Landslide Influencing Factors for Landslide Susceptibility Mapping in Lombardy, Italy

A selection of  Landslide Influencing Factors used for Landslide susceptibility mapping through machine learning models covering the Lombardy region in Italy.

A list of the factors:

Averaged Hourly Precipitation for the year of 2020. Source: Precipitation data from ARPA Lombardia.

Digital Elevation Model [meters], 5m/pix. Source: GeoPortale Lombardia.

Eastness [unitless], 5m/pix. Source: DTM derived.

Faults buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.

Land Use Land Cover Map. Source: GeoPortale Lombardia.

Lithology, 5m/pix. Source: GeoPortale Lombardia.

Normalized Difference Vegetation Index, [unitless], 10m/pix. Source: Sentinel-2 derived for the year 2020.

Northness [unitless], 5m/pix. Source: DTM derived.

Orientation of the slope faces [degrees], 5m/pix. Source: DTM derived.

Plan Curvature [unitless], 5m/pix. Source: DTM derived.

Profile Curvature [unitless], 5m/pix. Source: DTM derived.

River buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.

Road buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.

The 90th percentile of hourly precipitation for the year of 2020. Source: Precipitation data from ARPA Lombardia.

Topographic Wetness Index, 5m/pix . Source: DTM derived

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.