)

    • Table 2. Ground truths of wheat tiller density and corresponding VI values

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      Table 2. Ground truths of wheat tiller density and corresponding VI values

      序号“1米双行”
      小麦茎蘖数      		小麦茎蘖密度地面
      真值/(s·m-2)      		FVC
      平均值      		VDVI
      平均值      		NGRDI
      平均值      		NGBDI
      平均值      		RGRI
      平均值
      11386900.4830.1520.0750.2421.166
      21738650.5710.1930.1150.2831.269
      31376850.4720.1470.0680.2381.150
      41537650.5010.160.0820.2521.184
      51366800.4750.1490.0720.2371.168
      61266300.4670.1450.0650.2391.140
      71457250.4980.1590.0820.2481.185
      81165800.4300.1280.0480.2221.103
      9914550.4020.1150.0390.2031.086
      101628100.5180.1680.0860.2641.191
      111025100.4220.1240.0450.2171.098
      121638150.5400.1780.0980.2721.220
      131055250.4220.1240.0460.2161.099
      141105500.4330.1290.050.2221.111
      151487400.5180.1680.0880.2631.199
      16944700.4930.1570.0780.2491.173
      17894450.4180.1230.0440.2141.094
      18854250.4560.1400.0580.2371.129
      191708500.5420.1790.1020.2681.234
      20974850.4810.1510.0720.2431.161

    • Table 3. Statistic values of vegetation and soil in FVC, VDVI, NGRDI, NGBDI and RGRI maps

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      Table 3. Statistic values of vegetation and soil in FVC, VDVI, NGRDI, NGBDI and RGRI maps

      VI植被土壤
      最大值最小值均值标准差最大值最小值均值标准差
      FVC0.8510.6870.7700.0520.1840.1330.1580.016
      VDVI0.5440.3010.3890.071-0.013-0.256-0.0690.089
      NGRDI0.2500.1670.2040.026-0.035-0.073-0.0470.011
      NGBDI0.4740.3230.3750.0430.0720.0460.0590.008
      RGRI1.6671.4001.5160.0830.9320.8630.9110.020

    • Table 4. Ground truths and prediced values of wheat tiller density

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      Table 4. Ground truths and prediced values of wheat tiller density

      序号小麦茎蘖密度地面真值
      /(株·m-2)      		小麦茎蘖密度预测值
      /(株·m-2)
      1470455
      2445455
      3425455
      4850865
      5485465
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    Meng-meng DU, Roshanianfard Ali, Ying-chao LIU, [in Chinese]. Inversion of Wheat Tiller Density Based on Visible-Band Images of Drone[J]. Spectroscopy and Spectral Analysis, 2021, 41(12): 3828

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    Paper Information

    Category: Research Articles

    Received: Mar. 14, 2021

    Accepted: --

    Published Online: Dec. 17, 2021

    The Author Email: Meng-meng DU (dualmon.du@haust.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2021)12-3828-09

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology