Flood mapping, damage assessment, and susceptibility zonation in northeastern Bangladesh in 2022 using geospatial datasets

被引:0
|
作者
Rahman, Md. Mizanur [1 ]
Kamruzzaman, Mohammad [1 ]
Deb, Limon [2 ]
Islam, H. M. Touhidul [3 ]
机构
[1] Bangladesh Rice Res Inst, Farm Machinery & Postharvest Technol Div, Gazipur 1701, Bangladesh
[2] Bangladesh Rice Res Inst, Agr Econ Div, Gazipur 1701, Bangladesh
[3] Begum Rokeya Univ, Dept Disaster Management, Rangpur 5400, Bangladesh
关键词
Sentinel-1; SAR; GEE; Flood map; Damage assessment; Machine learning; Susceptibility zonation; LOGISTIC-REGRESSION; SAR; BASIN; EXPERIENCE; RATIO; WATER; GIS;
D O I
10.1016/j.pdisas.2024.100402
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study assesses flood inundation, impacts, and susceptibility zones in northeastern Bangladesh during the 2022 flood. The region is highly vulnerable to recurrent flooding Due to its geographic position and climate change impacts. The Sentinel-1 SAR data on the Google Earth Engine (GEE) platform was used to generate flooded areas using a simple change detection technique with thresholding. This analysis was further supported by incorporating cropland, population, national highway, and DEM datasets for a comprehensive damage assessment. Findings show that 55.76 % (10,993.09 km2) of the area was inundated, impacting 10.69 million people and causing severe displacement and health hazards. Sylhet, Kishoreganj, and Brahmanbaria districts were the most affected, with 2.73 million impacted in Sylhet alone. Additionally, 67.87 % of agricultural land was flooded, particularly in Sunamganj, and 43.38 % of national highways (535.08 km2) were damaged. A flood susceptibility zonation map identified high-susceptibility areas like central Sunamganj and parts of Kishoreganj to assist authorities in resource allocation and mitigation. The flood extent model achieved strong predictive accuracy (AUC: 0.97 % RF, 0.96 % LR, and 0.94 % DT), providing crucial insights for regional flood management and guiding communities with limited modeling capacities.
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页数:18
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