SUSM: a scenario-based urban growth simulation model using remote sensing data

Figures & data

Figure 1. SUSM model structure.

Figure 2. Urban growth curve (S growth curve).

Table 1. Confusion matrix for validation of SUSM’s simulation.

	Observed urban growth
Simulated urban growth		Urban	Non-urban
	Urban	Hits (H)	False alarms (F)
	Non-urban	Misses (M)	Correct rejections (C)

Figure 3. Pune metropolis, PMC: Pune Municipal corporation, PCMC: Pimpiri Chinchwad Municipal Corporation, PCB: Pune Cantonment Board, KCB: Kirkee Cantonment Board.

Figure 4. Input datasets of SUSM.

Table 2. Location of urban growth seeds supplied to SUSM in scenario 1.

Name of the seed, location	Year of seed planting	Latitude	Longitude
Hinjewadi SEZ Phase 1	2004	18°35ʹ13.22”N	73°44ʹ3.48”E
Magarpatta City, Hadapsar	2004	18°30ʹ44.59”N	73°55ʹ47.20”E
Hinjewadi SEZ Phase 2	2008	18°35ʹ41.24”N	73°42ʹ28.48”E
Eon IT park, Kharadi	2008	18°33ʹ0.32”N	73°57ʹ8.27”E
Hinjewadi SEZ Phase 3	2011	18°34ʹ45.23”N	73°40ʹ52.52”E

Table 3. Logistic regression coefficients for the period of 1992 to 2001.

	1991–2001
Spatial variable	β		S.E.
Intercept	3.215	***	0.338
Slope	−0.015		0.030
Distance to city centre	−0.051	***	0.015
Distance to important roads	−0.133	*	0.069
Distance to railway stations	−0.123	***	0.026
Distance to major industries	−0.032	***	0.012
Distance to built-up	−2.531	***	0.252
Percentage of urban in one sq.km	0.020	**	0.008
Nagelkerke’s R^2	0.64
AIC	944.59
Moran’s I of Residuals	0.0699***

***p < .01; **p < .05; *p < 0.1

Table 4. Comparison of projected urban area to the remote sensing–derived urban area.

Year	Observed urban area (km^2) from remote sensing data	Projected urban area (km^2) using SUSM	Discrepancy
1990	107.5	–
2001	162.4	174.8	12.4
2013	322.9	318.4	−4.5

Figure 5. The urban growth curve of Pune metropolis (total area:1643 km²).

Figure 6. SUSM simulations used for validation (a) Urban growth transition potential and (b) Urban growth simulation maps of 2013.

Table 5. Validation results of SUSM.

Fit metric	Score	95% C.I.
Producer’s accuracy (Sensitivity)	75.76%	[75.38%, 76.14%]
User’s accuracy (Precision)	78.85%	[78.66%, 79.04%]
Overall accuracy	95.06%	[95.02%, 95.09%]
Specificity (True negative rate)	97.46%	[97.44%, 97.49%]
Matthews correlation coefficient	0.75	–
Figure of fit	0.63	–
Fuzzy Kappa	0.81	–
AUC	0.90	–

Figure 7. (a) Validation map showing the pixel level comparison of SUSM’s urban growth simulation with respect to observed urban growth from 2001 to 2013. (b) ROC curves of modelled urban growth transition potential of Pune for 2013.

Figure 8. (a) Urban growth simulations based on scenario 1: urban development plan (i.e. PMR regional development plan), (b) Urban growth simulations based on scenario 2: no urban development plan (i.e. business as usual based on the historic trend observed from 1992–2001 and without any future development measures), (c) and (d) comparison of simulated growth of Pune based on scenario 1 and scenario 2, respectively, with observed urban growth from 2001 to 2013.