Potential of remote sensing techniques for tsunami hazard and vulnerability analysis-a case study from Phang-Nga province, Thailand

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Römer, H.; Willroth, P.; Kaiser, G.; Vafeidis, A.T.; Ludwig, R. et al.: Potential of remote sensing techniques for tsunami hazard and vulnerability analysis-a case study from Phang-Nga province, Thailand. In: Natural Hazards and Earth System Science 12 (2012), Nr. 6, S. 2103-2126. DOI: http://dx.doi.org/10.5194/nhess-12-2103-2012

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Recent tsunami disasters, such as the 2004 Indian Ocean tsunami or the 2011 Japan earthquake and tsunami, have highlighted the need for effective risk management. Remote sensing is a relatively new method for risk analysis, which shows significant potential in conducting spatially explicit risk and vulnerability assessments. In order to explore and discuss the potential and limitations of remote sensing techniques, this paper presents a case study from the tsunami-affected Andaman Sea coast of Thailand. It focuses on a local assessment of tsunami hazard and vulnerability, including the socio-economic and ecological components. High resolution optical data, including IKONOS data and aerial imagery (MFC-3 camera) as well as different digital elevation models, were employed to create basic geo-data including land use and land cover (LULC), building polygons and topographic data sets and to provide input data for the hazard and vulnerability assessment. Results show that the main potential of applying remote sensing techniques and data derives from a synergistic combination with other types of data. In the case of hazard analysis, detailed LULC information and the correction of digital surface models (DSMs) significantly improved the results of inundation modeling. The vulnerability assessment showed that remote sensing can be used to spatially extrapolate field data on socio-economic or ecological vulnerability collected in the field, to regionalize exposure elements and assets and to predict vulnerable areas. Limitations and inaccuracies became evident regarding the assessment of ecological resilience and the statistical prediction of vulnerability components, based on variables derived from remote sensing data.
License of this version: CC BY 3.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2012
Appears in Collections:Naturwissenschaftliche Fakultät

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pos. country downloads
total perc.
1 image of flag of Germany Germany 215 58.27%
2 image of flag of United States United States 28 7.59%
3 image of flag of India India 12 3.25%
4 image of flag of Indonesia Indonesia 11 2.98%
5 image of flag of United Kingdom United Kingdom 11 2.98%
6 image of flag of Thailand Thailand 8 2.17%
7 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 8 2.17%
8 image of flag of Portugal Portugal 6 1.63%
9 image of flag of Italy Italy 6 1.63%
10 image of flag of China China 6 1.63%
    other countries 58 15.72%

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