Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques
Abstract Introduction After flood occurrences, remote sensing images provide crucial information for mapping flood inundation extent. Optical satellite images can be utilized to generate flooded area maps when the flooded areas are free from clouds. Materials and Methods In this study flooded area w...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-03-01
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| Series: | Geoenvironmental Disasters |
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| Online Access: | https://doi.org/10.1186/s40677-023-00236-7 |
| _version_ | 1827982796638912512 |
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| author | Asif Sajjad Jianzhong Lu Xiaoling Chen Chikondi Chisenga Nausheen Mazhar |
| author_facet | Asif Sajjad Jianzhong Lu Xiaoling Chen Chikondi Chisenga Nausheen Mazhar |
| author_sort | Asif Sajjad |
| collection | DOAJ |
| description | Abstract Introduction After flood occurrences, remote sensing images provide crucial information for mapping flood inundation extent. Optical satellite images can be utilized to generate flooded area maps when the flooded areas are free from clouds. Materials and Methods In this study flooded area was calculated using a variety of water indices and classification algorithms, calculated on Landsat data. Pre-flood, during flood, and post-flood satellite data were collected for in-depth flood investigation. The delineation of inundated areas was done using the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Water Ratio Index (WRI). In order to detect and compare flooded areas with water indices, the supervised maximum likelihood algorithm was also used for land use and land cover mapping. Results The results of the investigation allowed for a flooded area and recession. The analysis revealed that the flooded area covered about 68% of the study area, and remained standing for seven weeks. We used the misclassified areas approach, as determined, using the classified results, to improve the results of the flooded areas, generated through the use of each of the 3 water indices. The result showed that the MNDWI images showed better accuracy of above 90%, which reflects the reliability of the results. Conclusion This proposed remote sensing (RS) technique provides a basis for the identification of inundated areas with less misclassified areas, which enable an emergency response to be targeted, for newly flooded areas. Thus, the present study provides a novel rapid flood mapping perspective and provides a considerable contribution to flood monitoring. |
| first_indexed | 2024-04-09T22:37:52Z |
| format | Article |
| id | doaj.art-18d915621a32418cb058cd0635b13a18 |
| institution | Directory Open Access Journal |
| issn | 2197-8670 |
| language | English |
| last_indexed | 2024-04-09T22:37:52Z |
| publishDate | 2023-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Geoenvironmental Disasters |
| spelling | doaj.art-18d915621a32418cb058cd0635b13a182023-03-22T12:20:24ZengSpringerOpenGeoenvironmental Disasters2197-86702023-03-0110111810.1186/s40677-023-00236-7Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniquesAsif Sajjad0Jianzhong Lu1Xiaoling Chen2Chikondi Chisenga3Nausheen Mazhar4Department of Environmental Sciences, Faculty of Biological Sciences, Quaid-I-Azam UniversityState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityDepartment of Earth Sciences, Ndata School of Climate and Earth Sciences, Malawi University of Science and TechnologyDepartment of Geography, Lahore College for Women UniversityAbstract Introduction After flood occurrences, remote sensing images provide crucial information for mapping flood inundation extent. Optical satellite images can be utilized to generate flooded area maps when the flooded areas are free from clouds. Materials and Methods In this study flooded area was calculated using a variety of water indices and classification algorithms, calculated on Landsat data. Pre-flood, during flood, and post-flood satellite data were collected for in-depth flood investigation. The delineation of inundated areas was done using the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Water Ratio Index (WRI). In order to detect and compare flooded areas with water indices, the supervised maximum likelihood algorithm was also used for land use and land cover mapping. Results The results of the investigation allowed for a flooded area and recession. The analysis revealed that the flooded area covered about 68% of the study area, and remained standing for seven weeks. We used the misclassified areas approach, as determined, using the classified results, to improve the results of the flooded areas, generated through the use of each of the 3 water indices. The result showed that the MNDWI images showed better accuracy of above 90%, which reflects the reliability of the results. Conclusion This proposed remote sensing (RS) technique provides a basis for the identification of inundated areas with less misclassified areas, which enable an emergency response to be targeted, for newly flooded areas. Thus, the present study provides a novel rapid flood mapping perspective and provides a considerable contribution to flood monitoring.https://doi.org/10.1186/s40677-023-00236-7Riverine floodRapid flood mappingWater indicesOptical satellite dataFlood monitoring |
| spellingShingle | Asif Sajjad Jianzhong Lu Xiaoling Chen Chikondi Chisenga Nausheen Mazhar Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques Geoenvironmental Disasters Riverine flood Rapid flood mapping Water indices Optical satellite data Flood monitoring |
| title | Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques |
| title_full | Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques |
| title_fullStr | Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques |
| title_full_unstemmed | Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques |
| title_short | Rapid assessment of riverine flood inundation in Chenab floodplain using remote sensing techniques |
| title_sort | rapid assessment of riverine flood inundation in chenab floodplain using remote sensing techniques |
| topic | Riverine flood Rapid flood mapping Water indices Optical satellite data Flood monitoring |
| url | https://doi.org/10.1186/s40677-023-00236-7 |
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