Using Multi-Angular Hyperspectral Data to Estimate the Vertical Distribution of Leaf Chlorophyll Content in Wheat

被引:18
|
作者
Wu, Bin [1 ,2 ]
Huang, Wenjiang [1 ,3 ]
Ye, Huichun [1 ,3 ]
Luo, Peilei [1 ]
Ren, Yu [1 ,2 ]
Kong, Weiping [4 ]
机构
[1] Chinese Acad Sci, Key Lab Digital Earth Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100190, Peoples R China
[3] Chinese Acad Sci, Hainan Inst, Aerosp Informat Res Inst, Hainan Key Lab Earth Observat, Sanya 572029, Peoples R China
[4] Chinese Acad Sci, Key Lab Quantitat Remote Sensing Informat Technol, Aerosp Informat Res Inst, Beijing 100094, Peoples R China
基金
中国国家自然科学基金;
关键词
vertical profile; leaf chlorophyll content; multi-angular off-nadir spectral reflectance; canopy depth detection; wheat; VEGETATION INDEXES; WINTER-WHEAT; NITROGEN STATUS; USE EFFICIENCY; AREA INDEX; CANOPY; PROFILE; METER; INDICATOR; READINGS;
D O I
10.3390/rs13081501
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Heterogeneity exists in the vertical distribution of the biochemical components of crops. A leaf chlorophyll deficiency occurs in the bottom- and middle-layers of crops due to nitrogen stress and leaf senescence. Some studies used multi-angular remote sensing data for estimating the vertical distribution of the leaf chlorophyll content (LCC). However, these studies performed LCC inversion of different vertical layers using a fixed view zenith angle (VZA), but rarely considered the contribution of the components of the non-target layers to the spectral response. The main goal of this work was to determine the LCC of different vertical layers of the canopy of winter wheat (Triticum aestivum L.), using multi-angular remote sensing and spectral vegetation indices. Different combinations of VZAs were used for obtaining the LCC of different layers. The results revealed that the responses of the transformed chlorophyll in reflectance absorption index (TCARI) and modified chlorophyll absorption in reflectance index (MCARI)/optimized soil-adjusted vegetation index (OSAVI) to the upper-layer LCC were strongest at VZA 10 degrees. For the middle-layer LCC, the response was strongest at 30 degrees, but the response was significantly lower than that of the upper-layer. For the bottom-layer LCC, the responses were weak due to the obscuring effect of the upper- and middle-layer; thus, the LCC inversion of the bottom-layer data was not optimal for a single VZA. The optimal VZA or VZA combinations for LCC estimation were VZA 10 degrees for the upper-layer LCC (TCARI with coefficient of determination (R-2) = 0.69, root mean square error (RMSE) = 4.80 ug/cm(2), MCARI/OSAVI with R-2 = 0.73, RMSE = 4.17 ug/cm(2)), VZA 10 degrees and 30 degrees for the middle-layer LCC (TCARI with R-2 = 0.17, RMSE = 4.81 ug/cm(2), MCARI/OSAVI with R-2 = 0.17, RMSE = 4.76 ug/cm(2)), and VZA 10 degrees, 30 degrees, and 50 degrees for the bottom-layer LCC (TCARI with R-2 = 0.40, RMSE = 6.29 ug/cm(2), MCARI/OSAVI with R-2 = 0.40, RMSE = 6.36 ug/cm(2)). The proposed observation strategy provided a significantly higher estimation accuracy of the target layer LCC than the single VZA approach, and demonstrated the ability of canopy multi-angular spectral reflectance to accurately estimate the wheat canopy chlorophyll content vertical distribution.
引用
收藏
页数:15
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