Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology Progress in Disaster Science 11 (2021) 100185 Contents list[.]
Progress in Disaster Science 11 (2021) 100185 Contents lists available at ScienceDirect Progress in Disaster Science journal homepage: www.elsevier.com/locate/pdisas Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology ⁎ Kabir Uddin a,b, , Mir A Matin a a b International Centre for Integrated Mountain Development, GPO Box 3226, Kathmandu, Nepal Department of Forestry and Environmental Management, University of New Brunswick, Fredericton, E3B 5A3, Canada A R T I C L E I N F O Article history: Received February 2021 Received in revised form June 2021 Accepted 14 June 2021 Available online 18 June 2021 Keywords: Automatic flood mapping Flood dynamics Inundation Flood-prone areas Radar Sentinel GEE Disaster preparedness Flood shelters site Bangladesh A B S T R A C T Low-lying Bangladesh is known as one of the most flood-prone countries in the world During the last few decades, the frequency, intensity, and duration of floods have increased To ensure safety and save lives when people's homes submerge because of flooding, it is urgent to relocate them to safe shelters during the flooding In Bangladesh, the number of designated flood shelters is very less To plan and prioritise the building of shelters, flood hazard zonation and the identification of suitable locations for shelters are vital for disaster risk mitigation This study attempted the first and most extensive national flood inundation database and flood dynamics of Bangladesh developed between 2017 and 2020 using public domain Sentinel-1 Synthetic Aperture Radar (SAR) images were processed in the Google Earth Engine (GEE) and replicable methodology Using a set of analytic hierarchy process (AHP) criteria associated with flood disasters (e.g., floods recurrence areas), elevation, land cover, landform, population density, accessibility, distance to road, and distance to settlement layers were used to identify the hazard zones and the safest locations for building flood shelters The study assessed that 7.11% of the area was inundated by overflow water in June 2017 and 8.99% in August 2017 Similarly, in June, July, and August 2018; June, July and August 2019, and July 2020, with inundation covering 7.26%, 10.87%, 11.07%, 9.50%, 10.56%, 5.01% and 11.14% of the country, respectively The results show that extremely-high flood prone areas cover about 13% of Bangladesh Analysis of the suitability of flood shelters shows that about 8% is extremely-high suitable, 16% is very-high suitable, and 7% is very-low suitability for flood shelters The flood suitability and flood hazard maps would be helpful to support the local government, national and international organisations for flood disaster risk minimisation and the planning and construction of flood shelters Introduction A flood is a most frequent natural phenomenon producing an abnormal overflow of water that submerges a vast area that immediately impacts the everyday living conditions of affected communities and ecological vulnerability and raising social, economic consequences [30,45,55,79] Global damage from flood disasters and their frequency has been progressively intensifying due to the accelerated impact of human activities and climate change [69,76] Disasters are natural events that destroy homes, infrastructure, crops and may result in human death Disasters have been force people to internally displaced and leave their houses or places of usual residence and take shelter somewhere else to pursue refuge for a short or long period [4,22,34,42,53] According to the Internal Displacement Monitoring Centre, about 26.4 million people globally were evacuated from their homes each year due to natural hazards between 2008 and 2018, with 26.14% of them being from South Asia [36,81] Disasters also cause direct physical and mental damage to people who face various difficulties, including loss of accommodation and job, unfamiliar environment, and loss of social ties [61,81] Between 1960 and 2014, 2171 floods, droughts and extreme hydrological events occurred globally [35] Since 2018, among the different types of hazards, 50.62% of the displacement of people was caused by floods, followed by storms 34.54%, earthquakes and tsunamis 12.23% and wildfires 0.61% In 2018, 315 natural disasters affected more than 68 million people, cost USD 131.7 billion worldwide and caused 11,804 deaths[24] Similarly, in 2019, flooding, cyclones, heatwaves and wildfires caused thousands of deaths and injuries The direct economic loss from natural disasters in 2019 was estimated to USD 232 billion [89] Among the different kinds of disaster, a flood is defined as when a considerable amount of overflowing water directly impacts living conditions [10,12] Once an area is inundated by floodwater, it interrupts everyday life, damages livestock and crops, halts economic activities, and spreads water-borne diseases [82] Every year on average, about 350 million people are affected by flooding across the globe [50,59] In 2018, from the 315 different natural disaster events recorded, flood inundation caused 24% of the total deaths from natural disasters [24] Globally, about US $8 billion of economic losses resulted from the flooding event in March 2019 [64] In ⁎ Corresponding author E-mail addresses: Kabir.Uddin@icimod.org (K Uddin), Mir.Matin@icimod.org (M.A Matin) http://dx.doi.org/10.1016/j.pdisas.2021.100185 2590-0617/© 2021 The Author(s) Published by Elsevier Ltd This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/) K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 and GIS could play a vital role to identify suitable locations for flood shelters In this study, we describe a reproducible automatic method, based on the Google Earth Engine, for generating rapid flood extent data on the national scale to assistance the disasters preparedness agencies by offering timely GIS data and maps on such flooded areas to prioritise disaster response work in the ground Also, determining the flood-prone site and the suitable location for constructing emergency flood shelters using remote sensing and geographic information systems tools Finally, our research was able to fill this research gap and provide comprehensive and detailed information about the flood inundation area, flood risk and the appropriateness of flood shelters in Bangladesh The critical questions for the investigation were: recent years, the frequency of floods and the devastating magnitudes have most likely been enhanced by changing climate patterns resulting in fluctuations in precipitation patterns[64,77] As a result of the changes in the hydrological cycle, fluvial floods will cause estimated damage of USD 597 billion between 2016 and 2035 [95] Bangladesh experiences four types of floods almost every year due to its unique geographical location [33,60] In usual Natural flood events have a significant impact on the livelihoods of people living in floodplains (Fig S1) In Bangladesh flood water impact around 60% area of the country[22] Generally, about 26,000 sq km are inundated during the monsoon period in Bangladesh [49] However, during the 19th century, Bangladesh experienced six major floods in 1842, 1858, 1871, 1875, 1885 and 1892 [39], when half of the country was inundated During the 20th century, eighteen major floods occurred Among these, the floods in 1953, 1954, 1956, 1962, 1966, 1968, 1969, 1970, 1974, 1980, 1984, 1987, 1988 and 1998 were the most baleful [29,46] Several destructive floods also occurred in the current century: in the years of 2000, 2004, 2007, 2017, 2018 and 2019, which adversely affected the lives of the people and their property in Bangladesh [2,5,13,28,68,86] The flood in 1988 was the most catastrophic among all the historic disaster years when more than 2379 people were killed, 45 million were affected, and 82,000 sq km was inundated [5,28,68] There is a strong link between both the flood period and the flood-prone region, and the economic losses and casualties and the temporary accommodation facilities available during floods in Bangladesh and Bangladesh is prone to economic losses and casualties and temporary housing during the floods [1,28,45,62,63] A greatest number of people in Bangladesh live in flood-prone areas with limited flood shelters [32,48] For the mitigation of flood impact, it is essential to know the areas that are inundated by floodwater With the timely flood inundation information, disaster and relief agencies can speed up emergency responses for relief and rescue measures [40,72] At the same time, flood-affected people also can find a safe place to shelter [54,66,84] Therefore, near real-time map-based inundation information on floods can be crucial for disaster risk management [27,70,91] Flood maps provide essential inputs for assessing the progression of the inundation area and the severity of the flood [7] Satellite-based Earth observation techniques can be used for preparing near real-time flood maps and assessing damage to residential properties, infrastructure and crops [41] Though optical satellite imagery is the most applicable technique for landform mapping, it is not appropriate in Bangladesh due to the 78% probability of increased cloud cover during times of flooding [86] Consequently, C-Band Sentinel-1 Synthetic Aperture Radar (SAR) images are mostly chosen for flood mapping as they are freely available with a relatively high frequency of observation, and they are able to capture images during all-weather conditions Unlike optical remote sensing, SAR data are more sensitive to waterbodies and are helpful for determining flood frequency and severity, mapping and the accurate measurement of streams, lakes and wetlands [6,92] In Bangladesh, most rural houses are located in low-lying floodplain areas, which are highly susceptible to flooding [11,17,32,34,65] Many of these houses submerge during flooding and become unsuitable for habitation In this case, emergency accommodation in temporary flood shelters is required for the affected people [11] The location of the flood shelter concerning the distance from the settlement and accessibility is vital for efficient evacuation and relocation The flood shelter must be accessible and close to a settlement to ensure efficient evacuation and relocation On the other hand, the shelters should be built in an area free from the risk of flooding Over time, a good number of safe cyclone shelters have been established in the coastal regions of Bangladesh [67] However, in the flood-prone northern and central regions and the flood-prone area along the major rivers, a minimal number of designated flood emergency shelters exist other than a few elevated homesteads [66] In many cases, these small numbers of flood shelters are not located in the flood risk area for the evacuation of the majority of people Various factors should be considered related to flood proneness, safety and accessibility when identifying a suitable location for building flood shelters In this case, remote sensing I Is GEE emphatic of automatically developing a national-level rapid flood inundation map with Sentinel-1 images? II What is the spatial and temporal patterns of flood inundation areas was in Bangladesh? III Where are the area most at risk due to regular flood disasters? IV Where is the most suitable location to place flood shelters? Materials and methods 2.1 Study area The study was conducted for the whole of Bangladesh (Fig 1) Bangladesh is in the southern side of the foothills of the Himalayan mountain region and the northern edge of the Bay of Bengal, with the boundary between 20° 34′ N to 26°38 N and 88° 01′ N to 92° 41′ E, and with an area of 147,570 sq km A total of 310 rivers and tributaries flow across the country The Brahmaputra, Jamuna, Karnafuli, Meghna, Padma, Surma and Teesta rivers are considered the major rivers of Bangladesh About 50% of the country is within m of mean sea level, and most of the country is on a delta plain under the influence of the Padma, Jamuna and Meghna rivers Most of the land on the planes is used for crop production, and about 87% of rural households depend on crop farming for at least part of their earnings Bangladesh is the land of six seasons: summer, rainy season, autumn, late autumn, winter and spring with the highest 99% humidity in the rainy season Bangladesh has approximately 136 rainy days per year, an average of 1733 mm of yearly rainfall in the monsoon season [14,86] The place with the highest rainfall on the planet is Cherrapunji which is situated just a few kilometres from the northeast border of Bangladesh Because of the high annual rainfall and the Himalayan mountain regions, rivers flow with very high currents due to the topography When the water reaches the Bangladesh territory, it spreads over a large area and causes the regular flooding (Fig S1) 2.2 Data used The study takes advantage of satellite data available in the public domain that works during cloudy weather for flood inundation mapping For flood mapping of the whole of Bangladesh, around 11 scenes of Sentinel-1C-band interferometric wide swath (IW) frames with a 250 km swath were needed to enable comprehensive inundation mapping across Bangladesh To map flood inundation for June and August 2017; June, July and August 2018; June, July and August 2019 and July 2020, a total of 99 dual-polarisation Sentinel-1 Ground Range Detected (GRD) products were required The great benefit of Sentinel-1 SAR images is that data are freely available within h of capture to support Near-Real-Time (NRT) emergency response Sentinel-1 images can be accessed directly from the Copernicus Open Access Hub However, we retrieved images through the Google Earth Engine (GEE) For the flood map calibration and validation, on-demand Level-2 Landsat surface reflectance images with 137 paths and 43 rows, were taken from the USGS data providing sites on 19 September 2019 [31] K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig (a) Index map superimposed with three major rivers originating from the Himalayan mountain region and flowing across Bangladesh; (b) study area map of the whole of Bangladesh overdyed the major divisions and Sentinel-1 image composites In addition, Landsat-8 image collections between 01 January and 31 December 2018 were used for land cover mapping in the Google Earth Engine Additional secondary data, including shuttle radar topography mission (SRTM) digital elevation models [90] and Advanced Land Observation Satellite (ALOS) Landforms [80] data, were used because the elevation and landform of a particular location are some of the main factors involved in avoiding flood waters Areas of lower elevation are likely to flood faster as water flows from a higher altitude mountain to lower elevated floodplains Furthermore, UN-Adjusted Population Density 2020 [23], travel time to major cities (A global map of Accessibility data with pixel values representing minutes of travel time) [93], as well as road network information from OpenStreetMap [38], and Bangladesh settlement and nation, division, district, Upazila (Sub-district) administrative boundary information from the United Nations Office for the Coordination of Humanitarian Affairs [71] were obtained for analysis 2.3 Flood extent maps and other layer preparation To generate the recurrence interval of flood extents, Sentinel-1 data were processed using the Google Earth Engine as can be seen from Code S1 and Fig The Sentinel-1 GRD data injected in GEE had already been through most of the important SAR image pre-processing steps Sentinel-1 image processing in GEE was rapid as the imagery in the GEE ‘COPERNICUS/S1_GRD’ Sentinel-1 image was uploaded after the standard SAR image pre-processing steps to derive the backscatter coefficient (σ°) in decibels (dB) in each pixel For flood mapping, only speckle filters were required for the Sentinel-1 images to reduce granular noise, i.e., blurred features in images After the speckle filters, 370 random points were generated, and the points were labelled waterbodies and other areas with the help of a Fig Synthetic Aperture Radar (SAR) image processing steps during the flood inundation mapping using the Google Earth Engine K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Landsat-8 image from 19 September 2019 After this, we extracted the Sentinel −1 image from the same date (19 September 2019) with VV (vertical transmit and receive) and VH (vertical transmit, horizontal receive) band values for the 370 points labelled Fig shows the Sentinel-1 VV and VH backscatter value for waterbodies (flood inundation) and other samples Based on the backscatter mean value of the VV and VH, the flood inundation map for the particular areas were extracted Waterbodies present before mid-April were considered as being perennial waterbodies for 2017 and the years before June To have confidence in the developed flood maps, a validation procedure was required Finally, flood inundation maps were validated using sample points collected from the field and Landsat image on 19 September 2019 The accuracy assessment report of the flood inundation map presented in Table An omission and commission analysis was carried out using Sentinel-1- and Landsat-8-based flood inundation map on 19 September 2019 to ensure the quality In this process, Landsat-8-based flood inundation map was developed on object based image analysis (GEOBIA) The complete methodology used to develop the flood inundation maps is described in [25,26,84] Briefly, eCognition Developer software was used to produce the image at the object level by segmentation Usually, the term satellite image segmentation means splitting entities, such as objects, into the smaller compartment of the image The segmentation procedure creates new image objects or subdivision of an image into individual regions according to the user-defined criteria[15] Among the Chessboard, Quadtree-Based, Contrast Filter, Contrast Split, Bottom-up, and Multiresolution Segmentation in eCognition Developer, Multiresolution Segmentation was used to classify Landsat-8 image GEOBIA multi-resolution image segmentation method segments Landsat image into meaningful image objects based on the spectral characteristics of image pixels [3,21,87] During the Landsat based flood extent mapping, normalized difference water index (NDWI) and the land and water mask (LWM) derived from spectral values of the Landsat image information Lastly, a rule set was developed to create Landsat-based flood inundation maps The Landsat-based flood extent maps are displayed in Fig and Code S2 were used to see omission and commission transgressions with the Sentinel-1 based flood map For an accuracy appraisal, the Sentinel-1 SAR image classification result for 19 September 2019 was assessed with the waterbodies map obtained from Landsat-8 (19 September 2019) using 500 reference points assembled from the Landsat-8 classification map The overall accuracy of the 19 September 2019 flood inundation map was 97.73%, with a kappa value of 0.90, standard error kappa of 0.02, and a 95% confidence interval between 0.770 and 0.850 (Table 2) The evaluation of the flood map from SAR data compared to the optical image-based inundation map (Table S1) shows that for a particular cloud-free area, the Landsat-based map (19 September 2019) produced an inundated area of 2463 sq km while the Sentinel-1 SAR-based map presented an inundated area of Table Overall accuracy of the flood inundation map Land cover Land Waterbodies Total User's Accuracy (%) Land Waterbodies Total Producer's Accuracy (%) 291 298 97.65 201 202 99.5 292 208 500 99.65 96.63 n.a n.a 2372 sq km Within the Landsat- and Sentinel-based flood maps, 94% of inundated areas were common The visual judgement of the Landsatbased (19 September 2019) and Sentinel-1-based (19 September 2019) flood map can be seen in Fig Land cover is considered to be one of the key factors for any site suitability study The satellite image classification methods followed the national land cover classification methods using GEE [73,85] The land cover map of 2018 was developed using Landsat image composites Once a set of training data were collected using the Collect Earth Online (CEO), a supervised learning algorithm was applied to produce these land cover map [57] In this mapping input Landsat Data Continuity Mission (LDCM) bands Band −1 (Coastal / Aerosol), Band −2 (Visible blue), Band −3 (Visible green), Band −4 (Visible red), Band −5 (Near-infrared), Band −6 (Short wavelength infrared), and Band −7 (Short wavelength infrared) the indices Bare Soil Index (BSI), land and water mask (LWM), Normalized Difference Moisture Index (NDMI), Normalized difference vegetation index (NDVI), and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) were also used in the classification The efficiency of the 2018 land cover map was assessed using 65 points from the ground and (10 km × 10 km) 1400 reference points from CEO These were correlated with the land cover map to determine the error matrix, and an overall accuracy of 87.51% was found 2.4 Flood hazard assessment and shelter suitability analysis The flood hazard map identifies the area that could be flooded under different scenarios It can be demarcated through qualitative or quantitative assessments using spatial coverage of floods, which happens in an area over and over again [65] The flood hazard map can help government authorities to prioritise area planning In this regard, we analysed several types of factors, e.g., elevation, slope, land cover, landform, population density, accessibility, distance to road, distance to settlement layers and distance from the river played an important role in determining the right place for flood risk and area suitability [84] For the identification of a suitable location for the construction of flood shelters, a place must be in a flood-prone area, not occupy any productive land, not be submerged in floods waters, be accessible to people in a short time and be able to be Fig Box plots of Sentinel-1 VV and VH backscatter value for waterbodies (flood inundation) and other samples K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig Comparison of optical data and SAR-based flood inundation: (a) Landsat-8 image from 19 September 2019; (c) colour-coded Sentinel-1 image from 19 September 2019, showing waterbodies in blue; (b) classification result based on Landsat-8; (d) classification result based on Sentinel-1 data (dark blue: perennial water; light blue: flood inundation areas; green: other areas) used for multiple purposes Overall, the flood suitability analysis steps are presented in Fig Among the different factors, major rivers, settlements, and roads were necessarily vector data (Fig 6) Usually, the area close to a major river is prone to floods and is most likely to become inundated Shelters near people's houses or roads can be quickly reached Therefore, Euclidean allocations of roads and settlements were created to represent the distance from roads and settlements, in order to combine the raster layers, which had to be set to a common scale range from to In this process, each dataset was then reclassified to rank the potential flood-prone area and safe shelter location For flood hazard zonation mapping inundation extent data, distance from the river, elevation, and slope layers were used During the raster layer reclassification, each raster was ranked: the most flood hazardous zone was ranked ‘8’ and the least reasonable place was ranked ‘1’ Similarly, for floods recurrence areas, elevation, slope, land cover, landform, population density, accessibility, distance to road, distance to settlement layers were reclassified for emergency flood shelters Each raster was ranked: the most feasible place was ranked ‘8’ and the least reasonable place was ranked ‘1’ Once the raster layers were reclassified, a multi-criteria decisionmaking method known as Analytical Hierarchy Process (AHP) was used for the determination of the prioritised GIS layer associated with flood hazard and flood shelter suitability [20,74,75] Single suitability layers were created to reduce the number of GIS layers with their attribute by the weighted overlay (Fig 5) Five steps were used for the determination of suitability layers: (1) develop an AHP decision tree; (2) Form the relative Table Omission and commission matrix between Sentinel-1 and Landsat-8 images used for ensuring the quality of the developed maps Landsat-8 Sentinel-1 Class name Flood Inundation Area Other Flood Inundation Area 2233 139 Other 231 1769 Total 2463 1908 Total 2372 2000 4372 K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig Main methodological steps followed for the flood emergency suitability mapping using different factors associated with flood shelters for 2.04% of the flood inundation area; in 2020, the Dhaka division accounted for 2.24%, and the Mymensingh division accounted for 1.54% of the area of flood inundation The flood Hazard model results shows that 13.04% of the country is an extremely highly prone area (Fig 8) These are the areas inundated for the majority of monsoon by catastrophic floods The very high flood-prone area covers 6.02% of the country Analysis of flood-affected areas by the divisions of Bangladesh shows that more all less all divisions are prone to flood inundation The study determined that the Sylhet division is the most extremely high flood-prone area, accounting for 3.09% out of 13.04% of the area recognised in the whole of Bangladesh The Dhaka division is the second highest flood-prone area A significantly lower portion of the extremely highly prone zone was found in the Barisal division of Bangladesh due to there being less direct influence from primary river flow originating in the mountains From the different levels of suitability, it is possible to identify appropriate places for shelter construction The suitability ranking was done under the category of extremely suitable, very suitable, highly suitable, highmedium suitability, medium suitability, low-medium suitability, low suitability, very low suitability, and excluded, as shown in Fig The identified suitability map estimates that the extremely highly suitable area was 9.73%, the very highly suitable area was 16.22%, the high suitability area was 25.99% and the high-medium suitability area was 12.35% Besides the suitable zones, around 5.13% of the area was considered perennial waterbodies and closed forested area and so cannot be used for flood shelter sites From the division level analysis, it appears that the Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet divisions represent importance of a factor along with other influences of the decision matrix; (3) manage the continuous validity of assessment matrix forms; (4) calculate the relative rank of each factor and weigh the overall rating of each level; (5) give the score to each element based on the score index system Once flood hazard and shelter suitability maps were ready, a bivariate choropleth analysis was used to visualise the priority area for the emergency shelter to be established Bivariate choropleth maps are the most popular type of univariate thematic map that visualise two variables [78] In this process, ArcGIS Map Algebra was used for the calculation Results The flood inundation maps developed for the whole country of Bangladesh are presented in Fig The results demonstrate that 7.11% of the area was inundated by overflow water in June 2017 and 8.99% in August 2017 Similarly, more areas were flooded during the awful floods in June, July and August 2018; June, July and August 2019, and July 2020, with inundation covering 7.26%, 10.87%, 11.07%, 9.50%, 10.56%, 5.01% and 11.14% of the country, respectively Analysis of the flooded areas in the divisional regions of Bangladesh shows that the Sylhet division experiences more floods almost every year Among the eight divisions of Bangladesh, the Sylhet division was inundated to the maximum extent in July 2020 In June 2017, June 2018, June 2019, July 2019 and July 2020, the flood inundated areas were 2.76%, 2.59%, 2.43%, 2.69% and 3.10%, respectively In addition, floods also caused havoc in the Rajshahi division in August 2017, August 2018, July 2018, July 2019 and July 2020, representing 1.26%, 2.36%, 1.93%, 2.17%, and 2.01% of the area of Bangladesh In 2017, the Rangpur Division of Bangladesh accounted K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig GIS layers used for the flood suitability mapping Discussion 0.21%, 1.58%, 0.19%, 1.62%, 2.72%, 2.65% and 0.75% of the extremely highly suitable area, respectively, and 0.89%, 3.27%, 0.54%, 2.37%, 3.47%, 4.00% and 1.61% represent the very highly suitable area, respectively, and so can be considered for flood shelter site selection Among the divisions of Bangladesh, the Barisal division does not fall into the very high suitability for flood shelter zone instead of cyclone shelters Considering the Upazila level analysis, from the 89 Upazila districts, 23 should be selected for flood shelter construction on a priority basis (Fig S2 and Table S3) Based on the developed flood hazard map, the suitability a bivariate choropleth analysis was performed as is shown in Fig 10 Bangladesh is one of the most frequent flood disasters affected country in the world, and it is under constant threat of flooding, which damages infrastructure, lives, a considerable amount of food and causes substantial financial losses The flood inundation extent, flood hazard and flood shelter suitability map are beneficial for the disaster management authorities in terms of supporting the preparation, relief and rescue operations in Bangladesh Particularly during the flood and cloudy monsoon seasons, a compelling synthetic aperture radar (SAR) image-based real-time support K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig Flood extents of June and August 2017; June, July and August 2018; June, July and August 2019; and July 2020 of Bangladesh during flooding incidents, mapping and monitoring flood conditions, including mapping the flood inundation area hugely crucial Considering the overall disaster circumstances in Bangladesh, our study provides realtime flood inundation maps for the developed a series of flood inundation maps of Bangladesh from 2017 to 2020 for different months using freely available Sentinel-1 SAR data utilizing an online platform and replicable methodology The analysed flood inundation maps offer temporal and spatial dynamics changes of the flooding region throughout the county without downloading bulk image files and lengthy desktop image processing The study's findings are appropriate for resource allocation decisions in rural K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig Flood hazard map of Bangladesh The worry of flood disaster management is establishing shelters in suitable locations, but this is ignored in Bangladesh as sometimes flood shelters are constructed on sites close to influential elite villagers [51] In addition, sometimes, the Bangladesh government has attempted to turn a school into a flood shelter in some places along the Jamuna river, and sometimes an educational building-cum-flood-cyclone shelter is on its way to established sinking into the riverbed before the inauguration[58] In this case, remote sensing and GIS technology can play a vital role in addressing those issues and identifying locations based on unbiased scientific analysis In this regard, our study's findings, which can visualise the sites with the most potential for establishing flood shelters, are genuinely needed Flood hazard zonation is also an essential step for future flood disaster management The probability that a flood of a certain intensity will occur planning for disaster management [51] Using the long-term flood extents and other factors, flood hazard and flood shelter suitability maps were produced for establishing safe flood evacuation sites [51,84] Since Bangladesh is a low-lying country, it is challenging to avoid floods without the intervention of flood control work Usually, the regular flood inundation areas strongly correlate with the locations and flood control activities [8] Among the different kinds of flood prevention initiations, the provision of emergency safe shelters is considered the best flood management approach as it does not cause any negative consequences on water flow and environmental conditions [66] Nevertheless, these safe shelters must be built on locations of maximum efficiency for safer relocation Shelters built far from settlements or on inaccessible sites are not helpful for mitigation K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig Flood shelter suitability map of Bangladesh inundation maps play a crucial role in planning, decision-making and executing flood management work [96] For this study, the use of no-cost Sentinel-1 radar images revealed a high potential for flood mapping due to their open-access facility Furthermore, using the image processing techniques using GEE produced a better classification accuracy on flood maps quickly [52,94] and enabled the endowment of a framework for rapid flood monitoring on a national level [44] Nevertheless, there were some difficulties in flood maps due to the floating vegetated areas [83] On the Sentinel-1 SAR images, seldom cultivated land for paddy plantation appeared as inundated areas Mapping flood in the mountain areas was another challenge as mountain shadow also give similar backscatter profiles or spectral response of the inundation areas To overcome these problems, ground knowledge is essential Alternatively, over an extended period is determined [18,65,88] Flood hazard is mainly used to define flood-prone zones [88] There are vast populations in lowland areas affected by flood disasters because flood hazard areas are not demarcated using GIS and remote sensing approaches The flood hazard map can strongly discourage people from establishing their houses in floodprone areas In the past, several flood mapping investigation was conducted for the 1988 flood mapping to assist relief works [51] After that, few flood inundation mapping studies have been undertaken mainly through theoretical researchers related to flood in Bangladesh without focusing on emergency response and post-flood disaster management identifying flood hazard and flood shelter suitability [22,28,65] However, real-time flood map performs a vital role in relief operations [9,16] Also, long term flood 10 K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Fig 10 Priority area for flood shelter construction based on the bivariate choropleth analysis using flood hazard and flood shelter suitability maps in Bangladesh a drone camera is a rising tool for mapping real-time flood inundation in disaster management [19,47] Due to flying continuation and payload limit, the drone would not be practical if vast areas were flooded [56] Due to the low elevated flat landscape and climatic features, around 80% of the population is at risk of flooding Following the devastating flood disaster occurrences, the Government of Bangladesh (GOB) has made significant efforts to reduce its disaster vulnerability primarily through post-disaster projects Executing the resilient flood management process a guideline on Flood Response Preparedness Plan of Bangladesh also prepared[57] Bangladesh recently constructed flood protection barriers and switches on different rivers and have been dredging the canals and less than hundred flood shelters [57] To comprehensively flood disaster management policies in Bangladesh, Flood Forecasting and Warning Centre (FFWC) under the Bangladesh Water Development Board (BWDB) deployed a flood prediction models to generate possible flooding scenarios intent to disseminate between the multiple stakeholders working floods [22,43] Linked to previous struggles, Bangladesh is now much more protected from disasters due to these post-disaster activities However, based on the published research, opinion determined that considerably less research has been conducted for rapid flood inundation mapping using SAR images [86] A rapid flood extent map can be used to deliver information on the flood hazards during response operations to mitigate damage [37,97] In this aspect, our study on flood-prone zones and shelter suitability assessments using the historical flood extents of June and August 2017; June, July and August 2018; June, July and August 2019; and July 2020 of 11 K Uddin, M.A Matin Progress in Disaster Science 11 (2021) 100185 Appendix A Supplementary data Bangladesh used a robust integrated method based on remote sensing and GIS In addition, the study described an efficient method of identifying flood hazard and flood suitability maps based on a freely available dataset Finally, the methodology provides a potential solution to determine safe shelter suitability and the characterisation of flood-prone zones for bridging the GIS data gaps for disaster management in Bangladesh Supplementary data to this article can be found 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This study also included flood shelters suitability and flood hazard zonation models developed in ArcGIS using Model Builder that can be easily conceived by any GIS analyst from other flood disaster-prone countries Generating maps for secure and safe accommodation during floods to help disaster risk reduction procedures was the study's primary aim Floods are widespread in Bangladesh, and it is not possible to stop them, but they can be managed to reduce the loss of life and resources The method used for flood hazard and flood shelter suitability analysis can be helpful in disaster mitigation Finally, this mapping study can firmly guide long-term overall disasters preparedness and planning approaches across Bangladesh Author contributions Kabir Uddin: : Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Validation; Visualization; Writing - original draft; Writing - review & editing Mir A.Matin: Project administration; Writing - review & editing Declaration of Competing Interest The views and interpretations in this publication are those of the authors They are not necessarily attributable to ICIMOD and not imply the expression of any opinion by ICIMOD concerning the legal status of any country, territory, city or area or its authority, or concerning the delimitation of its frontiers or boundaries, or the endorsement of any product Acknowledgments The authors are very thankful to Pema Gyamtsho, Director General and Izabella Koziell, Deputy Director General of ICIMOD his support and encouragement This study was partially supported by core funds of ICIMOD, contributed by the governments of Afghanistan, Australia, Austria, Bangladesh, Bhutan, China, India, Myanmar, Nepal, Norway, Pakistan, Switzerland, and the United Kingdom This paper has been prepared under the SERVIR-HKH initiative funded by NASA and USAID Our special gratitude goes to Birendra Bajracharya, Program Coordinator, MENRIS, ICIMOD for their support in bringing out 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Bangladesh during flooding incidents, mapping and monitoring flood conditions, including mapping the flood inundation area hugely crucial Considering the overall disaster circumstances in Bangladesh, our... work in the ground Also, determining the flood-prone site and the suitable location for constructing emergency flood shelters using remote sensing and geographic information systems tools Finally,