FLOOD DETECTION IN TIME SERIES OF OPTICAL AND SAR IMAGES

23 citations as recorded by crossref.

1. Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning G. Konapala et al. 10.1016/j.isprsjprs.2021.08.016
2. AgriFloodNet: a dual patch CNN architecture for mapping flooded agricultural lands via bi-temporal multi-sensor images A. Jenifer et al. 10.1080/10106049.2022.2082549
3. Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey N. Mohammadi Foumani et al. 10.1145/3649448
4. Flood Detection with SAR: A Review of Techniques and Datasets D. Amitrano et al. 10.3390/rs16040656
5. U-net-based semantic classification for flood extent extraction using SAR imagery and GEE platform: A case study for 2019 central US flooding Z. Li & I. Demir 10.1016/j.scitotenv.2023.161757
6. SD-CapsNet: A Siamese Dense Capsule Network for SAR Image Registration with Complex Scenes B. Li et al. 10.3390/rs15071871
7. Detection of Forest Fires through Deep Unsupervised Learning Modeling of Sentinel-1 Time Series T. Di Martino et al. 10.3390/ijgi12080332
8. Towards global flood mapping onboard low cost satellites with machine learning G. Mateo-Garcia et al. 10.1038/s41598-021-86650-z
9. Multimodal Colearning Meets Remote Sensing: Taxonomy, State of the Art, and Future Works N. Kieu et al. 10.1109/JSTARS.2024.3378348
10. S1S2-Water: A Global Dataset for Semantic Segmentation of Water Bodies From Sentinel- 1 and Sentinel-2 Satellite Images M. Wieland et al. 10.1109/JSTARS.2023.3333969
11. Multimodal Satellite Image Time Series Analysis Using GAN-Based Domain Translation and Matrix Profile A. Radoi 10.3390/rs14153734
12. A new multi-source remote sensing image sample dataset with high resolution for flood area extraction: GF-FloodNet Y. Zhang et al. 10.1080/17538947.2023.2230978
13. Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications F. Mena et al. 10.1109/JSTARS.2024.3361556
14. PDFID: A high-resolution flood inundation dataset with a long time series L. Chen et al. 10.1016/j.ejrh.2024.101715
15. Sentinel-1 SAR Images and Deep Learning for Water Body Mapping F. Pech-May et al. 10.3390/rs15123009
16. Segmentation and Visualization of Flooded Areas Through Sentinel-1 Images and U-Net F. Pech-May et al. 10.1109/JSTARS.2024.3387452
17. DAM-Net: Flood detection from SAR imagery using differential attention metric-based vision transformers T. Saleh et al. 10.1016/j.isprsjprs.2024.05.018
18. Flood sequence mapping with multimodal remote sensing under the influence of dense vegetation Z. Li & I. Demir 10.1080/01431161.2024.2305629
19. RETRACTED ARTICLE: Drought Prediction and Analysis of Water level based on satellite images Using Deep Convolutional Neural Network J. Balajee & M. Saleem Durai 10.1007/s10772-021-09850-y
20. Urban flood mapping using Sentinel-1 and RADARSAT Constellation Mission image and convolutional Siamese network N. Ghasemian Sorboni et al. 10.1007/s11069-024-06434-2
21. ISSLIDE: A New InSAR Dataset for Slow SLIding Area DEtection With Machine Learning A. Bralet et al. 10.1109/LGRS.2024.3365299
22. Near-Real-Time Flood Mapping Using Off-the-Shelf Models with SAR Imagery and Deep Learning V. Katiyar et al. 10.3390/rs13122334
23. A Framework to Assess Remote Sensing Algorithms for Satellite-Based Flood Index Insurance M. Thomas et al. 10.1109/JSTARS.2023.3244098