REMOT

Effective Managemenet of Irrigation Sectors Using Earth Observation Technologies

Introduction

REMOT aims to provide an innovative method for optimizing irrigation management in vineyards by globally inferring plant water stress using Earth Observation (EO) technologies. This integrated tool uses a constrained optimization model to determine the optimal water volume for each irrigation sector, maximizing efficiency while minimizing water consumption.

Objetive

Develop an innovative method for optimized vineyard irrigation management by globally inferring plant water stress using EO technologies.
Perform this inference through the analysis of temporal series of vegetation indices derived from satellite imagery (Sentinel-2 and Menut).
Use the results to plan targeted field inspections and guide on-the-ground irrigation actions efficiently.

Space-driven Innovation

The REMOT project exploits advanced Earth observation technologies for precise irrigation sectors management. It is primarily based on Sentinel-2 imagery, while the Menut nanosatellite provides higher spatial resolution (4.75 m) and RedEdge bands, enabling analyses not possible with Sentinel alone. By combining both data sources, REMOT increases temporal resolution, reduces cloud-related gaps, and allows a rigorous comparison of techniques.

Impact on climate resilience

REMOT contributes significantly to climate resilience by enabling optimized and efficient management of water resources, which are increasingly threatened by drought and regulatory constraints. By minimizing water use at the sector level, the project directly supports SDGs 2, 12, and 15, fostering sustainable agriculture and effective resource stewardship.

This precise water management approach enhances the viticulture sector’s competitiveness and long-term viability in the face of climate change.

From Lab to Market: Clients and Commercial Roadmap

The solution has direct and immediate market potential. The REMOT project was conceived with a clear vision of real-world applicability and commercial scalability. Developed in close collaboration with AGROPIXEL and RAVENTÓS CODORNÍU, the solution bridges the gap between advanced Earth observation research and practical application in precision viticulture.

Its modular, data-driven design allows for easy scalability to other woody crops (olive trees, almond trees, fruit trees) and wider adoption within the agricultural sector. This initiative guarantees a direct path from the laboratory to the market, strengthening the Catalan NewSpace ecosystem and enabling the transition to more efficient, data-driven, and sustainable agriculture.