## 2 Materials and Methods
### Study Area Selection and Hazard Assessment  
After an extensive literature search focused on the hazard context in the Basilicata Region (Section Multi-Hazard Context in the Basilicata Region), the municipalities choice was based on the results obtained via the flood hazard mapping performed in previous works [31] coupled with the neighboring municipalities affected by significant landslide events in the past (Section Multi-Hazard Context in the Basilicata Region) and intersected by the landslide hazard layer in GIS environment (Figure 1). In particular, the intersection tool allowed us to conduct both qualitative and quantitative investigations based on the percentage of the territory potentially affected by landslide, flood, and multi-hazard scenarios for each census tract. The cartographic methodology was specifically explained in [PERSON] et al. [31]. However, the landslide hazard layer was also included in this analysis in order to construct a multi-hazard map.  
As regards the qualitative investigation, a specific hazard classification was provided to show the combination of different hazard types found within each census tract (Table 3). As shown in Table 3, the column \"Scenario\" includes a set of alphanumeric codes derived from the specific hazard classes provided in Section Multi-Hazard Context in the Basilicata Region. Census tracts only intersected by the landslide hazard layer fell into the LH (landslide hazard) classification, census tracts only characterized by flood hazard were related to the FH (flood hazard) classification, whereas census tracts potentially affected by both hazards were associated with the MH (multi-hazard) scenario. Therefore, the letters included in each scenario provide the type of hazards located in each census tract, whereas the numbers represent the count of the combinations. In total, 13 scenarios were detected in census tracts only affected by LHs, 3 scenarios were detected for the case of FHs and 15 scenarios were detected for census tracts intersected by MHs. The advantage of this qualitative methodology is that is provides specific hazard information for each census tract, avoiding cartographic overlap in the final maps.  
In terms of quantitative analysis, the percentage of the territory potentially affected was determined by calculating the extent of the LPH, MPH, HPH, P1, P2, P3, and P4 scenarios, in km\({}^{2}\), in each census tract. Since P1, P2, P3, and P4 (Section Multi-Hazard Context in the Basilicata Region) covered different areas within a single census tract, each extent was summed up to obtain a unique value for the LH scenario. On the contrary, since the LPH flood scenario often included census tract areas characterized by MPH and HPH, the extent of each scenario was treated separately in order to preserve the different return period scenarios.  
Figure 2: Methodological workflow for data integration at census tract level.  
The extent of each scenario was then compared with the total extent of the census tracts in order to measure the percentage of the territory potentially affected by LH, HPH, MPH, and LPH. The percentage of the territory affected ranged between 0% and 100%. Census tracts with no part of the territory affected were excluded from the classification, whereas the others were classified into five hazard levels: Level 1 (very low), Level 2 (low), Level 3 (medium), Level 4 (high), and Level 5 (very high). This type of analysis led us to build a single-hazard map for the LH and FH scenarios. Moreover, in order to include census tracts affected by the multi-hazard scenario, a hazard matrix (Figure 3) was constructed to combine different hazard classes through the use of the raster calculator in the GIS environment.