Soil organic carbon modeling in cropland under several climatic scenarios using machine learning in western India

Abstract

This study combines machine learning, remote sensing, Google Earth Engine and GIS to model soil organic carbon in western India under different climate scenarios. High-emission pathways project soil-carbon losses, while conservation farming practices may support soil health and carbon recovery. Practical relevance: Evidence for climate-adaptive land management and sustainable agricultural planning.