Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine
One of the most severe floods in Peninsular Malaysia occurred during 2021-2022, displacing over 20,000 people and resulting in two deaths in Kelantan. Accurate flood extent data during such events is crucial for effective flood management, however, gathering this information is challenging due to li...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Penerbit Universiti Kebangsaan Malaysia
2024
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| Online Access: | http://journalarticle.ukm.my/24779/1/%5B13-25%5D%2065557-267806-1-PB.pdf |
| _version_ | 1824449812762722304 |
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| author | Yi, Lin Tew Mou, Leong Tan Liew, Juneng Sazali Osman, Mohamad Hafiz Hassan, Narimah Samat, Chun, Kiat Chang Li, Longhui |
| author_facet | Yi, Lin Tew Mou, Leong Tan Liew, Juneng Sazali Osman, Mohamad Hafiz Hassan, Narimah Samat, Chun, Kiat Chang Li, Longhui |
| author_sort | Yi, Lin Tew |
| collection | UKM |
| description | One of the most severe floods in Peninsular Malaysia occurred during 2021-2022, displacing over 20,000 people and resulting in two deaths in Kelantan. Accurate flood extent data during such events is crucial for effective flood management, however, gathering this information is challenging due to limited access to affected area. Google Earth Engine (GEE) offers rapid satellite image processing for flood inundation mapping, making it an effective tool for this purpose. In this study, GEE was utilized to generate flood inundation maps for the Kelantan River Basin (KRB) using Sentinel-1 SAR data. Site inspections and Sentinel-2 Multispectral Instrument (MSI) satellite images of the actual flood regions were then used to validate the flood inundation maps. Additionally, this study evaluated the effects of three distance thresholds (3-, 4- and 5-pixel) to differentiate inundated area from preliminary water surfaces. The findings showed that the flood inundation maps achieved an accuracy of 57 – 60%, with the highest accuracy observed under the 5-pixel threshold. The 2021-2022 flood, with an inundated area of 8.92 km2, was one of the worst experiences in Kota Bharu. These findings provide valuable insights to support local authorities in designing better flood mitigation strategies for the future. |
| first_indexed | 2025-02-19T02:08:47Z |
| format | Article |
| id | ukm.eprints-24779 |
| institution | Universiti Kebangsaan Malaysia |
| language | English |
| last_indexed | 2025-02-19T02:08:47Z |
| publishDate | 2024 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| record_format | dspace |
| spelling | ukm.eprints-247792025-02-07T01:53:37Z http://journalarticle.ukm.my/24779/ Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine Yi, Lin Tew Mou, Leong Tan Liew, Juneng Sazali Osman, Mohamad Hafiz Hassan, Narimah Samat, Chun, Kiat Chang Li, Longhui One of the most severe floods in Peninsular Malaysia occurred during 2021-2022, displacing over 20,000 people and resulting in two deaths in Kelantan. Accurate flood extent data during such events is crucial for effective flood management, however, gathering this information is challenging due to limited access to affected area. Google Earth Engine (GEE) offers rapid satellite image processing for flood inundation mapping, making it an effective tool for this purpose. In this study, GEE was utilized to generate flood inundation maps for the Kelantan River Basin (KRB) using Sentinel-1 SAR data. Site inspections and Sentinel-2 Multispectral Instrument (MSI) satellite images of the actual flood regions were then used to validate the flood inundation maps. Additionally, this study evaluated the effects of three distance thresholds (3-, 4- and 5-pixel) to differentiate inundated area from preliminary water surfaces. The findings showed that the flood inundation maps achieved an accuracy of 57 – 60%, with the highest accuracy observed under the 5-pixel threshold. The 2021-2022 flood, with an inundated area of 8.92 km2, was one of the worst experiences in Kota Bharu. These findings provide valuable insights to support local authorities in designing better flood mitigation strategies for the future. Penerbit Universiti Kebangsaan Malaysia 2024-11-29 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/24779/1/%5B13-25%5D%2065557-267806-1-PB.pdf Yi, Lin Tew and Mou, Leong Tan and Liew, Juneng and Sazali Osman, and Mohamad Hafiz Hassan, and Narimah Samat, and Chun, Kiat Chang and Li, Longhui (2024) Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine. Geografia : Malaysian Journal of Society and Space, 20 (4). pp. 13-25. ISSN 2682-7727 http://ejournal.ukm.my/gmjss/index |
| spellingShingle | Yi, Lin Tew Mou, Leong Tan Liew, Juneng Sazali Osman, Mohamad Hafiz Hassan, Narimah Samat, Chun, Kiat Chang Li, Longhui Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine |
| title | Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine |
| title_full | Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine |
| title_fullStr | Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine |
| title_full_unstemmed | Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine |
| title_short | Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine |
| title_sort | flood inundation mapping in the kelantan river basin malaysia using sentinel 1 sar and google earth engine |
| url | http://journalarticle.ukm.my/24779/1/%5B13-25%5D%2065557-267806-1-PB.pdf |
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