## 2 Materials and Methods
### Preparation of Landslide Conditioning Factors  
From the DEM generated from LiDAR data, various topographical layers were generated (LCFs). Table 2 presents an overview of various widely applied LCFs generated from the DEM and Figure 3 presents a graphical representation of some of the used LCFs. Based on some DEM analysis, hydrology-related layers were also extracted: the compound topographic index (CTI), integrated moisture index (IMI) and flow direction (FD). To create accurate LSM, we also generated a stream proximity layer based on the stream network extracted from the DEM (see Section 2.3) and Euclidian Distance Buffering (EDB) tool within ArcGIS. The additional auxiliary data presented in the previous subsection and Table 1 made the generation of additional geological, hydrological and environmental factors possible. Among them, tectonics, lithostriatgraphy and faults and thrust proximity were possible to generate by utilizing the geology map and [30]. The Normalized Difference Vegetation Index (NDVI) and lake proximity layers were created from the Senitel-2A data acquired on 25 March 2020. The lake proximity was generated based on Euclidian distance buffering and the lake shapefile extracted from the NDVI (Section 2.3). The Sentinel-2A data were also used to create a Land Cover (LC) map by supervised classification using the Maximum Likelihood (ML) approach and the Sentinel-2A spectral bands. The Overall Accuracy \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Generated Second-Order** & **Method** & **Data Type** & **Data Source** & **Link** \\ \hline DEM & Ground point extraction (class = 2) & LiDAR & ISOK & [[https://isok.gov/l/hydrorortal.html](https://isok.gov/l/hydrorortal.html)]([https://isok.gov/l/hydrorortal.html](https://isok.gov/l/hydrorortal.html)) \\ \hline Stream network & Flow direction and flow accumulation analysis & Shapefile & DEM & \\ \hline Geology map & Digitalization & Raster & Polish National Geological Institute, & [[https://geology.pgi.gov/l/](https://geology.pgi.gov/l/)]([https://geology.pgi.gov/l/](https://geology.pgi.gov/l/)) \\ \hline Roznow lake shapefile & NDVI \(<\) 0 & Sentinel-2A satellite image (25 March 2020) & European Space Agency & [[https://seichub.opernicus.eu/](https://seichub.opernicus.eu/)]([https://seichub.opernicus.eu/](https://seichub.opernicus.eu/)) \\ \hline Land cover map & Maximum Likelihood Classification & Sentinel-2A satellite image (25 March 2020) & European Space Agency & [[https://seichub.opernicus.eu/](https://seichub.opernicus.eu/)]([https://seichub.opernicus.eu/](https://seichub.opernicus.eu/)) \\ \hline Road network & - & Shapefile & OpenStreetMap & [[https://download.gotabric.de/](https://download.gotabric.de/)]([https://download.gotabric.de/](https://download.gotabric.de/)) \\ \hline Soil Suitability Map & Digitalization & Raster & Malopolska Spatial Information infrastructure & [[https://mip.geomapolska.pl/](https://mip.geomapolska.pl/)]([https://mip.geomapolska.pl/](https://mip.geomapolska.pl/)) \\ \hline Fault and thrust network & Digitalization & Raster & [30] & [30] \\ \hline Precipitation & Inverse distance weighed interpolation & Precipitation measurement in meteorological stations (points) & Institute of Meteorology and Water Management & [[https://danepubliczone.ingw-pl/](https://danepubliczone.ingw-pl/)]([https://danepubliczone.ingw-pl/](https://danepubliczone.ingw-pl/)) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Second-order input data generation from various data sources (DEM: Digital Elevation Model, ISOK: IT System of the Country Protection, NDVI: Normalized Difference Vegetation Index). (OA) of this LC map was assessed by comparing ground truth samples with the classification results, indicating that the OA of our map was approximately 94%--sufficient for this study. The shapefile of the road network was captured from OpenStreetMap, and similarly to previous distance-related layers, the distance to road layer was created.