Large-scale wheat lodging monitoring by band transformation of UAV and sentinel-2A multispectral imageryOA
Lodging negatively affects wheat yield and quality.Large-scale remote sensing monitoring of wheat lodging is significant for rapidly assessing the impacts of agricultural disasters and formulating precise management strategies.Large-scale remote sensing of wheat lodging requires sufficient in-situ samples,which are faced with the challenges of high cost,low efficiency,and poor real-time performance.This study proposes a method integrating unmanned aerial vehicle(UAV)and satellite(Sentinel-2A)multispectral imagery to achieve low-cost and efficient wheat lodging monitoring.By applying a multilayer perceptron(MLP)algorithm for band transformation,a wheat lodging ratio(WLR)estimation model was constructed based on high-precision UAV data and migrated to satellite data.This model was used to map the distribution of wheat lodging in Henan Province,China.The MLP algorithm achieved high accuracy and stability in band transformation between UAV and Sentinel-2A imagery,with R2 values>0.97 and RMSE values<0.015.The SPA_XGBoost model delivered the optimal performance in UAV-based WLR monitoring,with a testing set R2 of 0.8675,RMSE of 0.0732,and NRMSE of 12.13%.When applied to satellite imagery for WLR monitoring,the model yielded validation accuracies of R2=0.8458,RMSE=0.0985,and NRMSE=11.24%.In addition,UAV imagery was used to generate high-accuracy reference data,thereby laying a robust foundation for model construction and transfer.This study significantly reduced the time and economic costs of acquiring ground-truth samples and offered an effective solution for large-scale remote sensing of crop lodging that balances accuracy and scale.
Baoyuan Zhang;Meiyan Shu;Xiaoyuan Bao;Menglei Dai;Qian Sun;Xuguang Sun;Mingzheng Zhang;Ying Ren;Zongpeng Li;Ya’nan Tian;Xia Yao;Xiaohe Gu
College of Agriculture,Nanjing Agricultural University,Nanjing 211512,China Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,ChinaCollege of Information and Management Science,Henan Agricultural University,Zhengzhou 450002,ChinaState Key Laboratory of Aridland Crop Science,Gansu Agricultural University,Lanzhou 730070,ChinaInformation Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,ChinaJiangsu Co-Innovation Center for Modern Production Technology of Grain Crops,Yangzhou University,Yangzhou 225009,ChinaInformation Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,ChinaInformation Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,ChinaInformation Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,ChinaInstitute of Farmland Irrigation,Chinese Academy of Agricultural Sciences,Xinxiang 453002,ChinaInformation Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,ChinaCollege of Agriculture,Nanjing Agricultural University,Nanjing 211512,ChinaInformation Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China
农业科技
Wheat lodgingBands transformationMultilayer perceptronUAVSentinel-2A
《Information Processing in Agriculture》 2026 (1)
P.15-25,11
supported by the Henan Province Science and Technology Research Project(242102110357)the National Natural Science Foundation of China(42271319)the National Funded Postdoctoral Researcher Program(GZC202307)the Jiangsu Province Graduate Research and Practice Innovation Program Project(KYCX25_0980).
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