The role of soil forming factors (time, parent material, climate, biota, topography) on soil processes has commonly been studied using soil sequences where only one factor varies between sites. However, when multiple factors change, it becomes difficult to partition the importance of different soil forming factors for soil formation. We show for an altitudinal gradient how proximal sensing (portable XRF, Fourier-Transform Infrared [FTIR]), multivariate statistics and Bayesian mixing modelling can help to quantify the importance of two soil forming factors. First, we confirmed the existing qualitative soil-landscape model of concomitant shifts in parent material (greywacke loess to mafic volcanics) and climate (higher precipitation) with altitude, leading to increases in pedogenic oxides, soil carbon, and soil Fe, while Si concentrations and pH declined. Second, we applied a mixing model using immobile elements as parent material tracers to quantify the parent material contribution in soils across our gradient. Third, we conducted a variation analysis to determine how much variation in the soil FTIR spectra could be explained by parent material and climate. Parent material alone explained 31% of the variation, climate alone only 9%. However, if we had only considered climate as explanatory variable, it would have accounted for almost half of the total variation (41%) because of the strong interaction between climate and parent material, and therefore concealing the leading role of parent material. Given that parent material is often omitted in modern digital soil mapping, our results emphasize the importance of parent material as a predictor of spatial soil distribution.