Urban sprawl represents the physical expansion in contiguous urban expansion which is often caused by inclusion of outgrowths/ satellite towns neighboring the core urban town. Guntur is one such Urban Agglomeration which has been experiencing rapid changes of urban expansion with the inclusion of outgrowths and villages within its administrative boundary. The aim of this research is to analyze the urban sprawl dynamics of Guntur city and its environs at different periods and forecast the future urban growth pattern. Different geospatial techniques are employed in order to gather a holistic understanding of the change in urban sprawl over time using decadal intervals and over space. Firstly, land use/ land cover thematic maps of 1999, 2011 and 2020 were used to examine the nature of LULC change within the study region. Consequently, an empirical relationship between explanatory variable of urban growth and land-use transitions to built- up class is modeled using Multi- Layer Perceptron neural network. The predictive power of the explanatory variables is tested by extrapolating the modeled relationship to make future predictions, with the help of Markov Chain method for land demand projection. The validation results on testing predicted and actual 2020 LULC map showed that there is low level of disagreement between the two images in terms of allocation and magnitude of change. With a proof of high accuracy, the model is used to predict change for 2030, 2040 and 2050 years. Analysis of both hard and soft prediction suggests that increase in built- up is predominantly due to transitions from agricultural and wastelands. Location next to the urban core town of Guntur and along major roads is showing high potential of future development. Lastly, study of population and urban dynamics reveals that they have strong positive correlation both follow a positive trend of growth.
Keywords: Urban Sprawl, Land Use/ Land Cover Change, Population, Spatial Patten of Change, Change Prediction.