GIS and remote sensing-based spatiotemporal analysis of cumulative flood risk over Bangladesh’s national highways

Kashfia Nowrin Choudhury (), Helmut Yabar () and Takeshi Mizunoya ()
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Kashfia Nowrin Choudhury: University of Tsukuba
Helmut Yabar: University of Tsukuba
Takeshi Mizunoya: University of Tsukuba

Asia-Pacific Journal of Regional Science, 2022, vol. 6, issue 1, No 15, 335-364

Abstract: Abstract The national highways (NHs) play a significant role in the economy of Bangladesh. However, natural disasters, especially floods, interrupt the traffic flow almost annually affecting the sustainable growth of the economy. Therefore, understanding the extent and patterns of historical flood risk over the NHs is important to identify the most affected areas. The study combined remote sensing and GIS to map the flooding risks over the NHs. To conduct the analysis this study selected flood events with over 100 deaths from the past 20 years. The results identified not only the NH location but the affected lengths as well. With further analysis, it was obvious that a single impact of the flood may appear insignificant, but the cumulative risk is severe. The study area received a cumulative risk of 1400 km and the average flood affected approximately 200 km of the area. Five NHs (i.e. N1, N5, N6, N7, and N8) received a cumulative risk of over 200 km from seven floods. The 2007 July to October flood affected 15% of the study area and reached the highest risk in this study. A similar pattern of risk was also noticed over five NHs (i.e. N3, N4, N6, N7, and N8) multiple times. Further investigation of similarly affected road locations created an opportunity to address repeated impacts. The results of this study can contribute to the establishment of a reliable historical database that identifies the most flood-affected roads with specific lengths and locations for further decision-making regarding relevant flood mitigation policy formulation.

Keywords: National highways; Flood; Bangladesh; GIS; MODIS (search for similar items in EconPapers)
JEL-codes: L91 Q54 R42 Y91 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s41685-021-00216-5

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