Illitization of smectite in sedimentary systems, a process akin to 'reverse weathering', is a diagenetic process that has significant implications for sediment paragenesis and hydrocarbon exploration.However, the potential influence of chemical weathering on the illitization of smectite, and its possible control of the neogenesis of titanium (Ti)-oxides remain unclear.Altered volcanic tephra layers (i.e., K-bentonites) characterized by an interstratified illite-smectite (I-S) clay mineralogy serve as an excellent medium to investigate the illitization of smectite.In this study, we first investigated the fine structure of clay minerals and in-situ nano-mineralogy of This is the peer-reviewed, final accepted version for
Abstract Pedogenic weathering of aeolian materials plays an essential role in global nutrient and carbon cycling. A quick and effective approach for temporally high‐resolution and spatially large‐scale pedogenic investigations has long been needed. Here, we used visible and near‐infrared, mid‐infrared and sensor‐fused data to predict pedogenesis‐related soil properties (i.e., grain‐size distribution, clay‐mineral properties and geochemical ratios) in a thick loess sequence in central China. Sensor fusion was achieved at three different levels: (1) direct combination of spectral parameters (low‐level fusion; Fusion para ); (2) combination of spectral features selected by principal component analysis (middle‐level fusion; Fusion PCA ) and (3) fusion using outer product analysis (high‐level fusion; Fusion OPA ). Sensor‐fusion generally improves the model predictions for all soil properties, with increases in the values of the model efficiency coefficient (MEC) of 8% and the performance‐to‐interquartile range of 12%. Whole‐soil properties are optimally predicted with the Fusion para dataset using the random forest algorithm, yielding a mean MEC of 0.85. Spectral parameters D 2200 / D 1900 and AS 2200 are demonstrated as promising new pedogenic proxies, with higher values indicating more intense hydrolysis during pedogenesis. Spectral proxies along the loess sequence suggest that intense soil formation occurred during warm and humid interglacial periods when the East Asian summer monsoon intensified. The sensor‐fusion technique improved model performance for assessing mineral transformations and chemical weathering intensity, providing a quick and efficient means of interpreting pedogenic evolution, especially in the case of spatially large‐scale soil investigations. Highlights Fusion of VNIR and MIR spectra to model loess pedogenesis. Spectral modeling provides a robust surrogate for pedogenic evolution studies. Sensor fusion improves the performance of chemometric models. Sensor‐fusion models can reconstruct loess pedogenesis.
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