Regional-Scale Landslide Susceptibility Mapping Using Limited LiDAR-Based Landslide Inventories for Sisak-Moslavina County, Croatia
| Autor: | Davor Pollak, Vlatko Gulam, Iris Bostjančić, Marina Filipović |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
LiDAR
010504 meteorology & atmospheric sciences AHP Croatia Geography Planning and Development frequency ratio Extrapolation Analytic hierarchy process TJ807-830 Management Monitoring Policy and Law 010502 geochemistry & geophysics TD194-195 01 natural sciences Renewable energy sources landslide susceptibility regional‐scale GE1-350 0105 earth and related environmental sciences Environmental effects of industries and plants Renewable Energy Sustainability and the Environment Frequency ratio Landslide Landslide susceptibility regional-scale Geologic map Environmental sciences Lidar Scale (map) Cartography Geology |
| Zdroj: | Sustainability Volume 13 Issue 8 Sustainability, Vol 13, Iss 4543, p 4543 (2021) |
| Popis: | In this paper, for the first time, a regional-scale 1:100,000 landslide-susceptibility map (LSM) is presented for Sisak-Moslavina County in Croatia. The spatial relationship between landslide occurrence and landslide predictive factors (engineering geological units, relief, roughness, and distance to streams) is assessed using the integration of a statistically based frequency ratio (FR) into the analytical hierarchy process (AHP). Due to the lack of landslide inventory for the county, LiDAR-based inventories are completed for an area of 132 km2. From 1238 landslides, 549 are chosen to calculate the LSM and 689 for its verification. Additionally, landslides digitized from available geological maps and reported via the web portal “Report a landslide” are used for verification. The county is classified into four susceptibility classes, covering 36% with very-high and high and 64% with moderate and low susceptibility zones. The presented approach, using limited LiDAR data and the extrapolation of the correlation results to the entire county, is encouraging for primary regional-level studies, justifying the cost-benefit ratio. Still, the positioning of LiDAR polygons prerequires a basic statistical analysis of predictive factors. |
| Databáze: | OpenAIRE |
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