Please use this identifier to cite or link to this item: https://repository.unej.ac.id/xmlui/handle/123456789/112623
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dc.contributor.authorHIDAYAH, Entin
dc.contributor.authorPRANADIARSO, Tedy
dc.contributor.authorHALIK, Gusfan
dc.contributor.authorINDARTO, Indarto
dc.contributor.authorLEE, Wei-Koon
dc.contributor.authorMARUF, Mokhammad Farid
dc.date.accessioned2023-03-09T04:36:12Z
dc.date.available2023-03-09T04:36:12Z
dc.date.issued2023-03-08
dc.identifier.urihttps://repository.unej.ac.id/xmlui/handle/123456789/112623
dc.description.abstractFlood mapping is an essential component of planning flood mitigation. The availability of remote sensing data makes rapid flood mapping possible. This article develops an accurate method for rapid flood mapping using satellite imagery. Sentinel-2 imagery was tested by acquiring data before and after a flood event in a lowland area. Flooding extraction was performed using the newly developed Flood Inundation Extraction Index (FIEI) and compared to the Modified Normalized Difference Water Index (MNDWI), the most commonly used index. Based on the choice of threshold, the results are divided into flooded and non-flooded areas. Evaluation of the performance accuracy based on the total and kappa coefficients showed that the FIEI approach is more accurate than the MNDWI approach.en_US
dc.language.isoenen_US
dc.publisherActa geographica Slovenicaen_US
dc.subjectrapid flood mappingen_US
dc.subjectSentinel-2en_US
dc.subjectModified Normalized Difference Water Indexen_US
dc.subjectFlood Inundation Extraction Indexen_US
dc.subjectkappa coefficienten_US
dc.subjectaccuracyen_US
dc.subjectINDONESIAen_US
dc.titleFlood Mapping Based On Open-Source Remote Sensing Data Using an Efficient Band Combination Systemen_US
dc.typeArticleen_US
Appears in Collections:LSP-Jurnal Ilmiah Dosen

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