Fig. 2. (A) The location of two sample areas to show (B) The canopy of trees in Hasht Behesht Garden derived by applying ΔExGR index on the Worldview image C)The canopy of trees around Zayandeh-rood river derived by ΔExGR index on the worldview image.
Analyzing the relationship between calculated carbon sequestration and vegetation index using the GWR model
Table 6 represents the results of the relationship between ΔExGR as an independent variable with dependent variables (carbon sequestration) in GWR model. The results of the GWR regression modeling (Table 6) show that Residual Squares (R2) was 0.91, indicating what percentage of the changes in the dependent variable was explained by the independent variables. Also, the amount of adjusted residual squares (Adjusted R2) was 0.64. Using adjusted R2 is useful when we have more than one independent variable in the regression model. In this research, considering only one independent variable, we used R2 to investigate the relationship between vegetation index and carbon sequestration: there was a significant positive relationship between them. As it can be shown in table 6, the Sigma parameter (i.e., second root of the normalized Residual Square) was also used to show the relationship between dependent and independent variables. The less sigma value, the better relationship. In this analysis, the sigma value was 0.0399. Another parameter was the Corrected Akaike Information Criterion (AICc). The AICc is a mathematical method for evaluating how well a model fits the data it was generated from.Table 6- the relationship between calculated carbon sequestration and vegetation index using GWR model