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The product of Em and a vegetation coefficient (Kv = Ev/Em) is used to estimate the evapotranspiration of the ecosystem vegetation (Ev) under well-watered conditions with a full-canopy cover within the same microclimate.
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However, regression analysis of rainfall over forest cover and vegetation shows regression coefficient value of 0.0875 and 0.3459, respectively.
In the post-monsoon season, the regression analysis of temperature over forest cover and vegetation shows regression coefficient value of 0.1206 and 0.6854, respectively.
In the pre-monsoon season, the regression analysis of temperature over forest cover and vegetation shows regression coefficient values of 0.6876 and 0.5751, respectively.
However, regression analysis of rainfall over forest cover and vegetation shows regression coefficient value of 0.8417 and 0.0027, respectively in post-monsoon season, rainfall exhibited significant positive response to forest cover and temperature exhibited negative response to vegetation. 3.
However the correlation coefficient between vegetation index and vegetation coverage is slightly low.
Linear regression analyses showed that there were varying relationships between Russian wheat aphid density and spectral vegetation indices, with coefficients of determination (r2) ranging from 0.91 to 0.01.
Similarly, regression analysis between rainfall and vegetation shows low regression coefficient value of 0.3459 (Fig. 6b).
For the LAI and biomass, all vegetation indices produced similar coefficients of determination.
Vegetation density and resistance coefficients were determined on site and their spatial distribution through visual interpretation of Google Earth® pre tsunami imagery.
Similarly, Regression analysis between rainfall and vegetation shows a low regression coefficient value of 0.0027 (Fig. 8b).
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