Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards
The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing-based procedure for quickly updating the assessment of the population exposed to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/23/3943 |
| _version_ | 1797545939737509888 |
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| author | Giorgio Boni Silvia De Angeli Angela Celeste Taramasso Giorgio Roth |
| author_facet | Giorgio Boni Silvia De Angeli Angela Celeste Taramasso Giorgio Roth |
| author_sort | Giorgio Boni |
| collection | DOAJ |
| description | The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing-based procedure for quickly updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This is used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. To test the reliability of the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from the GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation against reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with a higher refresh rate makes this approach particularly suitable for applications in developing countries, where urbanization and population densities may change at a sub-yearly time scale. |
| first_indexed | 2024-03-10T14:23:03Z |
| format | Article |
| id | doaj.art-21f6bfdc7f704175b777a83016ef698c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T14:23:03Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-21f6bfdc7f704175b777a83016ef698c2023-11-20T23:13:26ZengMDPI AGRemote Sensing2072-42922020-12-011223394310.3390/rs12233943Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural HazardsGiorgio Boni0Silvia De Angeli1Angela Celeste Taramasso2Giorgio Roth3Department of Civil, Chemical and Environmental Engineering, University of Genoa, 16145 Genoa, ItalyDepartment of Civil, Chemical and Environmental Engineering, University of Genoa, 16145 Genoa, ItalyDepartment of Civil, Chemical and Environmental Engineering, University of Genoa, 16145 Genoa, ItalyDepartment of Civil, Chemical and Environmental Engineering, University of Genoa, 16145 Genoa, ItalyThe assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing-based procedure for quickly updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This is used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. To test the reliability of the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from the GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation against reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with a higher refresh rate makes this approach particularly suitable for applications in developing countries, where urbanization and population densities may change at a sub-yearly time scale.https://www.mdpi.com/2072-4292/12/23/3943exposureurban developmentnightlight intensitypopulation distributionnatural hazardsremote sensing |
| spellingShingle | Giorgio Boni Silvia De Angeli Angela Celeste Taramasso Giorgio Roth Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards Remote Sensing exposure urban development nightlight intensity population distribution natural hazards remote sensing |
| title | Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards |
| title_full | Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards |
| title_fullStr | Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards |
| title_full_unstemmed | Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards |
| title_short | Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards |
| title_sort | remote sensing based methodology for the quick update of the assessment of the population exposed to natural hazards |
| topic | exposure urban development nightlight intensity population distribution natural hazards remote sensing |
| url | https://www.mdpi.com/2072-4292/12/23/3943 |
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