Effects of adaxial and abaxial surface on the estimation of leaf chlorophyll content using hyperspectral vegetation indices

被引:20
|
作者
Lu, Xingtong [1 ]
Lu, Shan [1 ]
机构
[1] NE Normal Univ, Sch Geog Sci, Dept Geog Informat Sci, Changchun 130024, Peoples R China
基金
中国国家自然科学基金;
关键词
SPECTRAL REFLECTANCE; RED EDGE; LEAVES; ALGORITHM; CANOPIES; METER; RICE;
D O I
10.1080/01431161.2015.1012277
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Vegetation indices are frequently used for the non-destructive assessment of leaf chemistry, especially chlorophyll content. However, most vegetation indices were developed based on the statistical relationship between the spectral reflectance of the adaxial leaf surface and chlorophyll content, even though abaxial leaf surfaces may influence reflectance spectra because of canopy structure or the inclination of leaves. In the present study, reflectance spectra from both adaxial and abaxial leaf surfaces of Populus alba and Ulmus pumila var. pendula were measured. The results showed that structural differences of the two leaf surfaces may result in differences in reflectance and hyperspectral vegetation indices. Among 30 vegetation indices tested, R-672/(R-550 x R-708) had the smallest difference (4.66% for P. alba, 2.30% for U. pumila var. pendula) between the two blade surfaces of the same leaf in both species. However, linear regression analysis showed that several vegetation indices (R-850 - R-710)/(R-850 - R-680), VOG(2), D-730, and D-740, had high coefficients of determination (R-2 > 0.8) and varied little between the two leaf surfaces of the plants we sampled. This demonstrated that these four vegetation indices had relatively stable accuracy for estimating leaf chlorophyll content. The coefficients of determination (R-2) for the calibration of P. alba leaves were 0.92, 0.98, 0.93, and 0.95 on the adaxial surfaces, and 0.88, 0.87, 0.88, and 0.92 on the abaxial surfaces. The coefficients of determination (R-2) for the calibration of U. pumila var. pendula leaves were 0.85, 0.91, 0.86, and 0.90 on adaxial surface, and 0.80, 0.80, 0.84, and 0.88 on abaxial surface. These four vegetation indices were readily available and were little influenced by the differences in the two leaf surfaces during the estimation of leaf chlorophyll content.
引用
收藏
页码:1447 / 1469
页数:23
相关论文
共 50 条
  • [21] Retrieval of leaf chlorophyll content in Gannan navel orange based on fusing hyperspectral vegetation indices using machine learning algorithms
    Lian, Suyun
    Guan, Lixin
    Peng, Zhongzheng
    Zeng, Gui
    Li, Mengshan
    Xu, Yin
    CIENCIA RURAL, 2023, 53 (03):
  • [22] Assessing Rice Chlorophyll Content with Vegetation Indices from Hyperspectral Data
    Xu, Xingang
    Gu, Xiaohe
    Song, Xiaoyu
    Li, Cunjun
    Huang, Wenjiang
    COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE IV, PT 1, 2011, 344 : 296 - 303
  • [23] Upscaling from leaf to canopy: Improved spectral indices for leaf biochemical traits estimation by minimizing the difference between leaf adaxial and abaxial surfaces
    Wan, Liang
    Tang, Zheng
    Zhang, Jiafei
    Chen, Shuobo
    Zhou, Weijun
    Cen, Haiyan
    FIELD CROPS RESEARCH, 2021, 274
  • [24] HYPERSPECTRAL VEGETATION INDICES FOR CROP CHLOROPHYLL ESTIMATION: ASSESSMENT, MODELING AND VALIDATION
    Lin, Peirong
    Qin, Qiming
    Dong, Heng
    Meng, Qingye
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 4841 - 4844
  • [25] A comparison of hyperspectral chlorophyll indices for wheat crop chlorophyll content estimation using laboratory reflectance measurements
    Bannari, Abderrazak
    Khurshid, K. Shahid
    Staenz, Karl
    Schwarz, John W.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2007, 45 (10): : 3063 - 3074
  • [26] The impacts of bandwidths on the estimation of leaf chlorophyll concentration using normalized difference vegetation indices
    Ma, Mingliang
    Shi, Runhe
    Liu, Pudong
    Wang, Hong
    Gao, Wei
    REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY XI, 2014, 9221
  • [27] ANN-based Wheat Chlorophyll Density Estimation Using Canopy Hyperspectral Vegetation Indices
    Wang Dacheng
    Sen, Luorui
    Wang Jihua
    Li Cunjun
    Zhang Dongyan
    Zhang Yao
    Li Yufei
    ADVANCED MATERIALS IN MICROWAVES AND OPTICS, 2012, 500 : 243 - +
  • [28] A comparison of the predictive potential of various vegetation indices for leaf chlorophyll content
    Shichao Cui
    Kefa Zhou
    Earth Science Informatics, 2017, 10 : 169 - 181
  • [29] A comparison of the predictive potential of various vegetation indices for leaf chlorophyll content
    Cui, Shichao
    Zhou, Kefa
    EARTH SCIENCE INFORMATICS, 2017, 10 (02) : 169 - 181
  • [30] Optimal vegetation index for assessing leaf water potential using reflectance factors from the adaxial and abaxial surfaces
    Wang, Zitong
    Sun, Zhongqiu
    Lu, Shan
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2020, 172