Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques

Vatsavai, Ranga Raju; Tuttle, Mary; Bhaduri, Budhendra; Bright, Eddie A; Cheriyadat, Anil M.; Chandola, V.K.; Graesser, Jordan

doi:10.1109/igarss.2011.6049338

Cited by 6 publications

(6 citation statements)

References 8 publications

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“…Pre-and post-disaster satellite imagery and aerial photograph based visual interpretation have been carried out for assessing the damage to buildings and other structures in the past and more recent times (Chiroiu and Andre 2001;Yamazaki and Matsuoka 2007;Lu et al 2004;Vatsavai et al 2011). This technique can utilise the full experience and knowledge of experts in the analysis.…”

Section: Visual Interpretation Techniquesmentioning

confidence: 99%

“…The use of remote sensing and spatial analysis for generating essential information for tropical cyclone disaster management is increasing substantially (Martino et al 2009;Vatsavai et al 2011). However, the provision of information in every phase of management is challenging and requires a large amount of datasets and expertise in processing software (Belward et al 2007;Martino et al 2009).…”

Section: Challenges In Managing Tropical Cyclone Impact Using Remote mentioning

confidence: 99%

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Tropical cyclone disaster management using remote sensing and spatial analysis: A review

Hoque

Phinn

Roelfsema

et al. 2017

International Journal of Disaster Risk Reduction

146

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Tropical cyclones and their often devastating impacts are common in many coastal areas across the world. Many techniques and dataset have been designed to gather information helping to manage natural disasters using satellite remote sensing and spatial analysis. With a multitude of techniques and potential data types, it is very challenging to select the most appropriate processing techniques and datasets for managing cyclone disasters. This review provides guidance to select the most appropriate datasets and processing techniques for tropical cyclone disaster management. It reviews commonly used remote sensing and spatial analysis approaches and their applications for impacts assessment and recovery, risk assessment and risk modelling. The study recommends the post-classification change detection approach through object-based image analysis using optical imagery up to 30 m resolution for cyclone impact assessment and recovery. Spatial multi-criteria decision making approach using analytical hierarchy process (AHP) is suggested for cyclone risk assessment. However, it is difficult to recommend how many risk assessment criteria should be processed as it depends on study context. The study suggests the geographic information system (GIS) based storm surge model to use as a basic input in the cyclone risk modelling process due to its simplicity. Digital elevation model (DEM) accuracy is a vital factor for risk assessment and modelling. The study recommends DEM spatial resolution up to 30 m, but higher spatial resolution DEMs always performs better. This review also evaluates the challenges and future efforts of the approaches and datasets.

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Section: Visual Interpretation Techniquesmentioning

confidence: 99%

Section: Challenges In Managing Tropical Cyclone Impact Using Remote mentioning

confidence: 99%

Tropical cyclone disaster management using remote sensing and spatial analysis: A review

Hoque

Phinn

Roelfsema

et al. 2017

International Journal of Disaster Risk Reduction

146

View full text Add to dashboard Cite

show abstract

Section: Challenges In Managing Tropical Cyclone Impact Using Remote mentioning

confidence: 99%

“…However, the impact of these hazards can be minimized using a range of management approaches, for example, prevention/reduction and preparedness (Moe and Pathranarakul 2006;Khan 2008;Frazier et al 2013c;Mahendra et al 2011). Remote sensing and spatial analysis are efficient and accurate tool for providing a wide range of information to support cyclone management approaches through mapping, monitoring and modelling (Yamazaki and Matsuoka 2007;Islam and Chik 2011;Azaz 2010;Vatsavai et al 2011;Joyce et al 2009b). Repeated high spatial resolution (< 5 m pixels) satellite imagery before and after the cyclone event are great contributions of remote sensing for cyclone disaster management (Joyce et al 2009a;Martino et al 2009;Klemas 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Remote sensing represents a cost effective, convenient and accurate tool for mapping the impacts of tropical cyclones in small to large regions (Vatsavai et al 2011;Zhang et al 2013;Bhowmik and Cabral 2013). Advances in remote-sensing data and processing techniques allow use of low ( > 100 m ) to high (< 5 m) spatial resolution satellite images (multispectral and panchromatic) of the same areas before and after tropical cyclone hazards in order to map the impacts.…”

Section: Introductionmentioning

confidence: 99%

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Cyclone disaster mapping, monitoring and management using satellite remote sensing and spatial analysis

Hoque¹

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Tropical cyclones are one of the most catastrophic natural hazards regularly affecting tropical coastal areas globally. The overall impacts of tropical cyclones can be minimized using a range of management approaches, in terms of: prevention/reduction, and preparedness. Accurate and detailed spatial information on the natural and built environment is required to support the development, implementation and evaluation of these cyclone management approaches. There is a lack of appropriate mapping approaches and spatial models at local scales (<1000 km 2 ) to derive this information.This thesis developed and evaluated mapping approaches and spatial models at the local scale (<1000 km 2 ) by integrating remote sensing, field data and spatial analysis for assessing, monitoring and managing tropical cyclone impacts. Three specific objectives were addressed: (1) developing and evaluating an approach for assessing the multiple impacts of tropical cyclones through objectbased image analysis applied to moderate spatial resolution satellite imagery; (2) developing and testing a risk mapping approach for tropical cyclone impacts using an analytical hierarchy process (AHP) with data derived from remote sensing, field data and spatial analysis; and (3) producing and evaluating a simple risk modelling approach under present and future climate scenarios for tropical cyclone impacts using remote sensing, field data and spatial analysis. The developed mapping approaches and models were tested to justify the applicability in Sarankhola Upazila (151 km 2 ), a local government area in coastal Bangladesh. Cyclone Sidr (2007) was used as a case study for objective one in the study site.After introductory, review and research approach chapters, chapter four developed a method for mapping the multiple impacts of tropical cyclones. The object-based approach was used to map land cover types in pre-and post-cyclone Sidr (2007) damage to cropland and the changes to landforms. The damage results were verified using local damage reports and high spatial resolution satellite imagery that were taken after the cyclone.ii Chapter five integrated remote sensing, field data and spatial analysis for developing a multi-criteria tropical cyclone risk mapping approach at a local scale. Three risk components: 1-vulnerability and exposure; 2-hazard; and 3-mitigation capacity, and their 14 relevant criteria were considered.Thematic raster map layers were prepared for every criterion and weighted using AHP. A weighted overlay technique was used for generating vulnerability, hazard, mitigation capacity and risk maps.The verified results revealed that detailed cyclone risk information can be successfully mapped using geospatial techniques and an AHP at the local scale. The study found that incorporation of mitigation capacity significantly influenced the risk results. The approach also solved several issues for local level multi-criteria data generation, processing and integration. The approach provided was validated by confidence level assessment an...

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A Scalable Probabilistic Change Detection Algorithm for Very High Resolution (VHR) Satellite Imagery

Hong

Vatsavai

2016

2016 IEEE International Congress on Big Data (BigData Congress)

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Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques

Cited by 6 publications

References 8 publications

Tropical cyclone disaster management using remote sensing and spatial analysis: A review

Tropical cyclone disaster management using remote sensing and spatial analysis: A review

Cyclone disaster mapping, monitoring and management using satellite remote sensing and spatial analysis

A Scalable Probabilistic Change Detection Algorithm for Very High Resolution (VHR) Satellite Imagery

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