Disentangling the effects of vegetation and water on the satellite observations of soil organic carbon stocks in western European topsoils

Abstract. The performance of models based on satellite observations of soil organic carbon (SOC) stock in European soils is seriously limited by the complexity of natural land surfaces. Therefore, disentangling the SOC stock from other natural land surfaces including vegetation and water bodies has become a rather difficult but necessary task. This study proposed a novel and promising approach intended to resolve this frustrating problem. Based on a series of spectral narrowing, unchanging, and enlarging processes, 23,914,845 sets of SOC models were developed both for vegetation fuzzy disentangling and water fuzzy disentangling. The optimal model was obtained through comparison and was determined as the model that ultimately performed obviously better than the unfuzzified model. This model simulated the per-unit and total SOC stocks in western European topsoils as 99.742 t C ha⁻¹ and 9.373 Pg, respectively. In comparison with the results of previous studies, the gaps in the simulated per-unit SOC stocks across the western European countries were considerably narrower (83.673–104.334 t C ha⁻¹). The outstanding model performance and stable simulated per-unit values are the result of disentangling of the vegetation and water cover. This study proposed a valuable reference solution for disentangling the SOC stock from complex natural land cover.