Conclusion

Urban sprawl is posing challenges to sustainable development with key concerns of effective resource utilization, allocation of natural resources and infrastructure initiatives. The escalating urban growth in the study region has prompted concerns over the degradation of our living and environmental conditions. The study has attempted to understand LULC changes, the extent of urban expansion and urban sprawl in Bhopal city, quantified by defining important metrics (Complexity, Patchiness, Density and contagion/dispersion) and modelling the same for future prediction. Remote sensing and GIS techniques have been used to demonstrate their application for the monitoring and modelling of dynamic phenomena, like urbanisation. A Cellular automaton was used to simulate growth in Bhopal and surrounding area as a prototype for further regional applications with modest computational resources. The results demonstrate that the urban extent primarily consists of residential and commercial use that is assumed to have a linear relationship with population distribution. Thus, by incorporating urban extent, population distribution can be estimated by the model, in an indirect way. Different location conditions, such as road networks, business centre, urban centre, etc., were considered with various weights (transition probability) based on their relative significance. These properties provide a significant potential for modelling growth and changes under different conditions. Future urban extent, predicted for 2018 and 2022 are useful for visualizing and exploring potential development, as well as for assessing the impacts on agricultural lands. The results from the prediction of LULC indicate that the built-up in this area will increase by approximately 120 – 225% (based on CA-Markov) and 240-245% (based on ABM) from 2014 to 2022. ABM based prediction for built-up (in 2014) was comparable to the actual values (agreement greater than 99%). ABM could also bring out the major regions of growth such as Toomda and Sehore that are in the influence of urbanisation recently. These results will aid planners with prior visualization of growth for effective policy intervention. Despite the strengths of helping spatial and temporal decisions, CA-Markov has considerable limitations. Main drawback of the model CA-Markov is overcome with the consideration of current drivers or agents of changes through ABM for future transition probabilities. Physical urban growth in the region will undoubtedly continue, but it is required that the city planners and developers of Bhopal take a note of the situation and plan to ensure sustenance of natural resources. Land development policy in these cities have been highly inconsistent in recent years’ population growth and land development rates are impossible to synchronize. This also poses another great challenge in capturing the dynamics in contrast with other cities across the globe. ABM approach is capable of estimating probable sites for urban planning which synchronize with real scenario [54] [55]. Agent based simulations can capture reality more effectively as it provides us the flexibility to vary quantities and characteristics based on proximity of various amenities generating probability surface influenced by various agents, indicating urban development. The results of ABM clearly indicated the growth in places that were under the influence of growth of these agents considered. Thus we conclude agent based modelling was helpful and appropriate in developing future scenarios and application of ABM’s would help in understanding changing factors and dynamics to visualize the likely growth to provide basic amenities, infrastructure, etc.