利用光谱技术探索了水稻稻纵卷叶螟虫害的检测。 通过分析田间水稻稻纵卷叶螟受害区和对照区冠层反射光谱和一阶微分光谱特征差异发现, 可见光区(400～700 nm), 550 nm附近中度受害水稻冠层反射率明显低于对照冠层反射率值, 重度受害水稻冠层反射率则高于对照区冠层反射率; 水稻受害时, 叶片受损及干枯导致叶绿素含量降低, 对红光波段(600～700 nm)的吸收减小。 近红外区(750～770 nm)范围内, 受害水稻冠层反射光谱曲线均不同程度出现“尖峰”波动, 且光谱曲线红边拐点发生“蓝移”。 通过构建样本总体修正曲线, 提供了直观判别广域水稻是否受稻纵卷叶螟虫害侵扰的依据。 进一步探讨稻纵卷叶螟受害区定性检测参数发现, 利用NIR-NDVI特征可以有效地区分对照区和受害区区域, 经验证, 准确率达70%。

The canopy reflectance of rice was measured in the filed in order to monitor the damaged region caused by Cnaphalocrocis medinalis Guenee. The characteristics of canopy spectral reflectance were analyzed in contrast region and damaged regions. When rice plant was damaged by Cnaphalocrocis medinalis Guenee, the chlorophyll absorption was decreased in the band of 600-700 nm. The canopy reflectance of moderate damage region was lower than that of the contrast region, while the reflectance of severe damage region rice was higher near 550 nm. The canopy reflectance of Cnaphalocrocis medinalis Guenee damaged rice was fluctuant and exhibited the significant peak in the NIR band of 750-770nm. Meanwhile, red edge inflection point as one of the most important spectral parameters was analyzed at different damage levels based on the first derivative of reflectance spectra. The analysis results indicated that red edge inflection position moved to direction of blue light (short wavelength) with the affection severity increasing. Then the modified reflectance of rice canopy was calculated based on zero-mean calculation and standard deviation. It was easy to find the degree of deviation from the average of samples and distinguish the damaged region from experiment plots. The canopy modified reflectance was gently in the contrast region, but changed violently in the affected regions in the band of 750-950 nm. The analysis of Cnaphalocrocis medinalis Guenee affected regions illustrated that the Cnaphalocrocis medinalis Guenee was increased with the increase in severity. The vegetation index was applied in detection of Cnaphalocrocis medinalis Guenee damaged regions because of the composition of multi-wavelength information. The wavelengths 762 and 774 nm were chosen to build detection parameters of Cnaphalocrocis medinalis Guenee such as NIR-RVI, NIR-DVI, NIR-NDVI and KI. The results indicated that the NIR-NDVI could be used to identify the damaged region with contrast region efficiently. The accurate rate of 25 verification samples selected randomly reached 70%. The preliminary studies on rice Cnaphalocrocis medinalis Guenee damaged regions provided a new method to detect the affected regions in the wide area.