Soil organic carbon (SOC) is important in the global carbon cycle. Accurate estimation of SOC content in cultivated land is a prerequisite for evaluating the carbon sequestration potential and quality of soils. However, existing SOC prediction studies based on hyperspectral remote sensing neglect the spectral response of the physical properties of surface soil, leading to inadequate model generalization. With the exponential growth of remote sensing data, the development of pixel-level soil spectral correction methods based on multi-source remote sensing data has become an interesting and challenging topic. This method aims to minimize the effect of soil physical properties on spectra, thus addressing the poor spatiotemporal transferability of SOC prediction models due to uncertain variations in surface soil physical properties. In this study, a soil spectral correction strategy is constructed using satellite hyperspectral image (HSI) and synthetic aperture radar (SAR) images through multi-order polynomial regression and convolutional neural networks. This strategy considers soil physical variables such as soil moisture (SM) content and root mean square height (RMSH) of soil surface roughness. The soil spectral correction model and SOC content prediction model were established using 80 soil samples collected from Site 1. Afterward, the performance and transferability of both models were verified using the remaining 25 samples from Site 1 and 50 samples from Site 2. The results showed that: 1) The effect of SM and RMSH on the soil pixel spectrum can be significantly reduced after correcting HSI using soil spectral correction strategy. The correlation coefficients between the corrected pixel spectrum and the ground-based spectrum increase by over 60 % compared with those between the original spectrum and the ground-based spectrum. 2) Soil spectral correction improves the prediction accuracy and mapping capability of HSI for SOC content, with the highest RP2 of 0.743 and RMSEP of 3.455 g/kg at Site 1. 3) Compared with the original HSI-based SOC prediction model, the soil spectral correction strategy based on multi-order polynomial and convolutional neural network reduced the RMSEP of SOC prediction results at Site 2 by 5.082 g/kg and 5.454 g/kg, and the RP2 increased by 0.390 and 0.409, respectively. 4) When predicting SOC content from raw HIS, SM and RMSH contribute to more than 60 % of the bias, with SM having a larger bias than RMSH. The findings of this study emphasize the influence of soil physical properties on SOC prediction and contribute to the existing research on SOC mapping using HSI and SAR data.
The mountainous areas of Southwest China have the characteristics of valley deep-cutting, a large topographic gradient, complex geological structures, etc. With the development of infrastructure construction in the area, the construction of bridges across valleys has gradually increased, and the phenomenon of slope failure occurs more and more frequently. As the weak interlayer, the fault fracture zones have a significant influence on the geological structure and stability of slopes, while the complexity of the mechanism of the deformation and failure of slopes increases with the combination of the development of the fracture zones and toppling deformation. This paper took the toppling bank slope of bridge foundations developed with fault fracture zones in Lancang River as the research object. Through an on-site field survey and geological survey technologies, it identified the distribution range of the fracture zones on the bank slope and determined the characteristics of the rock mass in the fracture zones. A stability evaluation model for the bank slope of the bridge foundations was established using the limit equilibrium method and discrete element method. Based on the two-dimensional limit equilibrium analysis, the potential failure modes of the bank slope were explored, and the stability of the bank slope under bridge loads was calculated. Through the three-dimensional geological model of the bank slope, including the fracture zones and toppling bodies, the three-dimensional discrete element numerical simulation method was adopted to simulate and calculate the deformation and failure process of the bank slope under different bridge loads and working conditions. According to the calculation results, the influence of bridge loads and reservoir water on the stability of the bank slope was analyzed from the perspectives of displacement, plastic zone, stability coefficient, and other factors. The formation process of the plastic zone and the development of the sliding surface were revealed, the incentive mechanism of bridge loads and reservoir water on the deformation and failure of the bank slope was analyzed, and the influence of fault fracture zones on the stability of the bank slope and the development of toppling deformation was determined. The results indicate that the fault fracture zones are important geological structures that affect the deformation and failure of the bank slope as a weak interlayer. Under the influence of bridge loads and reservoir water, the stability of the bank slope is affected by the quality of the rock mass and the development of the fault fracture zones, resulting in the unmet need for safety requirements and maybe leading to instability. Based on the calculation results of the stability evaluation prediction model for the bridge foundation bank slope and the engineering geological conditions, the bridge scheme has been selected.
Mining causes damage to the soil and rock mass, while rainfall has a pivotal impact on the mining slope stability, even leading to geological hazards such as landslides. Therefore, the study evaluated the mine landslide stability and determined the effectiveness of the treatment measures under the impact of pore water pressure changes caused by rainfall, taking the Kong Mountain landslide in Nanjing, Jiangsu Province, China, as the research object. The geological conditions and deformation characteristics were clarified, and the failure mechanism and influencing factors were analyzed. Also, the landslide stability was comprehensively evaluated and calculated utilizing the finite element-improved limit equilibrium method and FLAC 3D 6.0, which simulated the distribution of pore water pressure, displacement, etc., to analyze the influence of rainfall conditions and reinforcement effects. The results indicated the following: (1) Rainfall is the key influencing factor of the landslide stability, which caused the pore water pressure changes and the loosening of the soil due to the strong permeability; (2) The distribution of the pore water pressure and plastic zone showed that, during the rainfall process, a large area of transient saturation zone appeared at the leading edge, affecting the stability of the whole landslide and led to the further deformation; (3) After the application of treatment measures (anti-sliding piles and anchor cables), the landslide stability increased under both natural and rainfall conditions (from 1.02 and 0.94 to 1.38 and 1.31, respectively), along with a reduction in displacement, plastic zones, etc. The Kong Mountain landslide, with the implemented treatment measures, is in good stability, which is in line with the evaluation and calculation results. The study provides certain contributions to the stability evaluation and treatment selection of similar engineering under rainfall infiltration.
Real-time imaging of transient structure of the electronic excited state is fundamentally critical to understand and control ultrafast molecular dynamics. The ejection of electrons from the inner-shell and valence level can lead to the population of different excited states, which trigger manifold ultrafast relaxation processes, however, the accurate imaging of such electronic state-dependent structural evolutions is still lacking. Here, by developing the laser-induced electron recollision-assisted Coulomb explosion imaging approach and molecular dynamics simulations, snapshots of the vibrational wave-packets of the excited (A) and ground states (X) of D2O+ are captured simultaneously with sub-10 picometre and few-femtosecond precision. We visualise that θDOD and ROD are significantly increased by around 50∘ and 10 pm, respectively, within approximately 8 fs after initial ionisation for the A state, and the ROD further extends 9 pm within 2 fs along the ground state of the dication in the present condition. Moreover, the ROD can stretch more than 50 pm within 5 fs along autoionisation state of dication. The accuracies of the results are limited by the simulations. These results provide comprehensive structural information for studying the fascinating molecular dynamics of water, and pave the way towards to make a movie of excited state-resolved ultrafast molecular dynamics and light-induced chemical reaction.
Neutral H2 formation via intramolecular hydrogen migration in hydrocarbon molecules plays a vital role in many chemical and biological processes. Here, employing cold target recoil ion momentum spectroscopy (COLTRIMS) and pump-probe technique, we find that the non-adiabatic coupling between the ground and excited ionic states of ethane through conical intersection leads to a significantly high yield of neutral H2 fragment. Based on the analysis of fingerprints that are sensitive to orbital symmetry and electronic state energies in the photoelectron momentum distributions, we tag the initial electronic population of both the ground and excited ionic states and determine the branching ratios of H2 formation channel from those two states. Incorporating theoretical simulation, we established the timescale of the H2 formation to be ~1300 fs. We provide a comprehensive characterization of H2 formation in ionic states of ethane mediated by conical intersection and reveals the significance of non-adiabatic coupling dynamics in the intramolecular hydrogen migration.
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