| Autor: |
Qizhi Teng, Lanyang Luo, Shenshen Li, Lisong Xing, Kunkun Shao, Shenggang Wang, Dacheng Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Frontiers in Earth Science, Vol 12 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2296-6463 |
| DOI: |
10.3389/feart.2024.1511834 |
| Popis: |
IntroductionEffective monitoring and evaluation of floodwaters are essential for disaster prevention and mitigation. The flood inundation range can be obtained by using traditional simulation methods, but these methods still have shortcomings. This work proposes an optimization method for traditional methods.MethodsThis study aims to introduce an effective solution for the rapid and accurate extraction of flood inundation areas, emphasizing the enhancement of extraction speed and dynamic monitoring throughout the flood event. The solution uses a normalized difference water index (NDWI), a refined threshold method, and a filtering process for microwave (radar) images. Sentinel-1 SAR (Synthetic Aperture Radar) and Sentinel-2 MSI (Multi-spectral Image) images served as the primary data sources. The Sentinel-2 images were preprocessed to extract pre-flood water bodies, while the Sentinel-1 SAR images were processed using the proposed filtering method to identify post-flood inundation areas.ResultsThe application and validation of this framework are demonstrated through the case of the 2020 flood event in Tongling, Anhui Province. The framework’s performance was validated through comparison with ground truth data, yielding high kappa accuracies of 98% for optical images and 89% for Synthetic Aperture Radar. The findings highlight the framework’s ability to capture high-accuracy changes in flood inundation areas and to characterize the dynamic process of flood inundation area changes.DiscussionThis study contributes to the field by enhancing the extraction speed and scope of water bodies from SAR images and improving the quality of microwave remote sensing data processing. It offers valuable insights for emergency rapid response and situational awareness in the context of extreme weather events and associated flood disasters. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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