Abstract
Abstract. This study aims to map the urban area in and around Pune region between the year 1991 and 2010, and predict its probable future growth using remote sensing and GIS techniques. The Landsat TM and ETM+ satellite images of 1991, 2001 and 2010 were used for analyzing urban land use class. Urban class was extracted / mapped using supervised classification technique with maximum likelihood classifier. The accuracy assessment was carried out for classified maps. The achieved overall accuracy and Kappa statistics were 86.33 % & 0.76 respectively. Transition probability matrix and area change were obtained using different classified images. A plug-in was developed in QGIS software (open source) based on Markov Chain model algorithm for predicting probable urban growth for the future year 2021. Based on available data set, the result shows that urban area is expected to grow much higher in the year 2021 when compared to 2010. This study provides an insight into understanding of urban growth and aids in subsequent infrastructure planning, management and decision-making.
Highlights
The land use change in urban area is a composite process
Accelerated urban expansion is usually associated with the social-economic factors
The main change of land use in these areas can be described as other type of land use converting into urban land
Summary
The land use change in urban area is a composite process. Several factors influence this process, including both physical aspects and human aspects. The main change of land use in these areas can be described as other type of land use converting into urban land. As a result, increased research interest is being directed to the monitoring of urban growth using GIS and remote sensing techniques. Remote sensing is increasingly used for identifying and analysis of urban expansion since it is cost effective and technologically efficient. In recent years, these methods have progressed and have been widely used in management of natural resource and urban planning
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