Estimation of the height and above-ground biomass of winter wheat based on DOM and DSM of UAV images

Y. Guo; Y.H. Jing; J. He; Y. S. Rong; L. G. Wang; W. Feng; Y. Z. Cheng; T. Liu; G. Q. Zheng

doi:10.1117/12.2634386

12 May 2022 Estimation of the height and above-ground biomass of winter wheat based on DOM and DSM of UAV images

Y. Guo, Y.H. Jing, J. He, Y. S. Rong, L. G. Wang, W. Feng, Y. Z. Cheng, T. Liu, G. Q. Zheng

Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121730Z (2022) https://doi.org/10.1117/12.2634386
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China

Abstract

The height (H) and above-ground biomass (AGB), as important phenotypic parameters, are important guides for growth monitoring and genetic improvement of winter wheat. In this study, digital orthophoto map (DOM) and digital surface model (DSM) of winter wheat at the filling stage were obtained based on different water and nitrogen treatments, using a UAV-mounted multispectral imager. Then a model was established for estimating height and biomass using the partial least squares method. The results showed that (1) at the same nitrogen application level, when each sample in various nitrogen levels was modeled separately, the model for estimating height established by N0 and N6 was better, with R² of 0.773 and 0.592, respectively; when all samples were modeled together, the R² was 0.831, which was better than the former. (2) The model of the relationship between height and measured biomass extracted by UAV under different nitrogen levels was robust, and the estimated model R² and RMSE were 0.598 and 4308.99 kg/ha, and the validated model R² and RMSE were 0.507 and 4939.31 kg/ha. (3) The R² and RMSE of the model using biomass per unit plant height with measured biomass were 0.881 and 2335.46 kg/ha, and the R² and RMSE of the transformed biomass estimation model were 0.876 and 2425.39 kg/ha, which improved the accuracy by 72.7% compared with the estimation model built by directly extracting the height using UAV. This indicates that DSM can accurately estimate the height and biomass of winter wheat, providing a reference for phenotypic studies as well as water and nitrogen management of winter wheat.

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Y. Guo, Y.H. Jing, J. He, Y. S. Rong, L. G. Wang, W. Feng, Y. Z. Cheng, T. Liu, and G. Q. Zheng "Estimation of the height and above-ground biomass of winter wheat based on DOM and DSM of UAV images", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121730Z (12 May 2022); https://doi.org/10.1117/12.2634386

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KEYWORDS

Unmanned aerial vehicles

Statistical modeling

Nitrogen

RGB color model

Agriculture

Data modeling

Statistical analysis

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