Geospatial and Ground Factors for Landslide Susceptibility Mapping using TS-Clustering and PS-InSAR (Bafoussam, West Region,Cameroon, 2019)

This dataset supports the study on landslide susceptibility mapping using a novel TS-Clustering approach integrating spatiotemporal deformation data from Persistent Scatterer InSAR (PS-InSAR) and contextual geospatial factors. It includes both raw and normalized versions of the contextual factors, multicollinearity test outputs (VIF), and ground dynamic features used for the TS-Clustering experiments. The dataset is composed of four `.pkl` files:- `factors_contextual_vif_data_2019.pkl`: Raw contextual factors with multicollinearity analysis (VIF)- `factors_contextual_vif_normalized_data_2019.pkl`: Normalized version of the above- `factors_ground_deformation_data_2019.pkl`: Raw ground deformation factors- `factors_ground_deformation_data_2019_normalized.pkl`: Normalized version of the above These files were used for unsupervised clustering, model testing, and landslide susceptibility analysis in the western region of Cameroon, Bafoussam(5 o 28' North, 10o 25' East). Please cite this dataset using the DOI provided by Zenodo.