基于无人机多光谱遥感和机器学习的棉花SPAD值预测
Prediction of SPAD value of cotton based on UAV multispectral remote sensing and machine learning
摘要
Abstract
[Objective]Cotton is an important economic crop in Xinjiang,so obtaining cotton chlorophyll content(SPAD value)quickly and accurately on the field scale is of great significance for accurate monitoring of cotton growth status and improving cotton yield and quality prediction.In this study,multi-spectral remote sensing technology combined with machine learning method was used to retrieve the SPAD value of cotton in Aksu area.A feasible method for large area estimation of SPAD value of cotton in the field,and provides an important reference for non-destructive and real-time monitoring of crop growth index.[Methods]The split zone design was used in the experiment,three nitrogen application levels and three irrigation quotas were selected.Firstly,the response law of SPAD value of cotton under different water and nitrogen treatments was analyzed.Then the spectral characteristics of cotton multispectral images in different periods were further ana-lyzed and the vegetation index was constructed.The correlation between vegetation index and SPAD value was analyzed,and the vegetation index with high correlation was selected.Four machine learning algorithms were used to model and analyze the SPAD value and multi-spectral index of the whole growth period of experiment 1 and experiment 2,and the optimal monitoring model was selected.The SPAD value of cotton in different pe-riods were predicted and inversed,and the model was verified by different field data.[Results]The SPAD value of cotton was estimated by UAV multispectral images and machine learning algorithm,and it was found that different growth periods were significantly affected by irrigation and fertilization conditions.The better esti-mation accuracy was obtained by screening the appropriate spectral index and modeling with the random forest model,and the estimation result of the model was the best at the flowering and boll stage,and the estimation progress R2of the model was between 0.68 and 0.73.The RF model had good stability in estimating the SPAD value of leaves among different fields.[Conclusion]The estimation of SPAD value of cotton leaves by RF al-gorithm based on UAV multispectral image calculation has good accuracy and stability.关键词
无人机多光谱/棉花/SPAD值/机器学习/随机森林Key words
UAV multispectral/cotton/SPAD value/machine learning/random forest分类
农业科技引用本文复制引用
方万成,汤秋香,林涛,崔建平,贾涛,鲍龙龙,王亮,樊世语,胡正东,邵亚杰..基于无人机多光谱遥感和机器学习的棉花SPAD值预测[J].新疆农业科学,2025,62(5):1041-1050,10.基金项目
国家自然科学基金项目(32260542) （32260542）
新疆农业科学院农业科技创新稳定支持专项(xjnkywdzc-2023007) （xjnkywdzc-2023007）
新疆维吾尔自治区重大科技专项(2020A01002-4-4) （2020A01002-4-4）
新疆维吾尔自治区重点研发专项(2022B02033-1) （2022B02033-1）
新疆维吾尔自治区重大科技专项(2022A02011-2-1) （2022A02011-2-1）
数字棉花科技创新平台建设项目 （）
新疆农业科学院自主培育专项(xjnkyzzp-2022002) （xjnkyzzp-2022002）
"天山英才"培养计划"棉花轻简高效栽培技术创新团队"(2023TSYCTD004) the Project of National Natural Science Foundation of China(32260542) （2023TSYCTD004）
the Agricultural S & T Innovation and Stability Support Special Project of Xinjiang Academy of Agricultural Sciences(xjnkywdzc-2023007) （xjnkywdzc-2023007）
the Major Scientific R & D Program Projects of Xinjiang Uygur Autonomous Region(2020A01002-4-4,2022B02033-1,2022A02011-2-1) （2020A01002-4-4,2022B02033-1,2022A02011-2-1）
Digital Cotton Technology Innovation Platform Construction Project （）
Autonomous Cultivation Project of Xinjiang Academy of Agricultural Sciences(xjnkyzzp-2022002) （xjnkyzzp-2022002）
"Tianshan Talent"Training Program Project"Cotton Light,Simple and Efficient Cultivation Technology Innovation Team"(2023TSYCTD004) （2023TSYCTD004）
