Bimal Kanti Paul
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Bimal Kanti Paul has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Jane Southworth
Department of Geography, University of Florida, Gainesville, FL 32611, USA
1 shared publication - Joynal Abedin
Texas A&M University
1 shared publication - Kevin D. Ash
University of Florida
1 shared publication - Mohammad Mehedy Hassan
Department of Geography, University of Florida, 3141 Turlington Hall and P.O. Box 117315, Gainesville, FL 32611-7315, USA
1 shared publication Rejuan Hossain Bhuiyan
Professor, Department of Geography and Environment, University of Dhaka, Bangladesh
1 shared publication
Latest Publications
- Open Access
- 21 October 2020
- Published by MDPI AG in Remote Sensing
- Vol. 12 (20) , 3454
A Quantitative Framework for Analyzing Spatial Dynamics of Flood Events: A Case Study of Super Cyclone Amphan
Identifying the flooding risk hotspot is crucial for aiding a rapid response and prioritizes mitigation efforts over large disaster impacted regions. While climate change is increasing the risk of floods in many vulnerable regions of the world, the commonly used crisis map is inefficient and cannot rapidly determine the spatial variation and intensity of flooding extension across the affected areas. In such cases, the Local Indicators of Spatial Association (LISA) statistic can detect heterogeneity or the flooding hotspot at a local spatial scale beyond routine mapping. This area, however, has not yet been studied in the context of the magnitude of the floods. The present study incorporates the LISA methodology including Moran’s I and Getis–Ord Gi* to identify the spatial and temporal heterogeneity of the occurrence of flooding from super cyclone Amphan across 16 coastal districts of Bangladesh. Using the Synthetic Aperture Radar (SAR) data from Sentinel-1 and a Support Vector Machine (SVM) classification, “water” and “land” were classified for the pre-event (16 May 2020) and post-events (22 May, 28 May, and 7 June 2020) of the area under study. A Modified Normalized Difference Water Index (MNDWI), and visual comparison were used to evaluate the flood maps. A compelling agreement was accomplished between the observed and predicted flood maps, with an overall precision of above 95% for all SAR classified images. As per this study, 2233 km2 (8%) of the region is estimated to have been inundated on 22 May. After this point, the intensity and aerial expansion of flood decreased to 1490 km2 by 28 May before it increased slightly to 1520 km2 (2.1% of the study area) on 7 June. The results from LISA indicated that the main flooding hotspots were located in the central part, particularly in the region off the north-east of the mangrove forest. A total of 238 Unions (smallest administrative units) were identified as high flooding hotspots (p < 0.05) on 22 May, but the number of flooding hotspots dropped to 166 in the second week (28 May) after Amphan subsided before it increased to a further 208 hotspots (p < 0.05) on 7 June due to incessant rainfall and riverbank failure in the south-west part of the study area. As such, an appropriate, timely, and cost-effective strategy would be to assess existing flooding management policies through the identified flooding hotspot regions. This identification would then allow for the creation of an improved policy to help curtail the destructive effects of flooding in the future.
- 21 October 2020
- Published by MDPI AG in Remote Sensing
- Vol. 12 (20) , 3454
Open AccessA Quantitative Framework for Analyzing Spatial Dynamics of Flood Events: A Case Study of Super Cyclone Amphan
Identifying the flooding risk hotspot is crucial for aiding a rapid response and prioritizes mitigation efforts over large disaster impacted regions. While climate change is increasing the risk of floods in many vulnerable regions of the world, the commonly used crisis map is inefficient and cannot rapidly determine the spatial variation and intensity of flooding extension across the affected areas. In such cases, the Local Indicators of Spatial Association (LISA) statistic can detect heterogeneity or the flooding hotspot at a local spatial scale beyond routine mapping. This area, however, has not yet been studied in the context of the magnitude of the floods. The present study incorporates the LISA methodology including Moran’s I and Getis–Ord Gi* to identify the spatial and temporal heterogeneity of the occurrence of flooding from super cyclone Amphan across 16 coastal districts of Bangladesh. Using the Synthetic Aperture Radar (SAR) data from Sentinel-1 and a Support Vector Machine (SVM) classification, “water” and “land” were classified for the pre-event (16 May 2020) and post-events (22 May, 28 May, and 7 June 2020) of the area under study. A Modified Normalized Difference Water Index (MNDWI), and visual comparison were used to evaluate the flood maps. A compelling agreement was accomplished between the observed and predicted flood maps, with an overall precision of above 95% for all SAR classified images. As per this study, 2233 km2 (8%) of the region is estimated to have been inundated on 22 May. After this point, the intensity and aerial expansion of flood decreased to 1490 km2 by 28 May before it increased slightly to 1520 km2 (2.1% of the study area) on 7 June. The results from LISA indicated that the main flooding hotspots were located in the central part, particularly in the region off the north-east of the mangrove forest. A total of 238 Unions (smallest administrative units) were identified as high flooding hotspots (p < 0.05) on 22 May, but the number of flooding hotspots dropped to 166 in the second week (28 May) after Amphan subsided before it increased to a further 208 hotspots (p < 0.05) on 7 June due to incessant rainfall and riverbank failure in the south-west part of the study area. As such, an appropriate, timely, and cost-effective strategy would be to assess existing flooding management policies through the identified flooding hotspot regions. This identification would then allow for the creation of an improved policy to help curtail the destructive effects of flooding in the future.
Urban earthquake hazard: perceived seismic risk and preparedness in Dhaka City, Bangladesh
Bangladesh is vulnerable to seismic events. Experts suspect that if an earthquake with a 7.0 magnitude occurred in large cities of Bangladesh, there would be a major human tragedy due to the structural failure of many buildings. The primary objectives of this paper are to examine seismic risk perception among residents of Dhaka City and investigate their levels of earthquake preparedness. A questionnaire survey conducted among 444 residents of the city provided the major source of data for the paper. The survey results suggest that an overwhelming majority of the respondents were not prepared for a major earthquake, which is anticipated to occur in Dhaka. Multivariate analysis of survey data reveals that value of residential unit and respondent educational levels appear as the most significant determinants of preparedness status of the respondents. This study recommends increasing earthquake awareness and preparedness among residents of Dhaka City.
Urban earthquake hazard: perceived seismic risk and preparedness in Dhaka City, Bangladesh
Bangladesh is vulnerable to seismic events. Experts suspect that if an earthquake with a 7.0 magnitude occurred in large cities of Bangladesh, there would be a major human tragedy due to the structural failure of many buildings. The primary objectives of this paper are to examine seismic risk perception among residents of Dhaka City and investigate their levels of earthquake preparedness. A questionnaire survey conducted among 444 residents of the city provided the major source of data for the paper. The survey results suggest that an overwhelming majority of the respondents were not prepared for a major earthquake, which is anticipated to occur in Dhaka. Multivariate analysis of survey data reveals that value of residential unit and respondent educational levels appear as the most significant determinants of preparedness status of the respondents. This study recommends increasing earthquake awareness and preparedness among residents of Dhaka City.