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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...

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Main Authors: Yi, Lin Tew, Mou, Leong Tan, Liew, Juneng, Sazali Osman,, Mohamad Hafiz Hassan,, Narimah Samat,, Chun, Kiat Chang, Li, Longhui
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2024
Online Access:http://journalarticle.ukm.my/24779/1/%5B13-25%5D%2065557-267806-1-PB.pdf
http://journalarticle.ukm.my/24779/
http://ejournal.ukm.my/gmjss/index
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spelling my-ukm.journal.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
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
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.
format Article
author Yi, Lin Tew
Mou, Leong Tan
Liew, Juneng
Sazali Osman,
Mohamad Hafiz Hassan,
Narimah Samat,
Chun, Kiat Chang
Li, Longhui
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
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
title 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_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_sort flood inundation mapping in the kelantan river basin, malaysia, using sentinel-1 sar and google earth engine
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2024
url http://journalarticle.ukm.my/24779/1/%5B13-25%5D%2065557-267806-1-PB.pdf
http://journalarticle.ukm.my/24779/
http://ejournal.ukm.my/gmjss/index
_version_ 1823533636339630080
score 13.239859

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