Soil organic carbon prediction using satellite imagery
(2023)
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- Abstract
- The concern about the role of soils in the global carbon budget and the effects of soil organic carbon (SOC) decline on soil quality has been incorporated in international treaties. Initiatives such as ‘4 per 1000 Soils for Food Security and Climate’ or ‘The Farm to Fork’ strategy are being implemented in the context of the Paris Agreement to mitigate climate change. This requires a robust measurement, reporting and verification (MRV) system to track that the policy goals are being met. However, difficulties arise when implementing MRV systems, as cost-effective and accurate SOC maps that cover large areas with high spatial and temporal resolution are needed. This PhD thesis assessed the potential of remote sensing to provide a tool for a rapid, repeatable and cost-effective SOC monitoring in croplands. The process of deriving a final soil product is however hindered by the conditions of the soil surface, which needs to be bare, dry and smooth. Therefore, the first objective was to assess the effects of disturbing factors such as soil moisture, crop residues and soil crust on SOC prediction from Sentinel-2 satellite imagery. Secondly, we tested the potential of the created SOC maps as a tool for detecting areas under conservation agriculture. This resulted in an original work as we have: - Defined a methodology that allows obtaining pure soil pixels from Sentinel-2 imagery in Belgium, and - Used a Sentinel-2 derived SOC map and uncertainty map to evaluate the difference in SOC content of conservation agriculture fields from conventional agriculture fields
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Citations
Dvorakova, K. (2023). Soil organic carbon prediction using satellite imagery. https://hdl.handle.net/2078.5/30608