e</sub>) 是用于衡量植物對水分需求的一個重要參數(shù),高效、及時地獲取 K<sub>c</sub> 對優(yōu)化灌溉管理,提升農業(yè)用水效率具有重要意義。本研究以冬小麥為研究對象,利用聯(lián)合國糧食及農業(yè)組織(FAO)推薦的雙作物系數(shù)法,并結合觀測得到的冬小麥長勢參數(shù)(株高、葉面積指數(shù)),進行冬小麥作物系數(shù)的估算;同時利用無人機遙感獲取多光譜的冬小麥影像,分析不同時期(拔節(jié)期、抽穗期和開花期)8種常用植被指數(shù)(歸一化植被指數(shù)、重歸一化植被指數(shù)、土壤調節(jié)植被指數(shù)、轉化葉綠素吸收反射指數(shù)、增強型植被指數(shù)、綠色歸一化植被指數(shù)、比值植被指數(shù)、差值植被指數(shù))與FAO推薦方法得到的作物系數(shù)的相關性;根據(jù)決定系數(shù)( ??<sup>2</sup> )選取適宜的植被指數(shù)建立作物系數(shù)估算模型,并與FAO推薦方法估算的作物系數(shù)進行比較。結果表明,拔節(jié)期至開花期,歸一化植被指數(shù)(NDVI)、重歸一化植被指數(shù)(RDVI)、土壤調節(jié)植被指數(shù)(SAVI)和轉化葉綠素吸收反射指數(shù)(TCARI)等4種植被指數(shù)與 K<sub>c</sub> 的相關性較好?;赥CARI/RDVI建立的冬小麥作物系數(shù)估算模型精度更高,拔節(jié)期、抽穗期和開花期估算模型的均方根差(RMSE)分別為0.14、0.12和0.15,拔節(jié)期、抽穗期和開花期的模型性能系數(shù) (EF) 分別為0.66、0.88和0.71。利用估算模型生成的作物系數(shù)分布圖可為冬小麥的合理灌溉提供科學依據(jù)。-龍源期刊網(wǎng)" />

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基于無人機多光譜估算冬小麥作物系數(shù)

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中圖分類號:S127 文獻標識碼:A 文章編號:1000-4440(2025)06-1169-10

Abstract: Crop coefficient( Kc )is a critical parameter for quantifying crop water requirements,and its eficient and timelyacqusitionisssntialforoptimizing irigationmanagementandimprovingagricultural wateruseeficiency.Intisstudy, winterwheatwastakenastheresearchobject,andthecropcoeficientofwinterwheatwasestimatedbyusing thedualcropcoefficientapproachrecommendedbytheFoodandAgricultureOrganizationoftheUnited Nations(FAO),combinedwith theobserved winterwheat growth parameters(plantheight,,leafarea index).Thecorrelationbetweeneightcommonvegetationindices (normalizeddiferencevegetationidex,renormalizeddiferencevegetationindex,soil-adjustedvegetationindex,rasfoed chlorophyllabsorptioinectaceindex,hacedvegetationindex,reennrmalizeddierencevgetatinindex,atiovege

tationindex,differencevegetation index)and Kc derived fromFAO-recommended methodswas analyzed at different growth stages(jointing,heading,and flowering periods) usingmultispectral imageryacquired throughunmannedaerial vehicle(UAV)remote sensing.According to the coefficient of determination (R2), ,the appropriate vegetation index was

selectedto establishthecropcoeffcient estimationmodel.Cropcoeffcientvaluesestimatedbythe model werecomparedwith thoseobtainedbytheFAO-recommendedalgorithm.Theresultsshowedthatthenormalizeddiffrencevegetationindex( NDW ), renormalized difference vegetation index( RDVI ),soil-adjusted vegetation index(SAVI)and transformed chlorophyll absorption in reflectance index ( TCARI )had a good correlation with Kc during jointing stage to flowering stage. The crop coefficient estimation model of winter wheat based on TCARI/RDVI was more accurate. The root mean square errors ( RMSE ) at jointing stage, heading stage and flowering stage were 0.14 ,0.12 and O.15,respectively.The model effciency coefficients( EF )at jointing stage,headingstageandfloweringstage wereO.66,O.88and0.71,respecively.Thecropcoeficient distributionmapgenerated bythismodel can provide a scientific basis for reasonable irrigation of winterwheat.

Key words:winter wheat;unmanned aerial vehicle(UAV);multispectral;crop coeficient;vegetation index

作物蒸散量(ET)包括土壤蒸發(fā)和植被蒸騰,是農田水分消耗的重要途徑,亦是制定合理灌溉制度的基礎[1-2]。(剩余12712字)

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