Imagine trying to take a photo of your garden, but it's always cloudy. Most satellites can't see through clouds, but this tool combines regular photos with radar that 'sees' through the weather. It's like giving a farmer X-ray vision to know exactly when their crops need water or fertilizer, regardless of the storm outside.
Farmers in cloudy tropical regions cannot use standard satellite monitoring because clouds block the view. This leads to the excessive use of fertilizers and water, increasing costs and environmental damage.
A diagnostic tool and algorithms that merge optical, infrared, and radar (SAR) data to monitor crop health regardless of cloud cover.
If you are a software provider dealing with data gaps in cloudy tropical regions — this project developed a multi-sensor diagnostic tool that integrates SAR and optical data. This allows for continuous crop monitoring throughout the growing season, reducing the reliance on clear skies.
If you are a plantation manager dealing with high fertilizer costs — this project developed a monitoring method that reduced nitrogen use from 165 to 139 kg/ha in Colombia. This helps match inputs to actual crop needs, lowering the environmental footprint.
If you are a verification firm dealing with the difficulty of monitoring degraded land in the tropics — this project developed a physically based tool to monitor crop phenology and health. This ensures reliable time series data even in cloud-prone areas.
Based on available project data, specific pricing or implementation costs are not provided.
Yes, the project plans to transfer the use case to maize, sunflower, sugar beet, potato, and wheat in Ukraine.
Based on available project data, the IP and licensing terms are not specified.
The tool integrates multi-sensor Copernicus data, specifically combining SAR (Sentinel-1) and optical (Sentinel-2) signals early in the processing chain.
The project period runs from 2024-01-01 to 2026-12-31.
The consortium is heavily industry-driven with an 86% industry ratio, consisting of 6 industrial partners and 1 university. With 5 SMEs involved across 4 countries (NL, CO, ES, FR), the project is structured for commercial application rather than pure academic research, led by an SME coordinator (ELEAF BV).
Contact ELEAF BV in the Netherlands
Contact us to explore licensing for multi-sensor crop monitoring algorithms.
