Spatio-temporal Urban Growth Modeling of Jaipur, India

Abstract Urban growth is a spatial and dynamic process that tends to increase the priority of urban planning for developing cities with a fast growing population and economy. Unplanned and illegal urban growth degrades the quality of the urban environment for city residents; therefore, adequate information and advanced technologies are required for better implementation of planning policies. The use of temporal data is indispensable for observing urban growth and for the planning of a city. The inclusion of remote sensing data is advantageous for mapping and monitoring urban growth in different periods. In this study, the urban growth of the city of Jaipur, with its spatial and temporal changes, was mapped over a period of 16 years (1989–2000 and 2000–2005) using Landsat satellite data. This study focuses on the further classification of the urban areas into different categories on the basis of density, use, and association by implementing a rule-based classification system on remotely sensed data. The Markov method, geographic information systems (GIS), and remotely sensed data were integrated to quantify urban expansion and the transition in the urban density of the different urban land use categories. Statistical tests were used to establish the importance of the Markov model for changes in land use. The results reveal that urban land development in Jaipur increased by 63 percent from 1989–2005, with an increase in density indicated by urban land-use classes, while an increase in the suburban class implied growth in the urban areas along the city periphery. The transition of land use indicates that urban areas are rapidly expanding as a result of the conversion of agricultural and barren land surrounding the city into urban areas. The scenario analysis quantified the increase in unplanned and informal urban growth in the future, which may have an impact on existing planning policies for the development of the city.