Creation of Geospatial Database Farming Systemusing Machine Learning

The integration of geospatial data and machine learning techniques has revolutionized agriculture by enabling data-driven decision-making and precision farming practices. This paper presents a comprehensive framework for the creation of a geospatial database farming system powered by machine learning algorithms. By harnessing diverse sources of geospatial data, including satellite imagery, soil samples, weather data, and topographical information, the system facilitates predictive modeling for crop yield estimation, soil health assessment, and pest management. Through case studies and empirical analysis, the effectiveness and applicability of the proposed system are demonstrated in improving agricultural productivity and sustainability.