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Measurement of nitrogen content in rice by inversion of hyperspectral reflectance data from an unmanned aerial vehicle Ciência Rural
Wen,Du; Tongyu,Xu; Fenghua,Yu; Chunling,Chen.
ABSTRACT: The Nitrogen content of rice leaves has a significant effect on growth quality and crop yield. We proposed and demonstrated a non-invasive method for the quantitative inversion of rice nitrogen content based on hyperspectral remote sensing data collected by an unmanned aerial vehicle (UAV). Rice canopy albedo images were acquired by a hyperspectral imager onboard an M600-UAV platform. The radiation calibration method was then used to process these data and the reflectance of canopy leaves was acquired. Experimental validation was conducted using the rice field of Shenyang Agricultural University, which was classified into 4 fertilizer levels: zero nitrogen, low nitrogen, normal nitrogen, and high nitrogen. Gaussian process regression (GPR) was...
Tipo: Info:eu-repo/semantics/article Palavras-chave: UAV; Hyperspectral remote sensing; Machine learning; Nitrogen content.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000600352
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