Urban spatial growth modelling using geospatial technologies

Abstract

Urbanization, is a occurrence both unavoidable and vibrant in nature, remain to shape the way of the cities are seen universally. This research work presents a framework for incorporating Artificial Neural Networks (ANN) and geographical information systems that is implemented for modeling of urban growth and predicting the future developable land. Urban systems have been well-known as a non-linear complex structure. The Lucknow Planning Area has been identified as a study area for this research, the objective of this study are (i) study the various urban growth models (ii) to analyze the land use land cover change in Lucknow planning area, (iii) identification of causative factor responsible for urban growth (iv) to select appropriate urban growth model for calibration and generate future growth potential, (v) after the model result Master Plan (2031) will be revisited after obtaining the model result and future growth potentials would be find out, lastly (vi) suggest applicability of urban growth model in master plan preparation. In the fast growing world, the city of Lucknow in the state of Uttar Pradesh is come into contact with rapid growth in context of urbanization. Data base required for this ANN based research remote sensing data used for land use land cover study, while GIS is used to develop the spatial and predictor drivers and perform spatial analysis on the results. Shannon’s Entropy calculation apply for built form analysis and other data used for factors identified responsible for urban growth in Lucknow such as transportation network, mobility services, medical facilities etc. through existing maps. As per model requirement Euclidean distance of these factors have been calculated. The computer based growth model is calculated through ANN algorithm. ANN is to learn the patterns of development in the study area. The input data for model calibration were used, amount of built up and non-built up cells, and the physical factors of urban growth in Lucknow such as transportation network, mobility services, medical facilities, recreational facilities, important business district. The output of the model shows high agreement with master plan to predict the future urban growth. The high agreement validates applicability of geospatial technologies. Thus it can be concluded that inclusion of geospatial techniques in master plan preparation will accelerate the process of master plan preparation.