National Engineering and Technology Center for Information Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China.
Center for Spatial Technologies and Remote Sensing (CSTARS), Department of Land, Air, and Water Resources, University of California, Davis, CA 95616-8617, USA.
Sensors (Basel). 2017 Mar 13;17(3):578. doi: 10.3390/s17030578.
Monitoring the components of crop canopies with remote sensing can help us understand the within-canopy variation in spectral properties and resolve the sources of uncertainties in the spectroscopic estimation of crop foliar chemistry. To date, the spectral properties of leaves and panicles in crop canopies and the shadow effects on their spectral variation remain poorly understood due to the insufficient spatial resolution of traditional spectroscopy data. To address this issue, we used a near-ground imaging spectroscopy system with high spatial and spectral resolutions to examine the spectral properties of rice leaves and panicles in sunlit and shaded portions of canopies and evaluate the effect of shadows on the relationships between spectral indices of leaves and foliar chlorophyll content. The results demonstrated that the shaded components exhibited lower reflectance amplitude but stronger absorption features than their sunlit counterparts. Specifically, the reflectance spectra of panicles had unique double-peak absorption features in the blue region. Among the examined vegetation indices (VIs), significant differences were found in the photochemical reflectance index (PRI) between leaves and panicles and further differences in the transformed chlorophyll absorption reflectance index (TCARI) between sunlit and shaded components. After an image-level separation of canopy components with these two indices, statistical analyses revealed much higher correlations between canopy chlorophyll content and both PRI and TCARI of shaded leaves than for those of sunlit leaves. In contrast, the red edge chlorophyll index (CI) exhibited the strongest correlations with canopy chlorophyll content among all vegetation indices examined regardless of shadows on leaves. These findings represent significant advances in the understanding of rice leaf and panicle spectral properties under natural light conditions and demonstrate the significance of commonly overlooked shaded leaves in the canopy when correlated to canopy chlorophyll content.
利用遥感监测作物冠层的组成成分，有助于我们了解冠层内光谱特性的变化，并解决光谱估算作物叶片化学性质的不确定性来源问题。迄今为止，由于传统光谱数据的空间分辨率不足，作物冠层中叶片和穗的光谱特性及其对光谱变化的阴影效应仍未得到很好的理解。为了解决这个问题，我们使用了具有高空间和光谱分辨率的近地成像光谱系统，研究了冠层中阳光照射和阴影部分的水稻叶片和穗的光谱特性，并评估了阴影对叶片光谱指数与叶片叶绿素含量之间关系的影响。结果表明，阴影部分的反射率幅度较低，但吸收特征比阳光照射部分更强。具体而言，穗的反射光谱在蓝色区域具有独特的双峰吸收特征。在所研究的植被指数（VIs）中，叶片和穗之间的光化学反射指数（PRI）存在显著差异，阳光照射和阴影部分之间的转化叶绿素吸收反射指数（TCARI）也存在进一步差异。利用这两个指数对冠层成分进行图像级分离后，统计分析表明，与阳光照射的叶片相比，阴影叶片的 PRI 和 TCARI 与冠层叶绿素含量之间的相关性更高。相比之下，无论叶片是否有阴影，红边叶绿素指数（CI）与所有研究的植被指数中与冠层叶绿素含量的相关性最强。这些发现代表了在自然光条件下对水稻叶片和穗光谱特性认识的重大进展，并表明在与冠层叶绿素含量相关时，通常被忽视的冠层阴影叶片的重要性。
