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HYPERSPECTRAL ANALYSIS OF RICE PHENOLOGICAL STAGES IN NORTHEAST CHINA

机译:东北地区稻纯度阶段的高光谱分析

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The objective of this contribution is to monitor rice (Oryza sativa L., irrigated lowland rice) growth with multitemporal hyperspectral data during different phenological stages in Northeast China (Sanjiang Plain). Multitemporal hyperspectral data were measured with field spectroradiometers (ASD Inc.: QualitySpec and FieldSpec3) for two field experiments and nine farmers' fields. The field measurements were carried out together with corresponding measurements of agronomic data (aboveground biomass [AGB], Leaf Area Index [LAI], number of tillers). Eight selected standard hyperspectral vegetation indices (VIs), proved in several studies to be highly correlated with AGB or LAI, were calculated on the measured experimental field data. Additionally, the best two-band combinations for the Normalized Ratio Index (NRI) were determined. The results indicate that the NRI performed better than the selected standard VIs at the stages of stem elongation, booting and heading and also across all stages. Especially during the stem elongation stage (R~(2) = 0.76) and across all stages (R~(2) = 0.70), the NRI performed best. When applying the NRI on the farmers' field data, the performance was lower (R~(2) < 0.60). Overall, the sensitive individual wavelengths (±10 nm) for the best two-band combinations were detected at 711 and 799 nm (for tillering stage), 1575 and 1678 nm (for stem elongation stage), 515 and 695 nm (for booting stage), and 533 and 713 nm (for all stages). The results suggest that hyperspectral-based methods can estimate paddy rice AGB with a satisfying accuracy. In the context of precision agriculture, the findings are useful for future development of new hyperspectral devices such as scanners or cameras which could be fixed on tractors or unmanned aerial vehicles (UAVs).
机译:这种贡献的目的是监测水稻(Oryza sativa L.,灌溉低地米)对于在中国东北地区(三江平原)不同生育期多时高光谱数据的增长。用字段光谱仪(ASD Inc .:的QualitySpec和FieldSpec3)为两个场实验和九个农田测量多时高光谱数据。实地测量用农学数据的对应测量(地上生物量[AGB],叶面积指数[LAI],数分蘖)一起进行。八个选择标准高光谱植被指数(VIS),在几项研究中被证明与AGB或LAI高度相关,计算所测量的试验田的数据。此外,被确定为标准化比值指数(NRI)最好的两波段组合。结果表明,在NRI茎的伸长的阶段进行比选择标准的VI更好,引导并在所有阶段航向和也。特别是在干伸长阶段(R〜(2)= 0.76)并在所有阶段(R〜(2)= 0.70),则执行NRI最好。当在农民的字段数据应用所述NRI,表现得较低(R〜(2)<0.60)。总体而言,敏感各个波长(±10nm)的最佳两波段的组合物在711和799纳米(对于分蘖期)检测,1575和1678纳米(对于干伸长阶段),515和695纳米(用于启动阶段),以及533和713纳米(对于所有阶段)。结果表明,基于高光谱的方法可以估算水稻AGB以满足精度。在精密农业的情况下,结果是对新的高光谱设备,诸如扫描仪或相机,其可以被固定在拖拉机或无人驾驶飞行器(UAV)未来的发展是有用的。

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