[P1-15] Urban spatial dynamics and future projections using Earth Data and Cellular Automata Model with Artificial Neural Network Approach: A Case Study Karachi, Pakistan
Keywords:Remote Sensing, Cellular-automata, Artificial Neural Network, Simulation
The world has gone through unprecedented rapid urbanization in the last several decades, characterized by population increases. Cellular automata and artificial neural network models for urban growth simulation have succeeded in their flexibility and progression. The spatial dynamic of (LULC) triggered by rapid urbanization has become a major concern in the city, it may cause socioeconomic and environmental issues. According to the research findings, there was an increase in built-up land and a decrease in other land use features, both historically and according to predictions. From 1990 to 2020, about 423.67 km2 of the built-up area expanded, with a decline in other land features. Between 2020 and 2050, the built-up area is predicted to increase by 561.93 km2, while other land features are expected to decrease. Therefore, the city administration should focus on spatial planning for future urban growth to reduce the concentration of socioeconomic and environmental challenges.