Machine Learning Approach to LULC Forecasting

This study explores the prediction of changes in Land Use and Land Cover (LULC) over the period of 2000 to 2040 in a region of Algeria. The research combines remote sensing data and machine learning techniques. Landsat image classification is applied to assess LULC changes for the years 2000 to 2020. In addition, a novel approach is employed to account for temporal factors influencing LULC changes in 2025, 2030, and 2040. Promising results are reported and discussed.