Comprehending urban growth pattern for delineating urban growth boundary of Hyderabad city

Abstract

Through most of history the human population has lived a rural lifestyle. However, in the first decade of the 20th century this trend started to change and the world is still becoming urbanized as thousands of people migrate to cities. Urbanization is now a rising trend seen all over the world, especially in an alarming rate in developing countries. This makes cities grow both in number and in physical size. In quite a lot of instances, the percentage increase in population is accompanied by more than proportional percentage increase of an urbanized area. This is an indication that the two growth rates differ and urban area grows in a more rapid pace. An urban system has been identified as a non-linear complex system which is a recursive one and an amalgamation of various physical and random factors. Urban growth can be defined as a system resulting from the complex dynamic interactions between the developable, the developed and the planned systems. Complexity of urban systems is distinguished by analyzing the spatial, temporal and decisionmaking dimensions. It is linked with the major current methods of modern urban modelling, such as cellular automata, multi-agent and spatial statistics, etc. This research concentrates on the complexity in structural and functional changes, temporal comparability, spatial patterns and patio-temporal processes of urban growth. With remotely sensed imagery and secondary data, this research work presents a methodology for monitoring and evaluating land use changes over time. My methodology primarily comprises of morphology analysis, urban land cover structure change and spatial pattern analysis, using Shannon’s entropy approach. The outcome shows that the integration of multiple spatial indicators can improve the capacity for interpretation and evaluation. This case study reveals temporal variation in the spatial urban growth process. This work presents an innovative method for the temporal measurement of urban growth for comparing urban sprawl. The method comprises temporal mapping, data disaggregation, integration on spatial gravity, and global evaluation. The findings reveal that the macro patterns of urban sprawl can be interpreted and compared from micro urban activities. This research also shows that pattern, process and behavior must be integrated into a whole towards understanding the complexity in urban growth. My study presents a preliminary pattern of urban sprawl planning imperatives for the study area. The main objective of the thesis is to delineate an Urban Growth Boundary (UGB). This framework is implemented by using exploratory data analysis and spatial logistic regression and the combination is proven to have a strong capacity for interpretation. Project-based Shannon’s entropy method is used for interpreting the spatial and temporal logic between various projects forming the whole urban growth. The findings from this research suggest method that can use to delineate a boundary which can control the spatial growth of a city, which is focused on GIS based method.