Data and code for machine learning analysis of aeolian transport processes

This repository provides representative datasets and analysis codes supporting a study on the application of machine learning methods to aeolian transport processes.
The dataset includes example and processed data illustrating the structure, variables, and feature representations used in the analysis, such as wind-related parameters and derived predictors relevant to aeolian transport. These data are representative subsets of larger field measurement datasets.
The code includes core scripts for data preprocessing, feature construction, model training, evaluation, and interpretability analysis. The machine learning workflow encompasses supervised classification and regression models, together with explainable machine learning techniques used to assess feature contributions.