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Coastal flooding in Asian megadeltas: Recent advances, persistent challenges, and call for actions amidst local and global changes
Asian megadeltas, specifically the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya,
Mekong, and Red River deltas host half of the world's deltaic population and are vital for …
Mekong, and Red River deltas host half of the world's deltaic population and are vital for …
Residual wave vision U-Net for flood map** using dual polarization Sentinel-1 SAR imagery
The increasing severity, duration, and frequency of destructive floods can be attributed to
shifts in climate, infrastructure, land use, and population demographics. Obtaining precise …
shifts in climate, infrastructure, land use, and population demographics. Obtaining precise …
A near-real-time flood detection method based on deep learning and SAR images
X Wu, Z Zhang, S ** is essential
for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep …
for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep …
Urban flood susceptibility map** using remote sensing, social sensing and an ensemble machine learning model
Flood susceptibility map** is crucial for urban disaster management. However, the
heterogeneity of urban land use and the complexity of terrain pose challenges to the …
heterogeneity of urban land use and the complexity of terrain pose challenges to the …
SAR-TSCC: A novel approach for long time series SAR image change detection and pattern analysis
Change detection has played an increasingly important role in multitemporal remote
sensing applications recently. Long time series analysis is providing new information of land …
sensing applications recently. Long time series analysis is providing new information of land …
[HTML][HTML] Improving the accuracy of flood susceptibility prediction by combining machine learning models and the expanded flood inventory data
H Yu, Z Luo, L Wang, X Ding, S Wang - Remote Sensing, 2023 - mdpi.com
Sufficient historical flood inventory data (FID) are crucial for accurately predicting flood
susceptibility using supervised machine learning models. However, historical FID are …
susceptibility using supervised machine learning models. However, historical FID are …
Unsupervised color-based flood segmentation in uav imagery
G Simantiris, C Panagiotakis - Remote Sensing, 2024 - mdpi.com
We propose a novel unsupervised semantic segmentation method for fast and accurate
flood area detection utilizing color images acquired from unmanned aerial vehicles (UAVs) …
flood area detection utilizing color images acquired from unmanned aerial vehicles (UAVs) …
[HTML][HTML] Interannual comparison of historical floods through flood detection using multi-temporal Sentinel-1 SAR images, Awash River Basin, Ethiopia
Synthetic-aperture radar (SAR) data from Sentinel-1 satellites provides unprecedented
opportunity to evaluate inter-annual flood characteristics, although consensus on best flood …
opportunity to evaluate inter-annual flood characteristics, although consensus on best flood …
[HTML][HTML] Super-resolution water body map** with a feature collaborative CNN model by fusing Sentinel-1 and Sentinel-2 images
Map** water bodies from remotely sensed imagery is crucial for understanding
hydrological and biogeochemical processes. The identification of water extent is mainly …
hydrological and biogeochemical processes. The identification of water extent is mainly …
A comparison of global flood models using Sentinel-1 and a change detection approach
Advances in numerical algorithms, improvement of computational power and progress in
remote sensing have led to the development of global flood models (GFMs), which promise …
remote sensing have led to the development of global flood models (GFMs), which promise …