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Validating the GIS-based Flood Susceptibility Model Using Synthetic Aperture Radar (SAR) Data in Sengah Temila Watershed, Landak Regency, Indonesia

Forum Geografi · Vol. 36 No. 2 (2023) · hlm. 185–201

DOI
10.23917/forgeo.v36i2.16368
ISSN
2460-3945, 0852-0682
Terbit
2023-03-30
Penerbit
Universitas Muhammadiyah Surakarta
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc-nd/4.0

Abstrak

In Indonesia, especially in regions where natural conditions and human activity coexist, flood disasters are a strong possibility. Flooding regularly has an impact on Sengah Temila, which is a component j/ of Indonesia's West Kalimantan Province. The issue in Sengah Temila is that there is little knowledge of the distribution of flood susceptibility in this region. The GIS-based flood susceptibility model has been widely used in Indonesia, but research dedicated to validating the model is limited. SAR-based analysis has been used for flood mapping in Indonesia, but its use for validating flood models has been limited. The objective of this study is to identify the optimal weighting scenario for a GIS-based multi-criteria analysis flood model for use in the Sengah Temila Watershed. The GIS-based model is created by merging spatial parameters, including slope, elevation, flow accumulation, drainage density, land use and land cover (LULC), soil type, normalized difference vegetation index (NDVI), curvature, rainfall, distance to river, and topographic wetness index (TWI) with weighted multi-criteria analysis. In addition, Sentinel-1 GRD images from before and after the floods have been retrieved from Google Earth Engine using past floods of the watershed. In order to create a SAR-based flood model, the researchers then integrated and categorized the results. Eleven weighting scenarios were used to create eleven GIS-based flood models. To calculate the degree of spatial similarity, all of these models were contrasted with the SAR-based model using the Fuzzy Kappa approach. We found that in order to achieve ideal weighting, slope, topographic wetness index (TWI), rainfall, and flow accumulation should each be given a larger value.

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Gunarto LatamaHasanuddin University3
Bistari BistariAfiliasi tidak diketahui3
Aynaz LotfataAfiliasi tidak diketahui2
Hamdani HamdaniMulawarman University2
Tarina DashelaAfiliasi tidak diketahui2
Veven VevenAfiliasi tidak diketahui2
Abas RudinUniversitas Halu Oleo1
Zainuddin ZainuddinHasanuddin University1
Badraeni BadraeniHasanuddin University1
Andi Aliah HidayaniHasanuddin University1
Besse Tenri NurkamilahHasanuddin University1
Dody Dh. TrijunoHasanuddin University1
Elmi Nurhaidah ZainuddinHasanuddin University1
Edison SaadeHasanuddin University1
Hasni Yulianti AzisHasanuddin University1
Irfan AmbasHasanuddin University1
Muhammad Iqbal DjawadHasanuddin University1
Marlina AchmadHasanuddin University1
Muh. Yusri KarimHasanuddin University1
Siti AslamyahHasanuddin University1
Yushinta FujayaHasanuddin University1
Mey Angraeni TamalSekolah Tingi Pertanian Kutai Timur1
Joni AriansyahAfiliasi tidak diketahui1
Suharyon SuharyonBadan Pengkajian dan Penerapan Teknologi1
Hendri PurnamaAfiliasi tidak diketahui1
Asmi Citra Malina A.R. TassakkaAfiliasi tidak diketahui1
Muhammad SahirAfiliasi tidak diketahui1
Herliyanti HerliyantiAfiliasi tidak diketahui1
Nur Ulfa DamayantiAfiliasi tidak diketahui1
Hanny Wahyuningtiyas SitorusAfiliasi tidak diketahui1
Rizky Ahmad YudanegaraAfiliasi tidak diketahui1
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Nia KurniatiAfiliasi tidak diketahui1
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Sumber metadata: OAI-PMH (metadata jurnal) http://journals.ums.ac.id/index.php/fg/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Validating the GIS-based Flood Susceptibility Model Using Synthetic Aperture Radar (SAR) Data in Sengah Temila Watershed, Landak Regency, Indonesia</dc:title>
	<dc:creator>Purwanto, Ajun</dc:creator>
	<dc:creator>Andrasmoro, Dony</dc:creator>
	<dc:creator>Eviliyanto, Eviliyanto</dc:creator>
	<dc:creator>Rustam, Rustam</dc:creator>
	<dc:creator>Ibrahim, Mohd Hairy</dc:creator>
	<dc:creator>Rohman, Arif</dc:creator>
	<dc:subject xml:lang="en-US">Geographical Information System; Remot Sensing; Geograpgy</dc:subject>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:description xml:lang="en-US">In Indonesia, especially in regions where natural conditions and human activity coexist, flood disasters are a strong possibility. Flooding regularly has an impact on Sengah Temila, which is a component j/ of Indonesia's West Kalimantan Province. The issue in Sengah Temila is that there is little knowledge of the distribution of flood susceptibility in this region. The GIS-based flood susceptibility model has been widely used in Indonesia, but research dedicated to validating the model is limited. SAR-based analysis has been used for flood mapping in Indonesia, but its use for validating flood models has been limited.  The objective of this study is to identify the optimal weighting scenario for a GIS-based multi-criteria analysis flood model for use in the Sengah Temila Watershed. The GIS-based model is created by merging spatial parameters, including slope, elevation, flow accumulation, drainage density, land use and land cover (LULC), soil type, normalized difference vegetation index (NDVI), curvature, rainfall, distance to river, and topographic wetness index (TWI) with weighted multi-criteria analysis. In addition, Sentinel-1 GRD images from before and after the floods have been retrieved from Google Earth Engine using past floods of the watershed. In order to create a SAR-based flood model, the researchers then integrated and categorized the results. Eleven weighting scenarios were used to create eleven GIS-based flood models. To calculate the degree of spatial similarity, all of these models were contrasted with the SAR-based model using the Fuzzy Kappa approach. We found that in order to achieve ideal weighting, slope, topographic wetness index (TWI), rainfall, and flow accumulation should each be given a larger value.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Muhammadiyah Surakarta</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2023-03-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journals.ums.ac.id/index.php/fg/article/view/16368</dc:identifier>
	<dc:identifier>10.23917/forgeo.v36i2.16368</dc:identifier>
	<dc:source xml:lang="en-US">Forum Geografi; Vol 36, No 2 (2022): December 2022; 185 - 201</dc:source>
	<dc:source>2460-3945</dc:source>
	<dc:source>0852-0682</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.ums.ac.id/index.php/fg/article/view/16368/8334</dc:relation>
	<dc:coverage xml:lang="en-US"></dc:coverage>
	<dc:coverage xml:lang="en-US"></dc:coverage>
	<dc:coverage xml:lang="en-US"></dc:coverage>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Ajun Purwanto, Dony Andrasmoro, Eviliyanto Eviliyanto, Rustam Rustam, Mohd Hairy Ibrahim, Arif Rohman</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-nc-nd/4.0</dc:rights>
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