Tropical cyclones are storms that cause extensive damage to property, disruption of transport and communication networks, loss of human and animal lives, and environmental degradation (Dube et al., 2009; Krapivin et al., 2012; Sahoo and Bhaskaran, 2018, Ying et al., 2014; Needham et al., 2015; Bakkensen and Mendelsohn, 2019). Around the world, around ninety tropical cyclones are formed per year, which causes catastrophic disasters (Murakami et al., 2013). Globally, tropical cyclones have caused the deaths of about 1.9 million people over the past two centuries (Shultz et al., 2005; Hoque et al., 2018). The approximate damage estimated was 26 billion USD each year (Mendelsohn et al., 2012; Hoque et al., 2019). Many studies have predicted an increased number and intensity of tropical cyclones over the years (Mendelsohn et al., 2012; Ranson et al., 2014; Varotsos et al., 2015; Alam and Dominey-Howes, 2015; Walsh et al., 2016; Moon et al., 2019). This increases the risk of impact on coastal communities, animals, environment, and properties (Varotsos and Efstathiou, 2013; Hoque et al., 2019). According to UNISDR's recent report 'Economic loss, poverty, and disasters, 1998-2017 climate-related disaster made over 4.4 billion people homeless, displaced, and injured worldwide. In India and Bangladesh, approximately 5.5% of the population was directly exposed to disasters in this period. India faced an absolute economic loss of 79.9 billion USD during 1998-2017. World Bank estimates suggest disaster causing over 16 billion USD in total damage in Bangladesh during 1980-2008(UNISDR, 2018).
The Bay of Bengal(BOB) is frequently affected by tropical cyclones. The geographical proximity of Bangladesh and the eastern coast of India to BOB makes the regions highly prone to cyclonic disasters (Islam and Peterson, 2009; Paul et al., 2010; Ahmed et al., 2016; Islam et al., 2016). In the last 100 years, around 17% of tropical cyclones have made landfall on coastal areas of the Bay of Bengal (Hoque et al., 2019). High-intensity tropical cyclones re-occur frequently causing extensive damage in the coastal region of both countries (Alamand Collins, 2010; Mallick et al., 2017). Further, these coastal regions are highly vulnerable due to large population density, high poverty rates, and the presence of temporary infrastructure. According to Paul and Dutt (2010), more than 1 million people were killed by cyclonic disasters since 1877 in coastal Bangladesh. Further, sea-level rise due to global warming will intensify the impacts of tropical cyclones on people's lives and livelihood across the coastal districts of both India and Bangladesh (Karim and Mimura, 2008; Sarwar, 2013; Abedin et al., 2019).
On 20th May 2020, the tropical cyclone ‘Amphan’ hit the coast of India and Bangladesh, accompanied by severe storm surges and rainfall (wind speeds up to 195kmph or 121mph). The cyclone caused causalities, killing around 88 people and leaving thousands homeless in India and Bangladesh (Aljazeera, 2020). The cyclone struck at a time when the region had already been ailing with the impact of the COVID-19 pandemic. In such a situation, the relief and recovery measures get further complicated. Therefore, finding the risk zones and estimating the damage is essential to provide an idea about the loss of property, agricultural and livestock, and various primary livelihoods. Some news reports and government organizations published estimated damage for a particular area (Sud and Rajaram, 2020) or specific aspects. Detailed reports on risks and overall damages in the entire cyclonic affected coastal and adjacent districts were not available.
Risk mapping is a fundamental technique to derive spatial information. Risk mapping assesses the impacts of any hazard or disaster that make people, properties, and environments vulnerable (Pradhan and Lee, 2010; Mohammady et al., 2012; Zare et al., 2013; Rashid, 2013; Pradhan et al., 2014; Youssef and Al-Kathery, 2015; Dieu et al., 2016; Aghdam et al., 2016). Remote sensing and geospatial technique have been used effectively for mapping risk-prone areas (Yin et al., 2010; Poompavai and Ramalingam, 2013; World Meteorological Organization Communications and Public Affairs Office Final, 2011). MODIS, Sentinel, Landsat data, and Census information are frequently used to understand flood, landslide, earthquake, cyclone impact on land-use land cover and socio-economic situation (Agnihotri et al., 2019; Haraguchi et al., 2019; Jeyaseelan, 2003; Tay et al., 2020; Aksha et al., 2020). A review of existing literature shows the spatial analysis techniques are commonly used for mapping risk (Kunte et al., 2014; Mori and Takemi, 2016; Hoque et al., 2017; Hoque et al., 2018; Karim and Mimura, 2008; Kumar et al., 2011; Dasgupta et al., 2011; Roy and Blaschke, 2013) with the use of multi-criteria based approach being used the most (Poompavai and Ramalingam, 2013; Gao et al., 2014; Quader et al., 2017). The spatial risk assessment model has proven useful in minimizing the loss of life and the socio-economic impact (Yin et al., 2013; Mahapatra et al., 2015; Masuya et al., 2015), while the current GEOSOM based shock assessment model can assist in mitigation and current impact assessment for a specific event.
Studies related to tropical cyclone risk mapping are done widely, but studies on spatial damage and loss estimation and mapping due to cyclones are very inadequate. An understanding of the socio-economic damages caused by tropical cyclones is important to undertake the proper recovery measures(Ahmed et al., 2016; Joyce et al., 2009). Moreover, spatial loss assessment is crucial for the allocation of resources for agricultural activities, regeneration of jobs, and other socio-economic activities by the funding agencies. There are two popular typologies, direct and indirect estimation. Direct cost considers the immediate cost of any disaster, whereas indirect estimation focuses on the disaster-associated consequences. Rather than distinguishing direct and indirect loss, several studies focus on the assets and output loss approach (Hallegatte, 2015). The Multi-sectorial Input-output model (Haque & Jahan, 2015), unit cost-based model (GoB, 2008; Roy et al., 2009; Government of Odisha, 2013) are commonly used to estimate the output loss. Significant advancements have been made in the damage assessment framework (Dolman et al., 2018). The availability of real-time satellite data and global socio-economic datasets has significantly improved the damage and loss estimation accuracy. Therefore, our recent study provides deep and elaborate details of damage estimation of the entire flood inundated areas after the cyclone.
This study develops a spatial framework that includes cyclone shock zones and damage and output loss intensity. UN-SPIDER recommended damage estimation practice and unit cost methods were combined to estimates output loss for the entire flood inundated areas caused by cyclone Amphan. This study seeks to analyse the situation of the areas majorly affected by recent inundation and flooding caused by the Amphan cyclone. Firstly, the study assesses the categories of Amphan shock zones to identify potentially exposed areas, rather than following the common risk zonation approach. Secondly, developing a spatial damages assessment framework to account for the economic cost of inundation and flooding on the crop, livestock, and housing units. In this study, the maps produced by risk assessment would be very helpful to identify the spread and intensity of disaster to create the most effective disaster mitigation plan in this area. This understanding of the socio-economic damages caused by tropical cyclones is important for reducing the losses by adopting proper recovery measures(Ahmed et al., 2016; Joyce et al., 2009).