CONCLUSION

Karnataka government’s initiative and focus to develop the major tier II cities such as Gulbarga in order to decongest the burgeoning Tier 1 city, Bangalore, has posed challenges to the district planners to accommodate the developmental activities at a higher speed while ensuring sustainability of natural resources. Availability of temporal spatial data has aided in monitoring the temporal land use dynamics. Spatial metrics in conjunction with the density gradient approach have been effective in capturing the patterns of urbanization at local levels. The techniques would aid as decision-support tools for unraveling the impacts of classical urban sprawl patterns in Gulbarga. A set of spatial metrics describing the morphology of unplanned areas have been extracted along with temporal land uses. The extracted indices have indicated the areas of high likelihood of ‘unplanned growth’ considering the three dimensions (size/density/pattern).

Land use assessed for the period 1973 to 2010 using Gaussian maximum likelihood classifier highlight that there has been a significant increase (22%) in urban area, with consequent reduction in vegetation cover. Shannon entropy computed using temporal data illustrates that Gulbarga city is showing the signs of sprawl in all directions with the gradual increase of entropy value. Spatial metrics at landscape level reveal that the landscape had a highly fragmented urban class and started clumping to form a single square in in 2002 especially in NE and NW direction in all circle and few inner circles in SE and SW directions, conforming to the other landscape metrics.

The urban pattern highlights the need for policy interventions for integrated urban planning considering land use, mobility and the sustainability of natural resources. This would help in appropriate mitigation measures in addressing traffic congestion, escalation in infrastructure costs, reduction of environment quality and social interactions. These techniques help to visualise the growth pattern and aid decision makers, stakeholders and planners in providing appropriate infrastructure and creating urban boundaries with the prior knowledge of thresholds, which support smart growth.

Acknowledgement

We are grateful to NRDMS Division, The Ministry of Science and Technology (DST), Government of India and Centre for infrastructure, Sustainable Transportation and Urban Planning (CiSTUP), Indian Institute of Science for the financial and infrastructure support.