Satellite data for sustainable farming

Kermap contributes to sustainable farming initiatives by providing actionable satellite data. We combine expertise in remote sensing and AI-engineeering to deliver quick, large-scale information on crop rotation and health. Our indicators and datavisualization tools facilitate crop monitoring and the quantification of environmental payments for players involved in the transition to sustainable agriculture.

Improved crop inventory

Our innovative AI models enhance traditional crop inventory using remote sensing, with gains in accuracy, velocity and scalability.

These deep learning techniques for instance proved successful in producing the first map of dominant crops in 2020 at plot level, with the corresponding stats on 11 European countries.

Key data for sustainable farming

Thanks to our AI-models, key data for sustainable agriculture contained in satellite imagery is automatically extracted from remote sensing data.

  • Soil cover identification : dominant crop classification, cover crop typology.
  • Long-terme plot analysis : cover rate and duration, heterogeneity, soon to be followed by soil moisture and yield rates

Then made easily accessible in our visualization tools : dashboards or cloud platforms, such as our Nimbo geobrowser and API.

Promoting environmental services

You are a public actor, company, farm co-op, or non-profit organization involved in a greening or payment for ecosystemic services programme (PES) ? Our crop monitoring processes provide you with efficient tools and relevant indicators to support farming professionals towards the adoption or sustainable agricultural practices.

Information produced by Kermap supports agroecology initiatives relying on soil conservation – such as EarthWorm Foundation’s Sols Vivants programme. Besides, Earth observation data can also contribute to water quality preservation, chemical input limitation or carbon sequestration.

Crop inventory : identification of two lots, corn in green, wheat in yellow

Carbon offset

Objective criteria to calculate carbon offset ? Satellite data have some in store. We provide large-scale monitoring of farming practices fostering soil carbon storage, through crop rotation or cover crops among others.

These indicators produced by remote-sensing supply key contributions to carbon offset measurement. Players active in the carbon credit field can thus improve the reliability of their initiatives to encourage the reduction of CO2 emissions. One illustration is our collaboration with MyEasyFarm for its MyEasyCarbon solution. This new carbon monitoring application designed for field crop producers uses data sourced by Kermap to automatically document interventions at plot scale.

Discover our solutions

Learn more on our crop monitoring techniques to promote sustainable farming.

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