Assessing tropical cyclone risks using geospatial techniques

Hoque, Muhammad Al-Amin; Phinn, Stuart; Roelfsema, Christiaan M; Childs, Iraphne R.

doi:10.1016/j.apgeog.2018.07.004

Cited by 95 publications

(51 citation statements)

References 44 publications

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“…However, to determine the weight of each variable for flood and earthquake hazards, AHP method was used (Saaty 2008). AHP is a widely used a multi-criteria, decision-making tool that serves a basis for integrating and determining the importance of criteria-variables (Althuwaynee et al 2014;Kazakis et al 2015;Kabenge et al 2017;Hoque et al 2018). We prepared a pairwise comparison matrix for flood and earthquake hazards.…”

Section: Weighting Criteria-variables Using Ahpmentioning

confidence: 99%

“…The relative importance of criteria was assessed from 1 to 9 implying low to high importance, respectively (Saaty 2008) (Table 2). A consistency ratio (CR) was used to justify the consistency of comparisons in the pairwise comparison matrix, and comparisons were considered consistent if CR was less than or equal to 0.1 (Hoque et al 2018).…”

Section: Weighting Criteria-variables Using Ahpmentioning

confidence: 99%

“…Since the study area is at constant risk to all three hazards, we assumed that each had the same relative importance and employed equal weights when preparing the integrated hazard map (Collins et al 2009). Each hazard maps were classified and then ranked 1-5, using the Jenks Natural Break classification method provided in ArcGIS (1 ¼ low, 5 ¼ high) (Devkota et al 2013;Hoque et al 2018).…”

Section: Integrated Hazard Assessmentmentioning

confidence: 99%

“…Hence, risk assessment, and ultimately vulnerability reduction, are processes that require multidisciplinary knowledge of various coupled physical and social processes to calculate the cumulative level of risk posed by hazards. Studies of natural hazard risk frequently emphasize the impacts of an individual hazard, such as landslides (Althuwaynee et al 2014;Pellicani et al 2017), floods (Kazakis et al 2015;Kabenge et al 2017), earthquakes (Theilen-Willige 2010; Dhar et al 2017), drought (Lehner et al 2006), sea level rise (Hinkel et al 2014), tropical cyclones (Hoque et al 2018), or wildfires (Adab et al 2013). However, in reality, many locations are prone to multiple natural hazards that can occur simultaneously or manifest in a set of cascading events (Kappes et al 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Spatial approaches can also help to identify optimal locations for disaster mitigation infrastructure and assist in evacuation, response, resource allocation, and evidence-based policymaking. Thus, the use of remotely sensed data, geographic information systems (GIS) software, and publicly available social, demographic, and economic data have potential to support modeling efforts in terms of increased spatial resolution, computing capacity, rigor in quantitative techniques, and sharing of data for public benefit (Wohl and Oguchi 2004;Bishop et al 2012;Hoque et al 2018) This study introduces a model for spatial multi-hazard risk assessment applied to Dharan, Nepal-a location for which spatial data availability is limited in terms of quality, quantity, and access. The purpose is to use the relevant, publicly available geospatial data to assist local decision and policy makers in the efficient deployment of resources for DRR by developing a procedural model for generating a composite risk map.…”

Section: Introductionmentioning

confidence: 99%

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A geospatial analysis of multi-hazard risk in Dharan, Nepal

Aksha

Resler

Juran

et al. 2020

Geomatics, Natural Hazards and Risk

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Natural hazard risk assessment generally focuses on a single hazard type, such as earthquakes, landslides, or floods. This emphasis tends to consider physical processes in isolation. However, most locations are simultaneously at risk to multiple, interacting hazards that generate cascading effects or synergies. Although scholars have proposed a multi-hazard risk framework based on probabilities, the quality and quantity of data required for such an approach are often unavailable in developing countries. Using geospatial and socioeconomic data, this study represents a first step in assessing multi-hazard risk in the city of Dharan, Nepal. Three hazards-landslides, floods, and earthquakes-were considered for an integrated hazard assessment using statistical methods and the Analytic Hierarchy Process (AHP). We employed a Social Vulnerability Index (SoVI) to create a vulnerability map of the study area, which was then combined with a multi-hazard hazard map to produce a total risk map. Our results indicate that eastern Dharan along the Seuti River and southwestern Dharan on the left bank of the Sardu River are at high risk to multiple hazards. Central Dharan and the hills in the western portion of the city are categorized as low risk areas. Data limitations, such as availability and spatial resolution, did not allow for dynamic modeling; however, our results identified the spatial extent of low to high risk areas, which can inform future disaster planning. For example, the methodology and results of this study could assist in the development of disaster risk reduction programs and policies. ARTICLE HISTORY

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