Urbanization is the physical growth of urban areas or the territorial progress of a region as a result of increase in population due to migration or peri-urban concentration into cities. Urbanization occurs as individual, commercial, and governmental efforts to improve the opportunities for jobs, education, housing, and transportation.  Influence of economic, political, geography and social factors among other factors that cause rural to urban transformation with high concentration of population at a particular place (Ramachandra et al., 2012a, 2012b; Bhaskar, 2012; Ramachandra, 2015a). Unpredictable and unprecedented urbanization exerts pressure on natural resources as open and green ecological spaces gets transformed into residential, industrial, and commercial use, threatening the sustainability of natural resources, which requires an immediate attention of the regional planners (Duh et al., 2008, Desai et al., 2009; Ramachandra et al., 2012a), to improve decision-making and ensure sustainability of natural resources. Understanding these dynamic processes requires monitoring of historical land cover changes and this also aid in the forecasting of urban growth with various plausible policy decisions (Shen et al., 2011).

The underlying effect of unplanned urbanisation is the dispersed or haphazard growth, often referred as urban sprawl (Huang et al., 2007), which leads to inefficient resource utilization (Ramachandra et al., 2012a, 2012b; Bharath S, 2012; Ramachandra and Bharath, 2013; Ramachandra et al., 2015b) and local ecology. This spurts major ecosystem changes affecting the provision of ecosystem goods and services (Grimm et al. 2008) due to the creation of fragmented suburbs and urban expansion near the fringes (Schwarz, 2010), resulting in the unsustainable use of natural resources leading to erosion of natural resources stock (Shen et al., 2011). The consequence of unplanned urbanisation is the loss of water-bodies, natural vegetation, agricultural lands (Wear et al. 1998), decline in the availability of surface as well as ground water (Ourso, 2001: Ramachandra et al., 2012a, 2012c), health impacts due to higher pollutants (Horowitz, 2002) apart from enhanced carbon and ecological footprints. This necessitates understanding of urban revolution that has culminated urban processes over years (Ward et al. 2000). Over the past three decades, urban sprawl and its impacts have attracted attention of regional planners and decision makers (Frenkel and Orenstein, 2012), which has also helped in the analysis of urbanisation process while taking advantages in advancements in geo-spatial technologies. 

Remote sensing technology through space-borne sensors provides spatial data at regular intervals and this data is available since 1970’s, which has been playing an important role in monitoring the landscape dynamics. Measurements and analysis of urban areas from remotely sensed data aids as an unbiased tool for urban landscape dynamics analyses and allow the user community to overcome data inconsistencies (Yang and Lo, 2002; Serra et al., 2003; Xian and Crane, 2005; Weng, 2007; Huang et al., 2007; Ramachandra et al., 2012b). Spatio-temporal data have been useful to generate information for assessing urbanisation process through explicit understanding of urban extent and structure (Sudhira et al., 2004; Maktav et al. 2005; Potere et al. 2009; Ramachandra et al., 2012a). Spatio-temporal patterns of urbanisation have been captured through landscape metrics such as density, continuity, concentration, clustering, centrality, nuclearity, mixed uses, and proximity (Galster et al., 2001; Frohn and Hao, 2006; Uuemaa et al., 2009), and urban sprawl through density, scatterness, and mixture of land use. Landscape metrics have been useful in measuring and understanding spatio-temporal patterns of the landscape dynamics for various applications (Dietzel et al. 2005, Weng 2007; Charles et al., 2005; Jat et al., 2008a, b; Deng et al.,2009; Ramachandra et al., 2012b, Ramachandra et al., 2016). Spatial metrics and indices such as Shannon entropy is efficient tool in identifying sprawl regions and vital insights of the urban growth (Ramachandra et al., 2012a, c; Lata et al., 2001; Sudhira et al., 2004, Ramachandra et al., 2014a, b)

India is the 2nd most populated country in the world and is undergoing rapid urbanization with drastic land use land cover (LULC) changes in recent years. Urbanization process has gained momentum with the government’s push for economic growth subsequent to globalization during early 1990’s. Megacities in India are urbanising at an unprecedented and irreversible rate, as the global proportion of urban population has increased from 28.3% in 1950 to 50% in 2010 (World Bank, 2011). Urbanisation of the Indian metropolis fuelling immigration from other cities results in the conversion of natural resources such as forests, open spaces and agricultural lands to urban impervious regions. The irregular and unplanned development of metropolitan cities has an impact on the peri-urban environment with the gaining impetus towards the destruction of open spaces (parks, wetlands, etc.)  For infrastructure and developmental activities, which has created imbalance in the ecosystem (Bhaskar, 2012) evident from increased local temperature, decline in groundwater table, enhanced pollutants, unabated dumping of solid waste, contamination of land, water, etc. These cities lack adequate infrastructure facilities such as sanitation, housing, improper drainages, transportation issues etc., (Desai et al., 2009; Ramachandra et al., 2012b). This necessitates advance understanding of urbanisation process by decision makers and planners to plan towards sustainable smart cities.

Urbanisation process is assessed through temporal land use analyses and through computation of spatial metrics in gradients of each zone. The study region includes the current spatial extent of a city with 10 km buffer. Buffer region is considered to account the growth in peri-urban region of a city. Main questions addressed are (i) the role of spatio-temporal data acquired through space-borne sensors to monitor urbanisation, and (ii) the effectiveness of spatial metrics to characterize urban growth.

This aided in the understanding of spatial urban growth for modelling the future likely urban dynamics in the mega metropolitan Indian cities.