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

Abstract

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.

Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review

“…Remote sensing (RS)-as an effective and rapid tool for monitoring large areas-is essential for the acquisition of geospatial data, which in turn constitutes the basis for risk assessment and management. RS is widely used for various aspects of the DRM, ranging from vulnerability [8] to rapid damage assessments [9], for diverse areas ranging from coastal ecosystems [10] to complex urban settings [11], and for disasters as diverse as landslides [12,13] or cyclones [14].Numerous methods have been developed to extract information from RS data to identify, characterize, or quantify different phases of the disaster risk cycle: response, recovery, prevention/mitigation, and preparedness [15]. However, early studies predominantly considered the physical side of the assessments for both pre-and post-disaster phases and hazard assessment, using direct observations.…”

“…Remote sensing (RS)-as an effective and rapid tool for monitoring large areas-is essential for the acquisition of geospatial data, which in turn constitutes the basis for risk assessment and management. RS is widely used for various aspects of the DRM, ranging from vulnerability [8] to rapid damage assessments [9], for diverse areas ranging from coastal ecosystems [10] to complex urban settings [11], and for disasters as diverse as landslides [12,13] or cyclones [14].…”

Coastal Social Vulnerability and Risk Analysis for Cyclone Hazard Along the Andhra Pradesh, East Coast of India

“…Disaster risk is determined by the intensity and frequency of hazards, as well as its exposure and vulnerability to these hazards (Peduzzi et al 2009;Sharma et al 2009;Hoque et al 2017). According to the IPCC report (2014), drivers of hazards, exposure, and vulnerability include many factors, like climatic and societal changes along with adaptation and mitigation measures that combine to form overall risk or potential impacts (Fang et al 2014).…”

Vulnerability Factors and Effectiveness of Disaster Mitigation Measures in the Bangladesh Coast

“…Adger 2006;Emrich and Cutter 2011;Dewan 2013;Islam et al 2016Islam et al , 2017. A number of studies have emphasized on the technical aspect and numerical modeling of tropical cyclone impacts (for example; Islam and Peterson 2008;Karim and Mimura 2008;Roy and Kovordányi 2012;Tasnim et al 2015;Hoque et al 2016Hoque et al , 2017bHoque et al , 2018. Hoque et al (2017a) systematically reviewed the researches on tropical cyclone disaster management using remote sensing and spatial analysis techniques.…”