Landslide susceptibility maps using ensemble machine learning models on basin and regional level in Lombardy, Italy

A selection of landslide susceptibility maps computed through ensemble machine learning models for the basins of Val Tartano, Upper Valtellina and Valchiavenna, and on a regional level for the Lombardy region in Italy. A list of the used base machine learning methods: Random Forest, AdaBoost, Neural Networks. A list of the used ensemble models: Stacking, Blending, Soft Voting. A full list of the model combinations can be found in the "Case Studies" document. The maps are in WGS 84/ UTM zone 32N (EPSG:32632). The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper: Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a casestudy in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263 The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam. The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.