基于多角度成像数据的新型植被指数构建与叶绿素含量估算

叶绿素含量的快速估算对于及时了解作物的长势、病虫害监测以及产量的评估都具有重要意义。利用自主研发的多角度成像观测系统获取了不同生育期玉米的高光谱影像，精确地提取出主平面内各个观测角度下玉米冠层的反射率。通过对ACRM模型模拟值和实测值的分析，计算出玉米冠层红波段下的热点-暗点指数(HDS)，并利用该指数对TCARI进行改进，提出一个基于多角度观测的新型植被指数HD-TCARI，最后使用多角度高光谱成像数据对其进行了地面验证。结果表明，HD-TCARI能够减小LAI对叶绿素估算的影响，当叶绿素浓度大于30 μg·cm-2，HD-TCARI与LAI的相关性R2仅为26.88%～28.72%;当叶绿素浓度较高时，HD-TCARI具有抗“饱和”的特性在LAI在1～6之间变化时，HD-TCARI与叶绿素浓度的线性关系R2较TCARI提高了约9%左右。利用多角度高光谱成像数据对HD-TCARI进行地面验证，其与叶绿素浓度的线性关系(R2=66.74%)明显优于TCARI所建立的估算模型(R2=39.92%)，证明了HD-TCARI指数具有更好地估算叶绿素浓度的潜力。

Assessment of Chlorophyll Content Using a New Vegetation Index Based on Multi-Angular Hyperspectral Image Data

The fast estimation of chlorophyll content is significant for understanding the crops growth, monitoring the disease and insect, and assessing the yield of crops. This study gets the hyperspectral imagery data by using a self-developed multi-angular acquisition system during the different maize growth period, the reflectance of maize canopy was extracted accurately from the hyperspectral images under different view angles in the principal plane. The hot-dark-spot index (HDS) of red waveband was calculated through the analysis of simulated values by ACRM model and measured values, then this index was used to modify the vegetation index (TCARI), thus a new vegetation index (HD-TCARI) based on the multi-angular observation was proposed. Finally, the multi-angular hyperspectral imagery data was used to validate the vegetation indexes. The result showed that HD-TCARI could effectively reduce the LAI effects on the assessment of chlorophyll content. When the chlorophyll content was greater than 30 μg·cm-2, the correlation (R2) between HD-TCARI and LAI was only 26.88%～28.72%. In addition, the HD-TCARI could resist the saturation of vegetation index during the assessment of high chlorophyll content. When the LAI varied from 1 to 6, the linear relation between HD-TCARI and chlorophyll content could be improved by 9% compared with TCARI. The ground validation of HD-TCARI by multi-angular hyperspectral image showed that the linear relation between HD-TCARI and chlorophyll content (R2=66.74%) was better than the TCARI (R2=39.92%), which indicated that HD-TCARI has good potentials for estimating the chlorophyll content.