I
en vegeta-
rsus diffe
MILKY
MATURITY
RHYS IOl0
GICAl HA
TURITY "
v
I
250
ated vege-
vegetation
g to the
;es. From
lase, the
on indices
i harvest,
all the
the same
point out
vegetation
, if the
iloited to
e sensing
observing
L profiles
tion cover
;ages. As
ion (R) is
vegetation
functions
vident in
3ver. That
ig phase.
.ated with
: for soil
leading is
Leld (if a
lition is
assumed until the harvest) it is essential to adopt
indices yielding the maximum variance between the
index values of the wheat fields. In Fig. 2 this
fact is illustrated taking into account three
spectral vegetation indices; the maximum percentage
variance at heading between index values of the
wheat yields is related to the ratio index (R). The
minimum variance between the field's index values,
corresponds to the maximum correlation with the
final grain yield.
Considering the ideal spectral profile plotted in
Fig. 3 from tillering to physiological maturity, it
is possible to identify three spectral profile
regions where the vegetation index families work to
the maximum efficiency.
From tillering to the end of the elongation stage,
the biophysical parameters closer to the final^grain
yield of the wheat, is the n° of plants per m . In
addition, during this time interval, % of soil
vegetation cover ranges from 10% to 45%. Thus the
reflectance of the soil is substantial portion of
the total radiance captured by the radiometre. The
perpendicular index yield values are less influenced
by the soil component.
From booting to heading, the soil vegetation cover
increases to 85%, the spectral component of the soil
is not as influential as in the previous stages and
the perpendicular indices are not as efficient as in
the ratio family. During these stages the
biophysical parameter most correlated to the final
grain yield can be considered the leaf area index,
that is closely tied to the soil vegetation cover.
It is not easy to explain why the ratio family is
more efficient than the vegetation indices belonging
to the other ones. One explanation is that the ratio
indices are less influenced by collateral effects
due to the plant architetture.
From flowering to the soft-dough stage the leaf
yellow component increases. In this time interval it
seems that the vegetation indices based on the
difference concept yield the maximum correlation
between the index values and the final grain yield
of the wheat field. No satisfactory explanation
exists in this case either, although it is possible
to relate the grain-filling-process to the duration
of the green leaf area index. This parameter can be
detected more efficiently by using indices based on
the difference concept rather than on the other
index families.
At the physiological maturity all the plant leaves
are yellowed and collapsed so that all the
vegetation indices proposed in this study have ^a
significant correlation with the n° of plant per m .
4 CONCLUSIONS
Wheat yield forecasting directly supported by means
of vegetation indices is still in a preliminary
phase since a significant correlation between
spectral vegetation index values and final grain
yield exists only at the heading phase. Moreover
this study has pointed out that the most appropriate
vegetation index can be selected only by considering
the phenological stage of the wheat crop. Although
it is not indicated in this report, the integrated
values of the vegetation indices have been
calculated and related to the final grain yield. The
use of the vegetation index duration values does not
significantly improved the relationship between the
remote sensing data and the biophysical parameters
of the wheat crop. On the other hand due to
cloudness in the area the quantity of space remote
sensing data is limited. Thus the possibility of
carrying out multitemporal observations in Central
and Northern Italy is rather low.
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winter wheat Dry-Matter production via Spectral
Reflectance Measurements. Remote Sens. Environ.
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Badhwar, G.D., and Shen, S.S. (1984): Techniques for
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Daughtry, C.S.T., Gallo, K.P., Bichl, L.L., Kanema-
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