Applying the Artificial Intelligence in forecasting the Urban growth for Al-Kut City, Iraq

Abstract

The integration of artificial intelligence (AI) with geographical and spatial data analysis enhances our understanding of the environment and addresses spatial challenges. Geospatial Artificial Intelligence (GeoAI) leverages advanced modeling and systematic visualization to monitor and predict spatial realities. This research explores the use of GeoAI in determining the directions of spatial expansion within a study area, specifically by integrating Artificial Neural Networks (ANNs) and Cellular Automata (CA) using MATLAB for data processing and analysis. The objective is to explore how these models interact to provide accurate predictions of urban growth.

Intelligent algorithms and models assist in urban planning by identifying the type, direction, and extent of future expansions. Machine learning, a branch of AI, is employed for high-accuracy classification and land use variability analysis. MATLAB software is utilized to train data and predict future land use changes. An analysis of Landsat satellite images from 2003, 2013, and 2023 was conducted using machine learning to classify land use, calculate area percentages, and illustrate the urban expansion in the study area. The findings indicate an increase in urban land from 8% in 2003 to 20% in 2023, demonstrating significant growth.