A near real-time spatial decision support system for improving sugarcane monitoring through a satellite mapping web browser

Abstract

The global importance of sustainable sugarcane as a source of food and energy has driven the development of decision-making tools based on remote sensing (RS) to improve crop management. An approach in agricultural lands is the implementation of spatial decision support systems (S-DSS) for crop monitoring. However, most of these systems are designed for global or regional scales, limiting their applicability to local contexts with specific requirements. This study proposes a methodology to address some weaknesses associated with the underuse of S-DSS by integrating end-user requirements into the design process. To achieve this an easy-to-use near real-time S-DSS was developed, tailored to the needs of two sugarcane cooperatives in Costa Rica, validated with real data and field work, and adapted to three management scales (cooperative, farm and plot). Our Sugarcane Satellite Tracking (SugarSaT) provides two core tools: sugarcane harvest progress monitoring and an early warning system. The results validated that SugarSaT offers a suitable approach for the monitoring of sugarcane plantations that uses current and historical satellite data. Regarding the harvested area, more than 93 % of plots was correctly identified when 100 % of the sugarcane was delivered to the mill whereas about the early warning system, a plot test considering anomalies caused by bloom achieved an overall accuracy of 75.3 %. A usability test revealed that 83 % of the surveyed agronomic advisors believed that SugarSaT is suitable for integration into their daily activities. In conclusion, this S-DSS represents a significant step forward in sugarcane monitoring, enabling agronomic advisors to leverage satellite imagery for spatially informed decision-making while balancing scientific insights with the practical needs of end-users.