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Urbanisation and Urban Sprawl

 

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

 

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