Introduction

Patterns and processes of globalization and consequent urbanization are the factors influencing contemporary land use trends and also posing challenges for sustainable land uses [9]. Analysis of landscape patterns  and  dynamics has become  the  primary objectives of  landscape, geographical and ecological studies in recent times.  Landscape changes involving large scale deforestation are the primary drivers of the climate change [52], [11] earth dynamics [51]. The spatial patterns of landscape transformation through time are undoubtedly related to changes in land uses [41]. Landscape changes are diverse but very often influenced by regional policies [6]. The  main  driving  factors  for global environmental changes are been  identified  as  agriculture  intensification  [17], [19], urbanisation  [40] in  the  context  of  local  policies [24,30,34]. The socio-economic impacts are often determinants of the type of land use within a given region, which in turn affect environmental issues [32], [35]. In order to address these urbanization challenges without compromising the environment values and their local sustainance, land use planning and necessary supporting data are crucial, especially to developing countries under severe environmental and demographic strains [12].

Urbanization is a irreversible process involving changes in vast expanse of land cover with the progressive concentration of human population. Urbanising landscapes will invariably have high population density that might lead to lack of infrastructure and provision of basic facilities. The  urban population  in  India  is growing at about 2.3% per annum with  the global urban population increasing from 13% (220 million in 1900) to 49% (3.2 billion, in 2005) and  is  projected  to  escalate to 60%  (4.9 billion)  by  2030  [42]. Population of Mysore is 1 million as per census 2001 compared to 0.653 million (1991).

The increase in urban population  is in  response  to  the growth  in  urban  areas  due  to  migration from either rural area or other cities.  There  are  48  urban agglomerations (Mega cities, Tier I)  having  a  population  of more  than  one million  in  India  (in  2011). Tier 1 cities have reached the saturation level evident from lack of basic amenities, traffic bottlenecks, higher concentrations of pollutants, higher crime rates due to burgeoning population. In this context, well planned Tier 2 cities offer humongous potential with the scope for meeting the basic amenities required. This entails thee provision of basic infrastructure (like roads, air and rail connectivity), adequate social infrastructure (such as educational institutions, hospitals, etc.) along with other facilities. Modeling and visualization of urban growth based on the historical spatio-temporal data would help in identifying the probable regions of intense urbanization and sprawl.

Urban sprawl implies a sharp imbalance between urban spatial expansion and the underlying population growth [5]. Sprawl  of  human  settlements   is  a  major  driving  force  of  land  use  and  land  cover changes  [3], [16] with detrimental impacts on natural resources and local ecology. Sprawl process entails the growth of the urban area from the urban center towards the periphery of the city municipal jurisdiction. These small pockets in the outskirts lack basic amenities like supply of treated water, electricity and sanitation facilities. Sprawl is associated with high negative impacts and especially the increasing dependency for basic amenities [50], the need for more infrastructure [5], the loss of agricultural and natural land, higher energy consumption, the degradation of peri-urban ecosystems etc., [23], [25], [27]. Understanding the sprawl over past few decades is crucial for the regional administration to handle the population growth and provide basic amenities while ensuring the sustainable management of local natural resources.

The information about the current and historical land cover/land use plays a major role for urban planning and management [54]. Mapping landscapes on temporal scale provide an opportunity to  monitor  the  changes,  which  is  important  for  natural  resource  management  and sustainable  planning  activities.In this context, “Density Gradient” with the time series spatial data analysis is potentially useful in measuring urban development [50]. This article presents the temporal land use analysis and adopts the density gradient approach to evaluate and monitor landscape dynamics and further explains the landscape pattern through use of landscape metrics.

Knowledge of the spatio-temporal pattern of the urbanization is important to understand the size and functional changes in the landscape. Spatial metrics were computed to quantify the patterns of urban dynamics, that aid in understanding spatial patterns of various land cover features in the region [33]. Quantifying the landscape pattern and its change is essential for monitoring and assessing the urbanization process and its ecological consequences [31], [20], [27], [46]. Spatial metrics have been widely used to study the structure, dynamic pattern with the underlying social, economic and political processes of urbanization [21], [22], [45], [53]. This has provided useful information for implementing holistic approaches in the regional land-use planning [48]. [1] reviews the spatial characteristics of metropolitan growth including analysis [2], [4], [14], [28] the study of urban landscapes.Applications of landscape metrics include landscape ecology (number of patches, mean patch size, total edge, total edge, mean shape), geographical applicationsby taking advantage of the properties of these metrics [15], [39], [44] and  measurement of ecological sustainability [43].

These studies also confirmed that Spatio-temporal data along with landscape metrics would help in understanding and evaluating the spatio temporal patterns of landscape dynamics required for appropriate management measures.

According to  the  City  Development  Plan (CDP),  a  20-year  vision  document for  Mysore,  there  has been  a  70%  increase  in  the  city’s spatial extent since  2001, resulting in the higher degree of sprawl at outskirts. Objectives of this study are to understand and interpret the evolving landscape dynamics through temporal analysis of land use land cover pattern taking 3km buffer, through spatial metrics.