本文選題：農(nóng)作物　切入點(diǎn)：冬小麥　出處：《植物營(yíng)養(yǎng)與肥料學(xué)報(bào)》2017年02期 　論文類型：期刊論文

【摘要】：【目的】高光譜遙感能快速、實(shí)時(shí)、無(wú)損監(jiān)測(cè)作物長(zhǎng)勢(shì)。研究不同氮磷水平下冬小麥不同生育時(shí)期地上部生物量高光譜遙感監(jiān)測(cè)模型,可提高地上部生物量高光譜監(jiān)測(cè)精度�！痉椒ā吭谖鞅鞭r(nóng)林科技大學(xué)連續(xù)進(jìn)行了5年田間定位試驗(yàn),設(shè)置5個(gè)施氮水平(N,0,75,150,225和300 kg/hm~2)和4個(gè)磷施用水平(P2O5,0,60,120和180 kg/hm~2),選用不同抗旱類型冬小麥品種,測(cè)定了從拔節(jié)期至成熟期生物量與冠層光譜反射率,通過(guò)相關(guān)分析、回歸分析等統(tǒng)計(jì)方法,建立并篩選基于不同植被指數(shù)的冬小麥不同生育時(shí)期生物量分段遙感監(jiān)測(cè)模型�！窘Y(jié)果】冬小麥生物量與光譜反射率在670 nm和930 nm附近具有較高相關(guān)性,在可見(jiàn)光和近紅外波段處均有敏感波段;在拔節(jié)期、孕穗期、抽穗期、灌漿期、成熟期,生物量與歸一化綠波段差值植被指數(shù)(GNDVI)、比值植被指數(shù)(RVI)、修正土壤調(diào)節(jié)植被指數(shù)(MSAVI)、紅邊三角植被指數(shù)(RTVI)和修正三角植被指數(shù)Ⅱ(MTVIⅡ)均達(dá)極顯著相關(guān)性(P0.01),相關(guān)系數(shù)(r)范圍為0.923~0.979;在不同生育時(shí)期,分別基于GNDVI、RVI、MSAVI、RTVI和MTVIⅡ能建立較好的生物量分段監(jiān)測(cè)模型,決定系數(shù)(R2)分別為0.987、0.982、0.981、0.985、0.976;估計(jì)標(biāo)準(zhǔn)誤差SE分別為0.157、0.153、0.163、0.133、0.132;預(yù)測(cè)值與實(shí)測(cè)值間相對(duì)誤差(RE)分別為8.47%、7.12%、7.56%、8.21%、8.65%;均方根誤差(RMSE),分別為0.141 kg/m~2、0.113kg/m~2、0.137 kg/m~2、0.176 kg/m~2、0.187 kg/m~2�！窘Y(jié)論】在拔節(jié)期、孕穗期、抽穗期、灌漿期、成熟期可以用GNDVI、RVI、MSAVI、RTVI和MTVIⅡ監(jiān)測(cè)冬小麥生物量,具有較好的年度間重演性和品種間適用性。同時(shí),分段監(jiān)測(cè)模型較統(tǒng)一監(jiān)測(cè)模型具有較好的監(jiān)測(cè)效果及驗(yàn)證效果,能有效改善高光譜遙感監(jiān)測(cè)模型精度。
[Abstract]:[objective] Hyperspectral remote sensing can be used to monitor crop growth quickly, in real time and without damage. The hyperspectral remote sensing monitoring model of aboveground biomass of winter wheat at different growth and growth stages was studied under different nitrogen and phosphorus levels. The accuracy of hyperspectral monitoring of aboveground biomass could be improved. [methods] the field positioning experiment was carried out in Northwest University of Agriculture and Forestry Science and Technology for 5 years. The biomass and canopy spectral reflectance of winter wheat varieties with different drought resistance types were measured from jointing stage to maturity stage. Regression analysis and other statistical methods were used to establish and screen segmental remote sensing monitoring models of winter wheat biomass at different growth stages based on different vegetation indices. [results] there was a high correlation between biomass and spectral reflectance near 670 nm and 930 nm. There were sensitive bands in both visible and near infrared bands, at jointing stage, booting stage, heading stage, grain filling stage, mature stage, Biomass and normalized green band difference vegetation index (GNDVI), ratio vegetation index (RVI), modified soil adjustment vegetation index (MSAVI), red triangulation vegetation index (RTVI) and modified triangular vegetation index 鈪，

本文編號(hào)：1619203