中国农业气象2026，Vol.47Issue(1)：63-72,10.DOI:10.3969/j.issn.1000-6362.2026.01.006
基于无人机多光谱遥感的农田土壤含水量反演
Inversion of Soil Water Content in Farmland Based on Multispectral Remote Sensing of UAV
摘要
Abstract
The inversion of the fine spatial distribution of soil water content in the seedling stage of winter wheat based on multispectral remote sensing of UAV can be used as a reference to plan irrigation in agricultural and improve irrigation efficiency.This study took the soil water content in the top layer(5cm)of winter wheat seedlings in Zhengzhou and Xinxiang as the inversion object,based on multispectral data from drones,selected the optimal spectral features,compared and validated the simulation results of random forest(RF)and gradient boosting(GB)machine learning models,and performed grid inversion of soil water content in the experimental area based on the optimal model.The results showed that the GB and RF models had a better inversion effects on the topsoil water content in Zhengzhou and Xinxiang during the wheat seedling stage,with R2 and nRMSE ranging from 0.926 to 0.983 and 5.6%to 14.4%,respectively.The modeling accuracy of GB and RF based on the aggregated data from both sites was good,with R2 and nRMSE of 0.902,0.787 and 6.9%,10.2%,respectively.The simulation results of the GB model were better than the RF model.The spatial accuracy of soil water inversion during the winter wheat seedling stage was 2cm,which better revealed the spatial heterogeneity of soil water in farmland.Both models performed well for different underlying surfaces and weather conditions and had high model generalization.The results can provide theoretical and technical support for accurate inversion of the water content of farmland soil using multi-spectral remote sensing from UAVs,which can benefit the development of precision agriculture and smart agriculture.关键词
土壤含水量/无人机/多光谱/机器学习Key words
Soil water content/UAV/Multispectral/Machine learning引用本文复制引用
叶昊天,姬兴杰..基于无人机多光谱遥感的农田土壤含水量反演[J].中国农业气象,2026,47(1):63-72,10.基金项目
国家重点研发计划项目(2022YFD2300202) （2022YFD2300202）
河南省科技攻关项目(242102321019) （242102321019）
中国气象局·河南省农业气象保障与应用技术重点开放实验室项目(AMF202602) （AMF202602）
