Biophysical and biochemical sources of variability in canopy reflectance

被引:946
作者
Asner, GP [1 ]
机构
[1] Univ Colorado, CIRES, CSES, Boulder, CO 80309 USA
基金
美国国家科学基金会; 美国国家航空航天局;
关键词
D O I
10.1016/S0034-4257(98)00014-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Analyses of various biophysical and biochemical factors affecting plant canopy reflectance have been carried out over the past few decades, yet the relative importance of these factors has not been adequately addressed. A combination of field and modeling techniques wee used to quantify the relative contribution of leaf, stem, and litter optical properties (incorporating known variation in foliar biochemical properties) and canopy structural attributes to nadir-viewed vegetation reflectance data. Variability in tissue optical properties was wavelength-dependent. For green foliage, the lowest variation was in the visible (VIS) spectral region and the highest in the near-infrared (NIR). For standing litter material, minimum variation occurred in the VIS/NIR, while the largest differences were observed in the shortwave-IR (SWIR). Woody stem material slowed opposite trends, with lowest variation in the SWIR and highest in the NIR. Leaf area index (LAI) and leaf angle distribution (LAD) were the dominant controls on canopy reflectance data with the exception of soil reflectance and vegetation cover in sparse canopies. Leaf optical properties (and thus foliar chemistry) were expressed most directly at the canopy level in the NIR, but LAI and LAD strongly controlled the relationship between leaf and canopy spectral characteristics. Stem material played a small but significant role in determining canopy reflectance in woody plant canopies, especially those with LAI<5.0. Standing litter significantly affected the reflectance characteristics of grassland canopies; small increases in the percentage of standing litter had a disproportionately large affect on canopy determine the relative contribution of tissue, canopy, and landscape factors that drive variation in a reflectance signal. Deconvolution of these factors requires an understanding of the sources of variance at each scale (which is ecosystem dependent) as well as an adequate sampling (spectral, angular, and temporal) of the shortwave (400-2500 nm) spectrum. (C)Elsevier Science, Inc. 1998.
引用
收藏
页码:234 / 253
页数:20
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