Wheat yield estimation from UAV platform based on multi-modal remote sensing data fusion

Crop yield estimations are important for national food security, people, and the environment. Timely and accurate estimation of crop yield at the field scale is of great significance for crop management, harvest and trade. It ultimately enables farmers to optimize inputs and economic return. We sele...

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Bibliographic Details
Published inZuo wu xue bao Vol. 48; no. 7; p. 1746
Main Authors Zhang, Shao-Hua, Duan, Jian-Zhao, He, Li, Jing, Yu-Hang, Schulthess, Urs Christoph, Lashkari, Azam, Guo, Tian-Cai, Wang, Yong-Hua, Feng, Wei
Format Journal Article
LanguageChinese
Published Beijing Chinese Academy of Agricultural Sciences (CAAS) 01.01.2022
Subjects
Accuracy
Agricultural production
Cameras
Crop growth
Crop management
Crop yield
Crops
Data integration
Elevation
Flowering
Food security
Information sources
Infrared cameras
Least squares method
Low altitude
Machine learning
Mathematical models
Modal data
Moisture content
Multisensor fusion
Parameters
Regression
Remote sensing
Soil water
Support vector machines
Terrain
Unmanned aerial vehicles
Vegetation
Water content
Wheat
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Summary:Crop yield estimations are important for national food security, people, and the environment. Timely and accurate estimation of crop yield at the field scale is of great significance for crop management, harvest and trade. It ultimately enables farmers to optimize inputs and economic return. We selected an irrigated wheat field in a region near Kaifeng, Henan province, for this study. The terrain in that region is undulating and spatial differences. We used a low-altitude unmanned aerial vehicle (UAV) remote sensing platform equipped with a multi-spectral camera, thermal infrared camera, and RGB camera to simultaneously obtain different remote sensing parameters during the key growth stages of wheat. Based on the extracted spectral reflectivity, thermal infrared temperature, and digital elevation information, we calculated the spatial variability of remote sensing parameters, and growth indices under different terrain characteristics. We also analyzed the correlations between vegetation indices, temperature p
ISSN:0496-3490
DOI:10.3724/SP.J.1006.2022.11053