| Autor: |
Raffaele Albano, Caterina Samela, Iulia Crăciun, Salvatore Manfreda, Jan Adamowski, Aurelia Sole, Åke Sivertun, Alexandru Ozunu |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Water, Vol 12, Iss 6, p 1834 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2073-4441 |
| DOI: |
10.3390/w12061834 |
| Popis: |
Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth–damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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