Introduction

Rapid urbanisation is quite alarming, especially in developing countries like India. Nature and human systems are getting affected due to growing urbanisation at all geographic scales (Herold et al., 2005). The rapid and often uncontrolled growth of the urbanising cities brings about numerous changes in the structure and functioning of landscape (Solon, 2009). Urban sprawl, a consequence of socioeconomic development under certain circumstances, has increasingly become a major issue facing many metropolitan areas (Ji, 2006). Bangalore is one among the fastest urbanising cities in Asia, undergoing redevelopment for economic purposes and is witnessing tremendous pressure on the infrastructure, civic amenities, public services, etc. The growing migrant population, increasing number of Information Technology and Bio-Technology firms, and real estate projects are demanding more resources within the city, forcing it to expand both horizontally and vertically leading to serious problems like scarcity of food, informal settlements, environmental pollutions, destruction of ecological structures, unemployment etc. The unprecedented growth and urban sprawl are often unnoticed by the planners, as they are unable to visualise this type of growth patterns. Since patterns are fundamental to many of the spatial-temporal relationships that we seek to discover, it is important to understand the factors and trend that influence the interpretation of the urbanising landscape. Therefore, characterising and understanding the changing patterns of urban growth is critical, given that urbanisation continues to be one of the major global environmental changes in foreseeable future (Rashed, 2008).

The spatio temporal trends of urban sprawl can be characterised by remotely sensed (RS) images acquired through space-borne satellites. Their large area coverage and repeat viewing provide information over a considerable range of spatial and temporal resolutions for mapping land cover (LC) resources (Mas, 2010). RS has the potential to provide additional levels of information about the links between land use and infrastructure change and a variety of social, economic and demographic process (Herold, et al., 2005). RS intertwined with time series modeling and spatial metrics (urban indicators) are very effective to understand the growth of urban areas for administration and future planning. Derivation of spatial metrics (landscape pattern metrics) from LC maps (Saura and Castro, 2007) aid in studying spatial urban patterns, sprawl, specific spatial model applications and analysis of spatio-temporal urban dynamics at different scales. They are used to quantify the spatial heterogeneity of individual patches, of all patches belonging to a common class, and of the landscape as collection of patches (Herold et al., 2005). They also aid in improved representation of heterogeneous characteristics of urban areas and in understanding the impact of urban development on surrounding environment. A wide variety of indices have been developed to characterise the landscape, some of which describes the proportion of landscape with a particular LC class, the size, number, and perimeter of each LC patch, and the complexity of the shape of the patch (Rashed, 2008). These metrices can be spatially non-explicit, aggregate measures, still reflecting important spatial properties, and, when applied to the multi-scale or multi-temporal data sets, they can be used to analyse and describe change in the degree of spatial heterogeneity (Herold et al., 2005). Since most of the metrics are based on geometric properties of landscape elements, that can provide simple quantitative measurements of a complex pattern, they are frequently adopted in landscape ecological research.

Objective : The objective of this paper is to describe changes in landscape structure and quantify the spatio-temporal urbanisation pattern in Greater Bangalore using spatial metrics. The analysis aims to answer the following questions:

1. What is the land use change from 1973 to 2010?

2. How do the landscape metrics for urban areas change over time?

3. Are there significant differences in sprawling pattern in different directions across the city?

4. Which of the metrices highlight significant variations in direction wise developmental pattern in the city?