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Remote sensing for resources development and environmental management
Damen, M. C. J.

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,
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.
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.
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
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