Maize biomass estimation by integrating spectral, structural, and textural features from unmanned aerial vehicle data

• Published in: European journal of agronomy Vol. 168; p. 127647
• Main Authors: Meng, Lin, Ming, Bo, Liu, Yuan, Nie, Chenwei, Fang, Liang, Zhou, Lili, Xin, Jiangfeng, Xue, Beibei, Liang, Zhongyu, Guo, Huirong, Yin, Dameng, Jin, Xiuliang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2025
• Subjects: aboveground biomass; Aboveground biomass (AGB); agronomy; algorithms; cameras; canopy; corn; data collection; ears; Ensemble learning; leaves; lidar; Maize; Organ biomass; precision agriculture; texture; Unmanned Aerial Vehicle (UAV); unmanned aerial vehicles; vegetation; Unmanned Aerial Vehicle (UAV); Maize; Organ biomass; Ensemble learning; Aboveground biomass (AGB)

The rapid and accurate estimation of maize aboveground biomass (AGB) and organ biomass at the field scale is crucial for monitoring crop growth and predicting yield. However, there is limited research on estimating crop organ biomass from unmanned aerial vehicle (UAV) remote sensing. This study used...