Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City)
Flood is known as one of the natural disasters that cause financial and human losses not only in developing countries but also in the developed countries. Synthetic Aperture Radar (SAR) sensors are an essential data source for flood crisis planners and experts, because they have the ability to image...
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I.R. of Iran Meteorological Organization
2023-09-01
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| Series: | Nīvār |
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| Online Access: | https://nivar.irimo.ir/article_181126_0e03d4910e2c1e6aca175ee95e52b19a.pdf |
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| author | Peyman Peymankhah Sara Attarchi Meysam Moharrami |
| author_facet | Peyman Peymankhah Sara Attarchi Meysam Moharrami |
| author_sort | Peyman Peymankhah |
| collection | DOAJ |
| description | Flood is known as one of the natural disasters that cause financial and human losses not only in developing countries but also in the developed countries. Synthetic Aperture Radar (SAR) sensors are an essential data source for flood crisis planners and experts, because they have the ability to image the earth's surface independently of weather conditions and time of the day. This advantage coupled with cloud computing platforms such as Google Earth Engine (GEE) provide a tremendous opportunity for the crisis response community for effective management plans. It allows them to quickly access ready data for analysis which is of great importance in case of flooding. The purpose of this research is to quickly monitor the flood of Kashkan river. The algorithm presented in this study uses time series images of Sentinel-1 and Landsat 8 along with other auxiliary data for flood monitoring in the GEE system. This algorithm relies on multi-temporal SAR statistics to identify unexpected floods in near real-time. Additionally, historical Landsat-based surface water class probabilities are used to distinguish unexpected floods from permanent or seasonal surface water. Based on the results of this research, Sentinel-1 images have an acceptable performance for flooded areas detection in Sentinel-1 images. Therefore, managers can use this method to obtain flood information and locations in order to reduce flood damages. |
| format | Article |
| id | doaj-art-feb08d6a87b04db7a797055d7b0632ec |
| institution | Kabale University |
| issn | 1735-0565 2645-3347 |
| language | fas |
| publishDate | 2023-09-01 |
| publisher | I.R. of Iran Meteorological Organization |
| record_format | Article |
| series | Nīvār |
| spelling | doaj-art-feb08d6a87b04db7a797055d7b0632ec2025-01-05T10:54:12ZfasI.R. of Iran Meteorological OrganizationNīvār1735-05652645-33472023-09-0147122-123829410.30467/nivar.2023.417413.1265181126Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City)Peyman Peymankhah0Sara Attarchi1Meysam Moharrami2M.Sc. Student, Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, IranDepartment of Remote sensing and GIS, Faculty of Geography, University of TehranPhD Student, Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, IranFlood is known as one of the natural disasters that cause financial and human losses not only in developing countries but also in the developed countries. Synthetic Aperture Radar (SAR) sensors are an essential data source for flood crisis planners and experts, because they have the ability to image the earth's surface independently of weather conditions and time of the day. This advantage coupled with cloud computing platforms such as Google Earth Engine (GEE) provide a tremendous opportunity for the crisis response community for effective management plans. It allows them to quickly access ready data for analysis which is of great importance in case of flooding. The purpose of this research is to quickly monitor the flood of Kashkan river. The algorithm presented in this study uses time series images of Sentinel-1 and Landsat 8 along with other auxiliary data for flood monitoring in the GEE system. This algorithm relies on multi-temporal SAR statistics to identify unexpected floods in near real-time. Additionally, historical Landsat-based surface water class probabilities are used to distinguish unexpected floods from permanent or seasonal surface water. Based on the results of this research, Sentinel-1 images have an acceptable performance for flooded areas detection in Sentinel-1 images. Therefore, managers can use this method to obtain flood information and locations in order to reduce flood damages.https://nivar.irimo.ir/article_181126_0e03d4910e2c1e6aca175ee95e52b19a.pdfflood monitoringsentinel-1landsat-8gee |
| spellingShingle | Peyman Peymankhah Sara Attarchi Meysam Moharrami Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City) Nīvār flood monitoring sentinel-1 landsat-8 gee |
| title | Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City) |
| title_full | Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City) |
| title_fullStr | Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City) |
| title_full_unstemmed | Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City) |
| title_short | Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City) |
| title_sort | rapid flood monitoring using sentinel 1 and landsat 8 images case study kashkan river poldakhter city |
| topic | flood monitoring sentinel-1 landsat-8 gee |
| url | https://nivar.irimo.ir/article_181126_0e03d4910e2c1e6aca175ee95e52b19a.pdf |
| work_keys_str_mv | AT peymanpeymankhah rapidfloodmonitoringusingsentinel1andlandsat8imagescasestudykashkanriverpoldakhtercity AT saraattarchi rapidfloodmonitoringusingsentinel1andlandsat8imagescasestudykashkanriverpoldakhtercity AT meysammoharrami rapidfloodmonitoringusingsentinel1andlandsat8imagescasestudykashkanriverpoldakhtercity |