Roorkee, Feb 11 (IANS): Researchers from the Indian Institute of Technology (IIT) Roorkee have developed an advanced predictive model to assess land cover changes.

The model developed using Cellular Automata (CA) and Geographic Information System (GIS) techniques was used to examine urban expansion in Ahmedabad, Chennai, Jaipur, and Surat over the past two decades.

The study, published in the journal Discover Cities, highlights the rapid pace of urbanisation and underscores the critical need for data-driven planning to guide sustainable growth. The model incorporates essential urban growth factors such as population density, proximity to central business districts, major roads, and drainage systems, enhancing the accuracy of urban development predictions.

"Sustainable urban planning is vital for India's rapidly expanding cities. This study provides a scientific framework for predicting urban growth patterns, enabling policymakers to make informed decisions that promote both infrastructure development and environmental sustainability," said Prof. Kamal Kishore Pant, Director of IIT Roorkee.

A central aspect of the research involves mapping impervious surfaces -- areas covered by buildings and roads that obstruct natural water infiltration. This analysis identifies potential urban flooding risks and offers strategies to mitigate environmental concerns.

"By integrating GIS and machine learning, our model not only offers high-accuracy predictions but also provides valuable insights into sustainable urbanisation strategies. This research will help smart city planners mitigate the negative effects of unplanned urban sprawl," said Prof. Rahul Dev Garg, Dean of Resources & Alumni Affairs and Faculty in the Department of Civil Engineering at IIT Roorkee.

This study is poised to become an essential tool for urban planners, policymakers, and environmentalists, guiding the sustainable development of India’s smart cities.

The model marks a significant step forward in leveraging technology for sustainable urbanisation and presents a scalable approach for cities across India to follow.