347 
Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 
Spectral components analysis: Rationale and results 
C.L.Wiegand & AJ.Richardson 
US Department of Agriculture, Agricultural Research Sevices, Weslaco, Tex., USA 
ABSTRACT: The spectral components analysis (SCA) identities, 
LAI/VI x APAR/LAI = APAR/VI [1] 
and LAI/VI x YIELD/LAI = YIELD/VI, [2] 
wherein VI denotes any one of several spectral veqetation indices available, LAI is leaf area index, APAR is 
absorbed photosynthetically active radiation, and YIELD is salable plant part (grain, fiber, or root), 
express the information conveyed by canopies about their development, response to stresses, and yield 
capability. The rationale of SCA is carefully presented as are the relations between numerator and 
denominator of each term in equation [1] for the crops wheat, cotton, and maize. Results show that APAR can 
be estimated almost as well from VI as from LAI, and that the relation is nearly linear. Equations [1] and 
[2] help to: quantify remote assessments of crop productivity; unify field-observed interrelations among 
LAI, APAR, and YIELD; and, validate remotely observable IAI and APAR inputs for plant process crop growth and 
yield models, or for growth analysis. 
1 INTRODUCTION 
Spectral components analysis implies that the plant 
stands integrate the growing conditions experienced, 
express the growth and yield responses through the 
canopies achieved, and that stresses severe enough 
to affect YIELD will be detectable through their 
effects on the development and persistence of 
photosynthetically active tissue in the canopies. 
Vegetation indices (Kauth and Thomas, 1976; 
Richardson and Wiegand, 1977; Tucker, 1979) are used 
to indicate the amount of photosynthetically active 
tissue in the canopies. 
The approach is expressed by equations [1] and [2] 
wherein each term represents the functional 
dependence of the numerator over the range of the 
seasonal values of the denominator variable. The 
equations are intended to convey the property of an 
identity; that is, if the individual terms on the 
left hold, then the right hand side of the equation 
follows. Additionally since the right hand side 
denominators are common the numerators APAR and 
YIELD must be related. 
We termed the approach "spectral components 
analysis" (SCA) by analogy with yield components 
analysis (Women et al., 1979; Black and Aase, 1982). 
The first application of SCA (Wiegand and 
Richardson, 1984) was to data for South Texas grain 
sorghum (Sorghum bicolor L., Moench) fields that had 
been sampled periodically to determine LAI and at 
maturity for grain yield. The spectral data were 
obtained by the Landsat multi spectral scanner (MSS) 
during grain filling whereas the APAR versus LAI 
relation was taken from Maas and Arkin (1978). 
Subsequently, snail plot experiments have been 
conducted for three crops: hard red spring wheat 
(Triticum aestivum L.), cotton (Gossypium hirsutum 
L.) (Wiegand et al., 1986) and corn (Zea mays, L.) 
(Maas et al., 1985). The purposes of this paper are 
to present the rationale for the approach and the 
relations term-by-term for equation [1] for these 
latter studies. 
2 RATIONALE 
The rationale for the approach embodies the 
following principles: 
a. leaf area index is a fundamental attribute of 
plant canopies (Jordan, 1983; Pearson, 1984) because 
the leaves are the dominant photosynthetically 
active tissue in the canopies. Assimilates of 
photosynthesis support further development and the 
increase in dry weight of all plant parts, roots, 
leaves, stans, and reproductive organs. 
b. Foliar characteristics dominate the 
interaction of electromagnetic radiation with plants 
so that interpretation from remote observations is 
based primarily on characteristics of the foliage 
(Wiegand et al., 1972). Spectral vegetation indices 
relate to many plant canopy characteristics (LAI, 
green biomass and percent cover) and are now 
recognized as a good measure of the amount of 
photosynthetically active tissue in the canopy any 
time during the season (Wiegand et al., 1986a). 
Thus the vegetation indices can reliably estimate 
LAI and intercepted or absorbed PAR. 
c. The crop canopies attained integrate the soil 
and aerial environments experienced including 
stresses (soil water availability, nematodes, 
herbicide residues, soil salinity, diseases, 
atmospheric pollutants), past and present management 
and cultural practices (fertility, irrigations, 
tillage, residue management, growth regulators, ...) 
and natural soil variation (water holding capacity, 
rooting depth, texture, soil depth, slope ...). The 
reflectance factor observations sense the effects 
(without diagnosing the cause) and "quantify" the 
response through the vegetation indices. 
d. Comercial agriculture is tuned by experience 
and experimentation (seeding rates and planting 
configurations, fertility levels, adapted cultivars, 
irrigations ...) to achieve canopy closure by the 
plant reproductive stage because high yields can not 
be achieved unless the available PAR is effectively 
intercepted during the reproductive phase. 
Throughout the plant's life cycle, but especially 
during reproduction, pathologists and entomologists 
protect the foliage, fruit, and main stans from 
insect, arthropod, fungal, viral and other plant 
predators. 
The converse is not true. Effective light 
interception does not insure high yields; the 
reproductive organs must be set and be protected 
from predators until harvest. Thus the VI observed 
relate to actual YIELD unless conditions were so 
stressful as to inhibit fruit set or retention, or 
the development of the reproductive organs was