基于無人機多光譜圖像的小麥葉片氮含量遙感監(jiān)測研究

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關鍵詞無人機；多光譜圖像；小麥葉片氮含量；監(jiān)測模型

中圖分類號S127文獻標識碼A

文章編號 0517-6611（2025）08-0243-05

doi：10.3969/j.issn.0517-6611.2025.08.049

開放科學（資源服務）標識碼（OSID）：

AbstractToacheeprecise，eient，dynamicandlow-ostirogenutrientmoitingincoprductioandpromoteteapiddance mentofnew-ualitgiulturalproductivityTsudyassdothexperenllyeasueddatain24adtokmadal cle（UAV）imagesasthedatasourcetoanalyzethe modelsbetwenthemainremotesensingparametersandleaf nitrogencontent（LNC）of weatatthejoitigsageandotigsage.TeresultsohatitieasibletmoiratLCattejtigstageandotigsagby usingthe normalizedgree-bluedierenceindex（NBD）ed-gen-buevegetationidex（RGBV）andRGBVIexcessrdE）ote sensingvariablsspetivelyOntissis，saiallstributedasofofatattejtigsagendotingageodby UAVremotesensigwithpracticalignificaneerefabricatedThresearchfidingscanprovidchncalsuportforagiculturalmangt departments to obtain reliable agricultural condition information and formulate precise fertilization management.

Key wordsUAV；Multispectral image； Wheat leaf nitrogen content；Monitoring model

小麥是江蘇省最主要的大田作物，已成為全國重要的小麥主產(chǎn)區(qū)，對國家糧油安全具有重要意義。（剩余5646字）