A novel approach (the CRATER method) for assessing tsunami vulnerability at the regional scale using ASTER imagery

Osso, Filippo Dall '; Bovio, Lorenza; Cavalletti, Alessandra; Immordino, Francesco; Gonella, M.; Gabbianelli, Giovanni; Ingegneria, Med

doi:10.5721/itjrs20104225

Cited by 10 publications

(8 citation statements)

References 41 publications

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“…From an operational point of view, recent major disasters (e.g. 2010 Haiti earthquake, 2010 Pakistan Flood, 2011 Japan tsunami and 2012 Italy earthquake) [Ajmar et al, 2008[Ajmar et al, , 2011Mahendra et al, 2010;Baiocchi et al, 2012;Bhattacharya et al, 2013] clearly demonstrated the potential role of geomatics in supporting emergency response and recovery, as already depicted in different papers published by EuJRS [Ajmar et al, 2008[Ajmar et al, , 2011[Ajmar et al, , 2012Borfecchia et al, 2010;Dall'Osso et al, 2010;Pignatelli et al, 2010;Rivolta et al, 2010;Baiocchi et al, 2012;Laneve et al, 2012;Perez et al, 2012]. Remote sensing based analyses are nowadays frequently adopted to support both decision makers and responders in the field during disaster management activities, as clearly pointed out by the United Nations in the 2011 humanitarian appeal: " […] Remote sensing in the hours and days after the Haiti earthquake yielded estimates of numbers of severely affected people that stood the test of time and allowed an unusually rapid flash appeal.…”

Section: Introductionmentioning

confidence: 88%

New perspectives in emergency mapping

Boccardo

2013

European Journal of Remote Sensing

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In recent years, growing attention is paid to remote sensing when used for disaster management applications. This is essentially due to the large variety of remotely acquired imagery available for the extraction of geometric and thematic features in order to map, delineate and grade natural disasters impacts. Another key point is the quick availability of those images in rapid mapping procedures in order to deliver the data (reference and thematic) to concerned users. This paper briefly describes the current state-of-the-art of remote sensing techniques usage in emergency mapping, paying particular attention, in the second part, to the GIO-EMS new operational service delivered by the European Commission.Keywords: Disaster management, emergency mapping, remote sensing, spatial data infrastructure (SDI), data model, image processing. General remarksStarting with this editorial, the Italian Society of Remote Sensing (AIT) aims to favour an International debate related to the main geomatics (with particular attention to remote sensing) applications. The short papers that will be published in the next European Journal of Remote Sensing (EuJRS) issues are conceived to deliver basic and operational information to all EuJRS readers on different topics, highlighting potentialities (also in terms of possible financing coming from National and International opportunities) of these new application fields. This first paper is related to geomatics and emergency management; applications on health, weather, atmosphere, climate change, water resources, energy, geology, cryosphere, forest, natural ecosystems, biodiversity, land cover, coastal, ocean and transportation, infomobility and Intelligent Transport Systems (ITS), will follow in the next months.

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Section: Introductionmentioning

confidence: 88%

New perspectives in emergency mapping

Boccardo

2013

European Journal of Remote Sensing

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“…This method is used to extract land use classes from MODIS images (Despini et al, 2009). Furthermore, this method is also applied for land use classification in the study of tsunami vulnerability assessment using ASTER imagery (Dall'Osso et al, 2010). The advantage of this method is that data from many different sources and files can be used together to make a single decision tree classifier.…”

Section: Satellite Image Analysismentioning

confidence: 99%

Remote sensing and spatial multi-criteria analysis for tsunami vulnerability assessment

Sambah

Miura

2014

Disaster Prevention and Management

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Purpose -The purpose of this paper is to assess the vulnerability of the Kesennuma area in Japan to a tsunami disaster and to map the area of inundation. Design/methodology/approach -Digital elevation model (DEM) data and ALOS image were used to create maps of the parameters of this study area: elevation, slope, coastal proximity, river, and land use. An analytical hierarchy process was used to assign weights to each parameter and a spatial multi-criteria analysis was applied through cell-based modelling for vulnerability mapping.Findings -The vulnerability map shows that 17.679 km 2 of the area could be inundated by a tsunami. High vulnerability areas were mostly found in coastal areas with a sloping coast and a cape area. A low elevation and the presence of rivers or water channels are factors that increase the impact of tsunamis. Inundation areas were predicted to spread in areas identified as having either high vulnerability or slightly high vulnerability. Research limitations/implications -Because of the limited geospatial data, the authors encourage further studies using DEM data with a high spatial resolution. Practical implications -The results of this research can be used as basic information for disaster mitigation and urban planning in coastal areas. Originality/value -This research creates a new approach for assessing which areas could be inundated by tsunamis, based on the vulnerability map generated through remote sensing and spatial multi-criteria analysis. Moreover, the parameters used are very close to those of actual inundation maps.

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“…A novel approach from the Coastal Risk Analysis for Tsunamis and Environmental Remediation (CRATER) project was applied for assessing tsunami vulnerability on a regional scale using ASTER imagery and SRTM version 3. This work analyzed the vulnerability of coastal zones and inland areas using the parameters of infrastructural, geomorphological, and ecological features for coastal zones, and parameters of land use, altimetry, and distance from the shoreline for inland areas [21]. Tsunami vulnerability mapping along coastal area of East Java also applied using high resolution of elevation data from NEXTMap World 10.…”

Section: After Earthquakesmentioning

confidence: 99%

Geo Spatial Analysis for Tsunami Risk Mapping

Sambah¹,

Miura²

2019

Advanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure

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Tsunami risk is a combination of the danger posed by tsunami hazard, the vulnerability of people to an event, and the probability of destructive tsunami. The spatial multicriteria approach made a possibility for integrating the vulnerability and risk parameters to assess the potential area that will be affected by the tsunami. The study applied the parameters of physical and social vulnerability and combined element at risk to assess tsunami risk in the coastal area of East Java Indonesia. All parameters in both tsunami vulnerability and tsunami risk assessment were analyzed through cellbased analysis in geographical information system. The weight of each parameter was calculated through the analytical hierarchy process. The results were provided as maps of tsunami vulnerability and tsunami risk. Tsunami risk map described five classes of risk. It described that coastal area with a low elevation and almost flat identified as high risk to the tsunami. The coastal area with a high density of vegetation (mangrove) was defined as the area with low level of tsunami risk. The existence of river and other water canals in coastal area was also analyzed for generating tsunami risk map. Risk map highlights the coastal areas with a strong need for tsunami mitigation plan.

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A novel approach (the CRATER method) for assessing tsunami vulnerability at the regional scale using ASTER imagery

Cited by 10 publications

References 41 publications

New perspectives in emergency mapping

New perspectives in emergency mapping

Remote sensing and spatial multi-criteria analysis for tsunami vulnerability assessment

Geo Spatial Analysis for Tsunami Risk Mapping

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