The Indian Ocean tsunami event of 26 December 2004 not only left massive casualties and economic damages, but also raised concerns about the destruction and recovery of coastal ecosystems. This work aimed to analyze the spatial patterns and temporal trajectories of vegetation damage and recovery using a multisensor multitemporal remote sensing, dataset. Using the study area of Koh Phra Thong, Thailand as a case study, we demonstrate the capabilities of remote sensing analysis in assessing the consequences of an extreme flooding event on the dynamics of coastal vegetation. Field surveys and satellite mid-resolution multispectral satellite data covering the period from February 2003 to December 2009 were used to map flooded areas and coastal vegetation loss and recovery following the tsunami. Normalized Difference Reflectance change detection was performed to map the extent of flooded areas. Vegetation Fraction Cover derived using spectral unmixing techniques was used to study the multitemporal changes in coastal vegetation after the event. Vegetation change detection techniques were applied to characterize the vegetation cover changes in two different timeframes: short term changes (from 4 days to 1 year after the event), and long term dynamics (up to 5 years after). Estimates of vegetation change (decline, recovery, and gain) were quantified and mapped, with extreme vegetation losses found directly after the tsunami (up to 79% in flooded areas). After one year, different trends had developed, indicating that recovering vegetation had reached up to 55% of pre-tsunami land cover, but with different trajectories for each vegetation type.

A multitemporal analysis of tsunami impact on coastal vegetation using remote sensing: a case study on Koh Phra Thong Island, Thailand

Villa P;Boschetti M;
2012

Abstract

The Indian Ocean tsunami event of 26 December 2004 not only left massive casualties and economic damages, but also raised concerns about the destruction and recovery of coastal ecosystems. This work aimed to analyze the spatial patterns and temporal trajectories of vegetation damage and recovery using a multisensor multitemporal remote sensing, dataset. Using the study area of Koh Phra Thong, Thailand as a case study, we demonstrate the capabilities of remote sensing analysis in assessing the consequences of an extreme flooding event on the dynamics of coastal vegetation. Field surveys and satellite mid-resolution multispectral satellite data covering the period from February 2003 to December 2009 were used to map flooded areas and coastal vegetation loss and recovery following the tsunami. Normalized Difference Reflectance change detection was performed to map the extent of flooded areas. Vegetation Fraction Cover derived using spectral unmixing techniques was used to study the multitemporal changes in coastal vegetation after the event. Vegetation change detection techniques were applied to characterize the vegetation cover changes in two different timeframes: short term changes (from 4 days to 1 year after the event), and long term dynamics (up to 5 years after). Estimates of vegetation change (decline, recovery, and gain) were quantified and mapped, with extreme vegetation losses found directly after the tsunami (up to 79% in flooded areas). After one year, different trends had developed, indicating that recovering vegetation had reached up to 55% of pre-tsunami land cover, but with different trajectories for each vegetation type.
2012
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Remote Sensing
Tsunami damages
Vegetation monitoring
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Descrizione: A multitemporal analysis of tsunami impact on coastal vegetation using remote sensing: a case study on Koh Phra Thong Island, Thailand
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/182230
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