DATA PROCESSING ARCHITECTURES FOR MONITORING FLOODS USING SENTINEL-1

10 citations as recorded by crossref.

1. A Sentinel-1 Backscatter Datacube for Global Land Monitoring Applications W. Wagner et al. 10.3390/rs13224622
2. Utilising Sentinel-1’s orbital stability for efficient pre-processing of sigma nought backscatter C. Navacchi et al. 10.1016/j.isprsjprs.2022.07.023
3. Extraction of Information on the Flooding Extent of Agricultural Land in Henan Province Based on Multi-Source Remote Sensing Images and Google Earth Engine J. Cui et al. 10.3390/agronomy13020355
4. Integrating Copernicus Satellite Products and Ground-Truthing for Documenting and Monitoring the Impact of the 2022 Extreme Floods in Pakistan on Cultural Heritage M. Khan et al. 10.3390/rs15102518
5. Flooded area detection and mapping from Sentinel-1 imagery. Complementary approaches and comparative performance evaluation A. Toma et al. 10.1080/22797254.2024.2414004
6. Monitoring Post-Flood Recovery of Croplands Using the Integrated Sentinel-1/2 Imagery in the Yangtze-Huai River Basin M. Li et al. 10.3390/rs14030690
7. Combining SAR and Optical Earth Observation with Hydraulic Simulation for Flood Mapping and Impact Assessment E. Psomiadis et al. 10.3390/rs12233980
8. Deriving exclusion maps from C-band SAR time-series in support of floodwater mapping J. Zhao et al. 10.1016/j.rse.2021.112668
9. Characterizing the 2020 summer floods in South China and effects on croplands X. Chen et al. 10.1016/j.isci.2023.107096
10. High-Resolution Flood Monitoring Based on Advanced Statistical Modeling of Sentinel-1 Multi-Temporal Stacks R. Colacicco et al. 10.3390/rs16020294