Smart Agriculture ›› 2022, Vol. 4 ›› Issue (1): 71-83.doi: 10.12133/j.smartag.SA202202004
• Topic--Crop Growth and Its Environmental Monitoring • Previous Articles Next Articles
DAI Mian1,2(), YANG Tianle1,2, YAO Zhaosheng1,2, LIU Tao1,2, SUN Chengming1,2(
)
Received:
2021-07-26
Online:
2022-03-30
Published:
2022-04-28
corresponding author:
SUN Chengming
E-mail:996982850@qq.com;cmsun@yzu.edu.cn
About author:
DAI Mian (1998-), female, postgraduate, research interest: intelligent monitoring of crop growth. E-mail: Supported by:
CLC Number:
DAI Mian, YANG Tianle, YAO Zhaosheng, LIU Tao, SUN Chengming. Wheat Biomass Estimation in Different Growth Stages Based on Color and Texture Features of UAV Images[J]. Smart Agriculture, 2022, 4(1): 71-83.
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URL: http://www.smartag.net.cn/EN/10.12133/j.smartag.SA202202004
Table 1
Algorithms of color indices
Index | Abbreviation | Computational formula |
---|---|---|
Visible Atmospheric Resistance Vegetation Index | VARI | |
Excess Red Vegetation Index | ExR | ExR= |
Excess Green Vegetation Index | ExG | ExG= |
Green Leaf Vegetation Index | GLI | GLI= |
Excess Green-Red Difference Index | ExGR | ExGR =ExG |
Normalized Difference Index | NDI | NDI= |
Modified Green Red Vegetation Index | MGRVI | MGRVI= |
Red Green Blue Vegetation Index | RGBVI | RGBVI= |
Table 3
Correlations between different color indices and wheat biomass based on UAV image (n=24)
Growth stage | ExG | VDI | ExR | ExGR | VARI | GLI | MGRVI | RGBVI |
---|---|---|---|---|---|---|---|---|
Pre-wintering stage | 0.594** | 0.458* | -0.619** | 0.678** | 0.743** | 0.657** | 0.706** | 0.598** |
Jointing stage | 0.813** | 0.823** | -0.824** | 0.911** | 0.817** | 0.809** | 0.687** | 0.625** |
Booting stage | 0.493* | 0.793** | -0.779** | 0.607** | 0.734** | 0.483* | 0.817** | 0.351 |
Flowering stage | 0.367 | 0.540** | -0.652** | 0.463* | 0.679** | 0.369 | 0.540** | 0.316 |
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