A theoretical analysis of the influence of heterogeneity in chlorophyll distribution on leaf reflectance

被引:24
|
作者
Barton, CVM [1 ]
机构
[1] Ctr Ecol & Hydrobiol Edinburgh, Penicuik EH26 0QB, Midlothian, Scotland
关键词
chlorosis; UBERTY; modeling; patchiness;
D O I
10.1093/treephys/21.12-13.789
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Attempts to determine the vitality of vegetation and to detect vegetation stress from remotely sensed data have focused on chlorophyll concentration, because it influences the reflectance of vegetation and tends to correlate with vegetation health and stress. Pollution, pathogens and pests can cause localized regions of chlorosis and necrosis across a leaf surface, but the extent to which these patches influence the overall reflectance and spectral signature of the leaf and canopy has not been tested. A conifer leaf model (LIBERTY), which simulates the influence of leaf biochemical concentrations of chlorophyll, water, lignin, cellulose and protein on the reflectance of leaves from 400 to 2500 nm, was used to determine the effect of patches of chlorosis on leaf reflectance. A fraction of the leaf f is assumed to be chlorotic with a chlorophyll concentration C-1. The remainder of the leaf has chlorophyll concentration C-2 such that mean leaf chlorophyll concentration, C-mean = fC(1) + (I-f)C-2, is constant for a range of f and C-1 values. LIBERTY can be used to estimate the reflectance of a leaf with a particular chlorophyll concentration at a particular wavelength R-lambda ,R-c (assuming other leaf properties remain constant), thus we can estimate the reflectance of the chlorotic leaf as fR(lambda ,c1) + (1 - f) R-lambda,R-,(C2). The model indicated that small areas of chlorosis have a disproportionately large influence on overall leaf reflectance. For example, a leaf with 25% of its area chlorotic can have the same reflectance (400-700 nm) as a homogeneous leaf with 60% less chlorophyll. Thus, determination of chlorophyll concentration from remotely sensed data is prone to underestimation when chlorophyll is nonuniformly distributed. Hence, attempts to model leaf and canopy reflectance using radiative transfer models will need to consider how to incorporate nonuniform chlorophyll distribution.
引用
收藏
页码:789 / 795
页数:7
相关论文
共 50 条
  • [1] Maize Canopy and Leaf Chlorophyll Content Assessment from Leaf Spectral Reflectance: Estimation and Uncertainty Analysis across Growth Stages and Vertical Distribution
    Yang, Hongye
    Ming, Bo
    Nie, Chenwei
    Xue, Beibei
    Xin, Jiangfeng
    Lu, Xingli
    Xue, Jun
    Hou, Peng
    Xie, Ruizhi
    Wang, Keru
    Li, Shaokun
    REMOTE SENSING, 2022, 14 (09)
  • [2] Signature analysis of leaf reflectance spectra: Algorithm development for remote sensing of chlorophyll
    Gitelson, AA
    Merzlyak, MN
    JOURNAL OF PLANT PHYSIOLOGY, 1996, 148 (3-4) : 494 - 500
  • [3] Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis
    Blackburn, George Alan
    Ferwerda, Jelle Garke
    REMOTE SENSING OF ENVIRONMENT, 2008, 112 (04) : 1614 - 1632
  • [4] Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance
    Daughtry, CST
    Walthall, CL
    Kim, MS
    de Colstoun, EB
    McMurtrey, JE
    REMOTE SENSING OF ENVIRONMENT, 2000, 74 (02) : 229 - 239
  • [5] LEAF REFLECTANCE VS LEAF CHLOROPHYLL AND CAROTENOID CONCENTRATIONS FOR 8 CROPS
    THOMAS, JR
    GAUSMAN, HW
    AGRONOMY JOURNAL, 1977, 69 (05) : 799 - 802
  • [6] Effects of leaf structure on reflectance estimates of chlorophyll content
    Serrano, Lydia
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2008, 29 (17-18) : 5265 - 5274
  • [7] LEAF REFLECTANCE-NITROGEN-CHLOROPHYLL RELATIONS IN BUFFELGRASS
    EVERITT, JH
    RICHARDSON, AJ
    GAUSMAN, HW
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 1985, 51 (04): : 463 - 466
  • [9] Retrieval of Chlorophyll Content in Maize From Leaf Reflectance Spectra Using Wavelet Analysis
    Lv, Jie
    Yan, Zhenguo
    INTERNATIONAL SYMPOSIUM ON OPTOELECTRONIC TECHNOLOGY AND APPLICATION 2014: IMAGING SPECTROSCOPY; AND TELESCOPES AND LARGE OPTICS, 2014, 9298
  • [10] THE INFLUENCE OF LEAF ORIENTATION AND THE SPECULAR COMPONENT OF LEAF REFLECTANCE ON THE CANOPY BIDIRECTIONAL REFLECTANCE
    ROSS, J
    MARSHAK, A
    REMOTE SENSING OF ENVIRONMENT, 1989, 27 (03) : 251 - 260