Assessment of flash flood detection in Erbil city using change detection indices for SAR images
The frequency and intensity of flash floods are expected to increase due to climate change, resulting in significant casualties and damage to infrastructure and the economy. Reliable and timely flood maps are essential for an effective disaster management plan. On December 17, 2021, a severe flash f...
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| Language: | English |
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Unviversity of Technology- Iraq
2024-11-01
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| Series: | Engineering and Technology Journal |
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| Online Access: | https://etj.uotechnology.edu.iq/article_184744_aa1ca253558227e3e6cbaff8a45c81c6.pdf |
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| author | Abbas Noori Abdul Razzak Ziboon Amjed AL-Hameedawi |
| author_facet | Abbas Noori Abdul Razzak Ziboon Amjed AL-Hameedawi |
| author_sort | Abbas Noori |
| collection | DOAJ |
| description | The frequency and intensity of flash floods are expected to increase due to climate change, resulting in significant casualties and damage to infrastructure and the economy. Reliable and timely flood maps are essential for an effective disaster management plan. On December 17, 2021, a severe flash flood in Erbil City resulted in twelve fatalities and extensive damage to the affected area. The ability of synthetic aperture radar (SAR) images to penetrate clouds and heavy precipitation is vital for accurate flood imaging. This study analyzed Sentinel-1 satellite-based radar images before and after the flood to detect the inundation. Two change detection techniques, the Normalized Change Index (NCI) and the Ratio Index (RI), combined with semi-automatic thresholding were employed. Both methods successfully identified the flooded region with consistent findings. The overall accuracy of NCI and RI were 90.5% and 84.3% respectively. The accuracy assessment revealed that the NCI method outperforms the RI method in detecting the flash flood event in Erbil City. This model is viable for disaster management, enabling the evaluation of damage to critical municipal infrastructure and other assets, thus supporting effective urban governance and timely response to emergencies. At the final stage of disaster management, this model can be implemented to evaluate the extent of loss on major municipal infrastructure and other properties within the area. |
| format | Article |
| id | doaj-art-0925655d9e6147d0aee68ffa6eede4c6 |
| institution | Kabale University |
| issn | 1681-6900 2412-0758 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Unviversity of Technology- Iraq |
| record_format | Article |
| series | Engineering and Technology Journal |
| spelling | doaj-art-0925655d9e6147d0aee68ffa6eede4c62024-12-01T08:32:52ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582024-11-0142111378138610.30684/etj.2024.151205.1777184744Assessment of flash flood detection in Erbil city using change detection indices for SAR imagesAbbas Noori0Abdul Razzak Ziboon1Amjed AL-Hameedawi2Civil Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq. Department of Surveying Engineering, Technical Engineering College of Kirkuk, Northern Technical University, Kirkuk 36001, Iraq.College of Engineering, Al-Esraa University, Baghdad, Iraq.Civil Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.The frequency and intensity of flash floods are expected to increase due to climate change, resulting in significant casualties and damage to infrastructure and the economy. Reliable and timely flood maps are essential for an effective disaster management plan. On December 17, 2021, a severe flash flood in Erbil City resulted in twelve fatalities and extensive damage to the affected area. The ability of synthetic aperture radar (SAR) images to penetrate clouds and heavy precipitation is vital for accurate flood imaging. This study analyzed Sentinel-1 satellite-based radar images before and after the flood to detect the inundation. Two change detection techniques, the Normalized Change Index (NCI) and the Ratio Index (RI), combined with semi-automatic thresholding were employed. Both methods successfully identified the flooded region with consistent findings. The overall accuracy of NCI and RI were 90.5% and 84.3% respectively. The accuracy assessment revealed that the NCI method outperforms the RI method in detecting the flash flood event in Erbil City. This model is viable for disaster management, enabling the evaluation of damage to critical municipal infrastructure and other assets, thus supporting effective urban governance and timely response to emergencies. At the final stage of disaster management, this model can be implemented to evaluate the extent of loss on major municipal infrastructure and other properties within the area.https://etj.uotechnology.edu.iq/article_184744_aa1ca253558227e3e6cbaff8a45c81c6.pdffloodsnormalized change indiexratio indexinfrastructuresar image |
| spellingShingle | Abbas Noori Abdul Razzak Ziboon Amjed AL-Hameedawi Assessment of flash flood detection in Erbil city using change detection indices for SAR images Engineering and Technology Journal floods normalized change indiex ratio index infrastructure sar image |
| title | Assessment of flash flood detection in Erbil city using change detection indices for SAR images |
| title_full | Assessment of flash flood detection in Erbil city using change detection indices for SAR images |
| title_fullStr | Assessment of flash flood detection in Erbil city using change detection indices for SAR images |
| title_full_unstemmed | Assessment of flash flood detection in Erbil city using change detection indices for SAR images |
| title_short | Assessment of flash flood detection in Erbil city using change detection indices for SAR images |
| title_sort | assessment of flash flood detection in erbil city using change detection indices for sar images |
| topic | floods normalized change indiex ratio index infrastructure sar image |
| url | https://etj.uotechnology.edu.iq/article_184744_aa1ca253558227e3e6cbaff8a45c81c6.pdf |
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