1. 安徽大学计算智能与信号处理教育部重点实验室，安徽 合肥 230039 2. 北京农业信息技术研究中心，北京 100097 3. 中国科学院遥感与数字地球研究所，北京 100094 4. Department of Geography, University of Lethbridge, Alberta T1K 3M4，Canada
Assessment of Chlorophyll Content Using a New Vegetation Index Based on Multi-Angular Hyperspectral Image Data
LIAO Qin-hong1, 2, 3, ZHANG Dong-yan1, 2, 3*, WANG Ji-hua2, YANG Gui-jun2, YANG Hao2, Coburn Craig4, Wong Zhijie4, WANG Da-cheng3
1. Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China 2. Beijing Agriculture Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China 4. Department of Geography, University of Lethbridge, Alberta T1K 3M4, Canada
Abstract：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.
廖钦洪1, 2, 3，张东彦1, 2, 3*，王纪华2，杨贵军2，杨 浩2，Coburn Craig4，Wong Zhijie4，王大成3 . 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 [J]. 光谱学与光谱分析, 2014, 34(06): 1599-1604.
LIAO Qin-hong1, 2, 3, ZHANG Dong-yan1, 2, 3*, WANG Ji-hua2, YANG Gui-jun2, YANG Hao2, Coburn Craig4, Wong Zhijie4, WANG Da-cheng3. Assessment of Chlorophyll Content Using a New Vegetation Index Based on Multi-Angular Hyperspectral Image Data . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(06): 1599-1604.
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