Enabling carbon farming: a robust, affordable and scalable approach leveraging remote and proximal sensing

<p>The main hurdle in instrumentalizing agricultural soils to sequester atmospheric carbon is a development of methods to measure soil carbon stocks on farm level which are robust, scalable and widely applicable. Specifically, it is necessary that socio-economic barriers related to cost, usability and accessibility are overcome. We present the Wageningen Soil Carbon Stock pRotocol (SoilCASTOR), a method for soil carbon stock assessment using satellite data, direct soil measurements via mobile soil sensors and machine learning which can help overcome these socio-economic hurdles. The method has a low cost per hectare and uses plug-and play tools (soil scanner), which lower the threshold users need to overcome. The method has been tested and applied for multiple farms in Europe and the United states on agricultural fields with variable crop rotations, soil types and management history. Results show that the estimates are precise, repeatable and that the approach is rapidly scalable. Carbon stocks in the top 30 cm range between 1.8-6.1 kg C/hectare and resolution is up to 10x 10 meters. The precision of farm C stocks is below 5% enabling detection of SOC changes desired for the 4 per 1000 initiative. The assessment can be done robustly with as few as 0.5 samples (or 2-3 minutes) per hectare over a range of scales, for farms varying from 20 to 200 hectares.These findings can enable the structural and widespread implementation of carbon farming. This approach has recently been awareded the Bayer Grants4Tech innovation prize.</p>