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4.1 Analysis of variability of crop parameters
The variability of both field parameters and spectral parameters of
the cropped field were studied by computing their standard
deviations and coefficient of variations (CV). The spectral
parameters were studied through computation of vegetation
indices from both spectro-radiometer and satellite data. Though,
the field size was not very large and the wheat crop was grown
with a single management practice, the CV values ranged from
12.99 to 19.22 per cents, for LAI, above ground biomass and final
crop yield (Table 5). Among the narrow band spectral indices,
IAPRS & SIS, Vol.34, Part 7, "Resource and Environmental Monitoring", Hyderabad, India,2002
high CV of 30.08 per cent. This can be mentioned here that, the
concerned field (4.43 ha), as per the conventional soil
classification, had two major soil types such as sandy loam and
clay loam. Thus the management practice based on conventional
soil classification could have resulted into only two types, where
as the remote sensing data, can identify larger variability. As
mentioned in the methodology, a brightness index was also
computed from merged data, which showed a standard deviation
of 3.15 and CV of only 2.25 per cent. This could be due to large
pixel size (23 m) as compared to the field size.
Table 7. Variability of field and spectral parameters for the soil
RVI (blue and red) had highest CV 745 %), followed by MSI Parameter Mean Std. Dev. C.V. (96)
and the NDVI. NDVI generated fromriear inftared and red bands, 0.C.(%) 025 0.057 22.98
had the lowest CV, because of saturation reached in NDVI values, =
i.e. why the mean NDVI is as high as 0.90. AsaibbleN om) 10323 1422 1577
Available P (ppm) 28.54 8.61 30.16
Table 5. Variability of field and spectral parameters for the crop Available K (ppm) 100.34 20.70 20.62
Parameters Mean | Std. Dev. | C.V.(%) BI 0.22 0.07 30.08
Above ground biomass (gm) | .803.00 112.74 14.04 SI 0.30 0.02 7.63
Yield (q/ha) 62.92 8.17 12.99 HI 2.84 0.14 4.92
LAI (14.03.2002) 3.90 0:75 19.22 CI 0.12 0.01 10.96
NDVI (552-687) 0.35 0.04 10.26 RI 63.77 32.51 50.98
NDVI (927-687) 0.90 0.02 2.59
RVI (552-687) 2.11 0.17 8.08 4.3 Analysis of interrelationship of Variability
RVI (927-687) 20.04 3.43 17.13
MSI 0.34 0.04 11.15 Attempt was also made to derive the relationship between narrow
The spectral indices derived from IRS LISS III broadband data
also showed high CV values for wheat crop (Table6). Even for 23
m resolution data, (i.e. the field included only 1496 pixel), the CV
values ranged from 13.26 per cent for NDVIg. wm to 20.13 per cent
for RVI.
Table 6. Variability of satellite derived indices for the cropped
field
Parameters Mean Std. Dev. C.V.(%)
NDVIR-NIR 0.49 0.09 17,73
NDVIGr-r 0.28 0.04 13.26
RVI 2.99 0.60 20.13
MSI 0.88 0.13 15.03
4.2 Analysis of variability of Soil Parameters
A similar analysis of variability was carried out for the soil
parameters (Table7). Among the soil nutrient parameters
Available phosphorus showed highest variability (CV= 30.16 96)
followed by percent organic carbon, OC (22.98 %). Among all the
narrow-band soil colour related spectral indices, redness index,
which is an indicator of iron content, produced a CV of as high as
50.98 per cent. The brightness index, which is dependent upon
soil organic matter, texture and soil moisture content, had also a
band spectral indices with field crop and soil parameters. These
relationships can be later on used to predict the soil and crop
parameters using spectral indices; this would present a non-
destructive method of estimation the variability. The correlation
study between crop parameters and spectral indices showed that
(Table 8), among all the parameters above ground biomass, at
harvest, had the highest correlation with spectral indices. LAI
produced very low correlation, for all the indices. Among the
indices RVI and NDVI, computed using Green and Red
reflectance, showed highest correlation with crop parameters.
MSI, as expected, produced a negative correlation with all the
crop parameters.
Table 8. Correlation study of spectral indices and crop parameters
NDVI NDVI RVI RVI MSI
(552-687) |(927-687)| (552-687) |(927-687)
Above 0.63 0.43 0.63 0.54 -0.50
Ground
Biomass
Yield (g/ha) 0.60 0.38 0.60 0.48 -0.44
LAI 0.15 0.18 0.16 0.22 -0.20
Since, above ground biomass showed the highest correlation with
all the narrow-band spectral indices, various regression equations
were tried to find the empirical relation between biomass and
indices. The best-fit regression equations with their statistical
