Deep learning for predicting soil properties and climate change

Soil is a fundamental natural resource that not only provides essential nutrients, minerals, and elements necessary for plant growth but also plays a vital role in climate regulation and broader ecosystem functioning. This master's thesis aims to improve the practises of modern Artificial Intelligence (AI) methodologies in Digital Soil Mapping (DSM) practices across Türkiye by integrating key environmental variables such as land cover, topography, climate data, and other spatial factors. To achieve this objective, a comparative analysis of seven different machine learning models was conducted to evaluate their performance in predicting soil properties based on these variables.