Predicting Prayagraj's Urbanization Trajectory using CA-ANN Modelling: Population Pressures and Land Use Dynamics.

Area of Science:

• Environmental Science
• Urban Planning
• Remote Sensing

Background:

• Land Use/Land Cover (LULC) dynamics are vital for resource management and conservation strategies.
• Understanding LULC changes is crucial for addressing urban growth pressures and balancing competing land uses.

Purpose of the Study:

• To assess and forecast LULC dynamics in Prayagraj city, India, from 1988 to 2028.
• To analyze the impact of human population pressure, agriculture, and urbanization on the city's landscape.
• To provide insights for sustainable urban planning and resource management.

Main Methods:

• Utilized long-term spatiotemporal Landsat datasets (1988-2018) for LULC change analysis.
• Employed Cellular Automaton (CA) and Artificial Neural Network (ANN) models for future LULC prediction.
• Incorporated exploratory layers (roads, educational institutes, slope, river, etc.) for model training and validation.

Main Results:

• Significant increase in Built-land (10.03%) and decrease in Agriculture land (-13.43%) and Forest land (-3.03%) between 1988 and 2018.
• Predicted a further 2.83% increase in Built-land by 2028, primarily impacting agricultural and forested areas.
• Model validation achieved a high accuracy of 90.29% with a kappa value of 0.87.

Conclusions:

• Prayagraj's LULC is undergoing rapid transformation driven by urbanization and population growth.
• Future LULC trends indicate continued pressure on natural and agricultural resources, demanding proactive urban planning.
• Delineating future development zones is essential for environmental sustainability and economic prosperity in Prayagraj.