## Appendix

Appendix A: Coefficients of causal factors and percentage built-up by linear regression analyses

 Dependent Variable (y) Independent Variables (x) Equation (y = a*x + b) Standard Error of ‘y’ Estimate Correlation Coefficient, r pcbuilt pop99 y = 0.000611 x + 10.87149 13.0163 0.5327 pcbuilt popaden y = - 0.0004 x + 19.5719 11.2594 0.2070 pcbuilt popbden y = 0.005774 x + 7.849476 10.1397 0.6474 pcbuilt agr y = 0.635301 x + 13.0499 13.2391 0.0990 pcbuilt mangdist y = - 0.31149 x + 22.93755 12.2142 0.3965 pcbuilt udupidist y = 0.315763 x + 5.584017 12.1528 0.4070

Appendix B: Coefficients of causal factors and percentage built-up by polynomial (order=2) regression analyses

 Dependent Variable (y) Independent Variables (x) Equation (y = a*x2 + b*x +c) Standard Error of ‘y’ Estimate Correlation Coefficient, r pcbuilt pop99 y = 0.0006*x2 – 1.5*10-9*x + 9.7776 10.9210 0.5784 pcbuilt popaden y = -0.00037*x2 – 2.7*10-9*x + 18.555 13.0577 0.2208 pcbuilt popbden y = 0.005651*x2 – 1.2*10-7*x + 6.8950 9.7880 0.6823 pcbuilt agr y = 0.66679*x2 + 0.05754*x + 13.3308 13.3190 0.1017 pcbuilt mangdist y = -1.7953*x2 + 0.02593*x + 36.8607 10.6784 0.6032 pcbuilt udupidist y = -0.9027*x2 + 0.002242*x + 15.9731 10.8729 0.5835

Appendix C: Coefficients of causal factors and percentage built-up by logarithmic regression analyses

 Dependent Variable (y) Independent Variables (x) Equation (log y = log(a) + b*log x) Standard Error of ‘y’ Estimate Correlation Coefficient, r lnpcbuilt lnpop99 y = – 0.429 + 0.331*x 0.7656 0.3835 lnpcbuilt lnpopaden y = – 1.308 + 0.527*x 0.7282 0.4779 lnpcbuilt lnpopbden y = + 7.796 – 0.593*x 0.6754 0.3363 lnpcbuilt lnagr y = + 2.275 + 0.104*x 0.8263 0.0799 lnpcbuilt lnmangdist y = + 3.718 – 0.456*x 0.7208 0.4939 lnpcbuilt lnudupidist y = + 2.008 + 0.114*x 0.8192 0.1527

 Energy CES IISc Envis Envis Node 