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Analysis of Rice False Smut Severity Levels in Donggang Using Vegetation Index Normalization

机译：植被指数规范化Donggang水稻假粉体严重程度分析

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摘要

Timely monitoring of crop disease development is very important for precision agriculture application. Remote sensing-based vegetation indices(VIs) can be good indicators of crop disease severity, but the result of inversion could be affected by the growing environment of crops and has strong uncertainly. Based on Ⅵ normalization, crop disease could be identified and has an inherent correlation, and eliminate the influence of variable field condition and the Ⅵ range variations. This technique was applied to rice fields infested with false smut in Donggang, Liaoning. Five typical VIs and a custom Ⅵ were calculated from the hyperspectral data collected by ground spectral survey using McPin. Six Vegetation indexes were normalized and the regression analysis of normalized result and ground survey result was carried out. The statistical analysis of the results showed that the mean value of normalized VIs had a good rule with the disease grade, and the variance of the disease level with a large number of samples was also very small, most of them were less than 0.1 which can provide reference for further study of automatic classification of disease. According to the analysis of the obtain result, the normalized Vegetation Indexes value has a inherent correlations with disease severity level acquired by ground survey, and with the development and application of more VIs, there is still a broader room for the development of this method.
机译：及时监测作物疾病的发展对于精密农业应用非常重要。基于遥感的植被指数（VI）可以是作物疾病严重程度的良好指标，但反转结果可能受到农作物不断增长的环境的影响，并且不确定。基于△标准化，可以识别作物疾病并具有固有的相关性，并消除可变场条件和ζ范围变化的影响。这种技术应用于辽宁东港的假粉丝感染的稻田。根据使用MCPIN通过地面光谱测量收集的高光谱数据计算五种典型的VIS和定制ⅵ。六种植被指数标准化，进行了归一化结果和地面调查结果的回归分析。结果的统计分析表明，标准化Vis的平均值具有良好的疾病等级规则，并且疾病水平与大量样品的差异也非常小，其中大部分都小于0.1提供进一步研究自动分类疾病的参考。根据分析结果，归一化植被指数值具有与地面调查获得的疾病严重程度水平的固有相关性，并随着更多VI的开发和应用，仍然是这种方法的开发更广泛的空间。

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