Addressing The Impact Of Land Use Land Cover Changes On Land Surface Temperature Using Machine Learning Algorithms

This article discusses the use of machine learning to predict future patterns in land use and land surface temperature changes in Kabul province, Afghanistan. By analyzing past trends and utilizing SVM and CA-LR models, the study aims to provide insights for urban planning and development in the region. The study also highlights the economic importance of Kabul province and its industries, which may be impacted by these changes.