Web-Based Geographic Information Systems for Precision Agriculture in Sugarcane Farming: A Comprehensive Review

Abstract

This review focuses on the role of the web-based Geographic Information System (GIS) in sugarcane precision agriculture. Climate change, resource depletion, and market uncertainties have affected production; meaningfully, precision agriculture technologies can be solutions to reduce resource use and increase yield. The innovations, applicability, advantages, and challenges of web GIS platforms applied to sugarcane are reviewed and systematically analyzed in this paper based on literature spanning the years 2015 to 2024. The findings demonstrate that web GIS aids decision-making at the farm level by giving access to spatial data in real-time, as illustrated by the cases reducing fertilizers by 25% and improving water-use efficiency by 15-20%. Machine learning enhances these capabilities: yield predictions up to R-squared = 0.82, while disease detection achieves 95% accuracy using UAV imagery. This notwithstanding, barriers to adoption still prevail, such as high initial investment, technicality, and connectivity limitations in the rural landscape. Future research should, therefore, target user-interface functions, AI integration, and higher accessibility to cascade benefits widely across the globe. This review explains how web-based GIS can elevate sugarcane farming toward sustainability and efficiency.