Assessing population exposure for landslide risk analysis using dasymetric cartography
Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2016-12-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | http://www.nat-hazards-earth-syst-sci.net/16/2769/2016/nhess-16-2769-2016.pdf |
| _version_ | 1818317574294732800 |
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| author | R. A. C. Garcia S. C. Oliveira J. L. Zêzere |
| author_facet | R. A. C. Garcia S. C. Oliveira J. L. Zêzere |
| author_sort | R. A. C. Garcia |
| collection | DOAJ |
| description | Assessing the number and locations of exposed people is a
crucial step in landslide risk management and emergency planning. The
available population statistical data frequently have insufficient detail for
an accurate assessment of potentially exposed people to hazardous events,
mainly when they occur at the local scale, such as with landslides. The
present study aims to apply dasymetric cartography to improving population
spatial resolution and to assess the potentially exposed population. An
additional objective is to compare the results with those obtained with a
more common approach that uses, as spatial units, basic census units, which
are the best spatial data disaggregation and detailed information available
for regional studies in Portugal. Considering the Portuguese census data and
a layer of residential building footprint, which was used as ancillary
information, the number of exposed inhabitants differs significantly
according to the approach used. When the census unit approach is used,
considering the three highest landslide susceptible classes, the number of
exposed inhabitants is in general overestimated. Despite the associated
uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment. |
| first_indexed | 2024-12-13T09:39:29Z |
| format | Article |
| id | doaj.art-9b3bc315d9734b20bced86d7b6284356 |
| institution | Directory Open Access Journal |
| issn | 1561-8633 1684-9981 |
| language | English |
| last_indexed | 2024-12-13T09:39:29Z |
| publishDate | 2016-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj.art-9b3bc315d9734b20bced86d7b62843562022-12-21T23:52:14ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812016-12-0116122769278210.5194/nhess-16-2769-2016Assessing population exposure for landslide risk analysis using dasymetric cartographyR. A. C. Garcia0S. C. Oliveira1J. L. Zêzere2Centre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Lisbon, 1600-276, PortugalCentre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Lisbon, 1600-276, PortugalCentre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Lisbon, 1600-276, PortugalAssessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment.http://www.nat-hazards-earth-syst-sci.net/16/2769/2016/nhess-16-2769-2016.pdf |
| spellingShingle | R. A. C. Garcia S. C. Oliveira J. L. Zêzere Assessing population exposure for landslide risk analysis using dasymetric cartography Natural Hazards and Earth System Sciences |
| title | Assessing population exposure for landslide risk analysis using dasymetric cartography |
| title_full | Assessing population exposure for landslide risk analysis using dasymetric cartography |
| title_fullStr | Assessing population exposure for landslide risk analysis using dasymetric cartography |
| title_full_unstemmed | Assessing population exposure for landslide risk analysis using dasymetric cartography |
| title_short | Assessing population exposure for landslide risk analysis using dasymetric cartography |
| title_sort | assessing population exposure for landslide risk analysis using dasymetric cartography |
| url | http://www.nat-hazards-earth-syst-sci.net/16/2769/2016/nhess-16-2769-2016.pdf |
| work_keys_str_mv | AT racgarcia assessingpopulationexposureforlandslideriskanalysisusingdasymetriccartography AT scoliveira assessingpopulationexposureforlandslideriskanalysisusingdasymetriccartography AT jlzezere assessingpopulationexposureforlandslideriskanalysisusingdasymetriccartography |