The Dead Sea ecosystem, with its hypersaline conditions, base-level fluctuations, and active tectonics, presents a unique challenge for geological studies. Its equilibrium is increasingly unbalanced due to overexploitation of water and mineral resources. Remote sensing, including drone-based photogrammetry and satellite imaging, monitors large-scale surface changes, while geophysical methods li…
Land subsidence is a worldwide threat that may cause irreversible damage to the environment and the infrastructures. Thus, identifying and mapping areas prone to land subsidence with accurate methods such as Land Subsidence Susceptibility Index (LSSI) mapping is crucial for mitigating the adverse impacts of this geohazard. Also, Machine Learning (ML) is now becoming a powerful tool to analyze v…
Due to the nature of black-box machine learning (ML) models used in the spatial modelling field of environmental and natural hazards, the interpretation of predictive model outputs is necessary. For this purpose, we applied four interpretation techniques consisting of interaction plot, permutation feature importance (PFI) measure, shapley additive explanation (SHAP) decision plot, and accumulat…
BasinVis 1.0, a MATLAB-based modular open-source program released in 2016, has been used for multiple application studies of sedimentary basin analysis and modelling in both academic and industry fields. Based on these studies and user feedbacks, we have improved the workflow, revised user interfaces and developed novel techniques for the compaction trend estimation of infilling sediments and i…