Can MODIS derived NDVI provides biophysical status of Tea bush?

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Can MODIS derived NDVI provide biophysical status of Tea bush?

5.3 Relation Between Tea Leaf Yield and MODIS NDVI:
Correlation analysis was carried out between area weighted averaged NDVI of tea for selected tea estate with their tea leaf yield for different years (2000-2004). The correlation coefficient ‘r’ values between yield and NDVI at critical time periods are shown in the table. Results showed that correlation is positive and significant irrespective of month of the NDVI over the years. During 2000 and 2001, tea leaf yield was found significantly related to NDVI at 95% level of significance while during 2003, correlation is positive at 1% level of significance.

Year	NDVI (April)	NDVI (June)	NDVI (August)
2000	0.503*	0.475*	0.440*
2001	0.489*	0.492*	0.469*
2002	0.561**	0.629**	0.520*
2003	0.643**	0.670**	0.680**
2004	0.530*	0.559**	0.553*

*Significant at 0.05% level & **Significant at 0.01% level
Year wise correlation between tea leaf yield and MODIS based NDVI of tea estates during different months

Variations could be well observed from the table. There were reasons for such variations. During the year 2000, there was outbreak of disease infestation due to heavy showers accompanied by high temperature and high humidity. This condition is highly favourable for Red Spider and Helopeltis attack. Apart from this, the ground LAI collected from the field showed lot of variations due to continuous plucking, infestations and also due to un-plucked areas. The different species also showed variations in the LAI readings. But still a significant correlation could be seen between tea leaf yield and MODIS NDVI of tea estates during different months.

5.3.1 Tea Yield Model
Linear relationships between tea leaf yield and MODIS NDVI were developed. Here five years yield from 2000 – 2004 as well as their corresponding NDVI were used for the yield model. The observations were linearly regressed for three different months as shown in the Table 10. It was observed that there is a significant positive correlation between yield and NDVI. The variance of 0.243 and 0.292 indicate that there is greater variability in the yield during different periods. Though the R2 value of the coefficient of determination was found to be less the relationships were significant.

Sr. No.	Equation	N	R²	SEE	F
1	1106.06 + 1472.55 * NDVI_June	88	0.243	287.09	27.56
2	797.29 + 1208.08 * NDVI_June + 890.43 * NDVI_Aug	88	0.292	279.24	17.52

Tea Leaf Yield Models Based on MODIS NDVI

The significance (probability) of the F value was set at 0.05 level. The entry probability of F value taken is less than 0.05 for significant result. The F probability result shows for all linear regression equation are less than significance F change. There is a close relationship between yield and NDVI. Therefore the Null Hypothesis1 (H0) which shows that there is a close relationship between yield, LAI and NDVI used for finding the yield variability is accepted while the alternative hypothesis (Ha) is rejected.

6. Conclusions:

To test whether MODIS derived NDVI is related to LAI, an empirical equation was established.
Equation shows that LAI in tea had significant and linear relationship with NDVI (R2=0.36).
NDVI observation at different time period alone could not explained much variance in tea leaf yield.
Statistical model for tea yield does not seem to be encouraging.
The performance of the model would have been much better if the weather parameters for the entire state would have been taken into consideration.
An improved statistical model for tea yield needs to be developed.

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