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Global floods, exacerbated by climate change, pose severe threats to human life, infrastructure, and the environment.
Envisat multi-polarized asar data for flood mapping
Henry, J.-B., Chastanet, P., Fellah, K., and Desnos, Y.-L. (2006) · 1929
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Speckle filtering of synthetic aperture radar images: A review
Lee, J.-S., Jurkevich, L., Dewaele, P., Wambacq, P., and Oosterlinck, A. (1994) · 1994
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Integration of remote sensing data and gis for accurate mapping of flooded areas
Brivio, P., Colombo, R., Maggi, M., and Tomasoni, R. (2002) · 2002
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Digital processing of synthetic aperture radar data
Cumming, I. G. and Wong, F. H. (2005) · 2005
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Global perspectives on loss of human life caused by floods
Jonkman, S. N. (2005) · 2005
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Socioeconomic vulnerability and adaptation to environmental risk: a case study of climate change and flooding in bangladesh
Brouwer, R., Akter, S., Brander, L., and Haque, E. (2007) · 2007
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Mapping of flood dynamics and spatial distribution of vegetation in the amazon floodplain using multitemporal sar data
Martinez, J.-M. and Le Toan, T. (2007) · 2007
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L. (2009) · 2009
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al. (2020) · 2010
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Observing global surface water flood dynamics
Bates, P. D., Neal, J. C., Alsdorf, D., and Schumann, G. J.-P. (2014) · 2014
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Early flood detection for rapid humanitarian response: harnessing near real-time satellite and twitter signals
Jongman, B., Wagemaker, J., Revilla Romero, B., and Coughlan de Perez, E. (2015) · 2015
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A review of damage-reducing measures to manage fluvial flood risks in a changing climate
Kreibich, H., Bubeck, P., Van Vliet, M., and De Moel, H. (2015) · 2015
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An integrated approach for assessing flood impacts due to future climate and socio-economic conditions and the scope of adaptation in europe
Mokrech, M., Kebede, A., Nicholls, R., Wimmer, F., and Feyen, L. (2015) · 2015
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U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., and Brox, T. (2015) · 2015
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Social vulnerability to floods: Review of case studies and implications for measurement
Rufat, S., Tate, E., Burton, C. G., and Maroof, A. S. (2015) · 2015
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
Shi, X., Chen, Z., Wang, H., Yeung, D.-Y., Wong, W.-K., and Woo, W.-c. (2015) · 2015
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Snap (sentinel application platform) and the esa sentinel 3 toolbox
Zuhlke, M., Fomferra, N., Brockmann, C., Peters, M., Veci, L., Malik, J., and Regner, P. (2015) · 2015
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J. (2016) · 2016
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Use of sar data for detecting floodwater in urban and agricultural areas: The role of the interferometric coherence
Pulvirenti, L., Chini, M., Pierdicca, N., and Boni, G. (2016) · 2016
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Sentinel-1-based flood mapping: a fully automated processing chain
Twele, A., Cao, W., Plank, S., and Martinis, S. (2016) · 2016
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A high-resolution flood inundation archive (2016–the present) from sentinel-1 sar imagery over conus
Yang, Q., Shen, X., Anagnostou, E. N., Mo, C., Eggleston, J. R., and Kettner, A. J. (2021) · 2016
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Rethinking atrous convolution for semantic image segmentation
Chen, L.-C., Papandreou, G., Schroff, F., and Adam, H. (2017) · 2017
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Feature learning and change feature classification based on deep learning for ternary change detection in sar images
Gong, M., Yang, H., and Zhang, P. (2017) · 2017
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Opensarship 2.0: A large-volume dataset for deeper interpretation of ship targets in sentinel-1 imagery
Li, B., Liu, B., Huang, L., Guo, W., Zhang, Z., and Yu, W. (2017) · 2017
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Normalized difference flood index for rapid flood mapping: Taking advantage of eo big data
Cian, F., Marconcini, M., and Ceccato, P. (2018) · 2018
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Fully convolutional siamese networks for change detection
Daudt, R. C., Le Saux, B., and Boulch, A. (2018) · 2018
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Flood detection in gaofen-3 sar images via fully convolutional networks
Kang, W., Xiang, Y., Wang, F., Wan, L., and You, H. (2018) · 2018
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Coherent change detection for multipass sar
Monti-Guarnieri, A. V., Brovelli, M. A., Manzoni, M., Mariotti d’Alessandro, M., Molinari, M. E., and Oxoli, D. (2018) · 2018
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Unified perceptual parsing for scene understanding
Xiao, T., Liu, Y., Zhou, B., Jiang, Y., and Sun, J. (2018) · 2018
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Unet++: A nested u-net architecture for medical image segmentation
Zhou, Z., Rahman Siddiquee, M. M., Tajbakhsh, N., and Liang, J. (2018) · 2018
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Preface: remote sensing for flood mapping and monitoring of flood dynamics
Domeneghetti, A., Schumann, G. J.-P., and Tarpanelli, A. (2019) · 2019
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Sentinel-1 grd preprocessing workflow
Filipponi, F. (2019) · 2019
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Coastal inundation mapping from bitemporal and dual-polarization sar imagery based on deep convolutional neural networks
Liu, B., Li, X., and Zheng, G. (2019) · 2019
Cited alongside, same era.
Flood risk assessment in south asia to prioritize flood index insurance applications in bihar, india
Matheswaran, K., Alahacoon, N., Pandey, R., and Amarnath, G. (2019) · 2019
Cited alongside, same era.
Bigearthnet: A large-scale benchmark archive for remote sensing image understanding
Sumbul, G., Charfuelan, M., Demir, B., and Markl, V. (2019) · 2019
Cited alongside, same era.
Flood Detection in Sar Images Based on Multi-Depth Flood Detection Convolutional Neural Network
Wu, C., Yang, X., and Wang, J. (2019) · 2019
Cited alongside, same era.
Masked autoencoders are scalable vision learners
He, K., Chen, X., Xie, S., Li, Y., Dollár, P., and Girshick, R. (2022) · 2022
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Evaluation of several fully convolutional network in sar image change detection
Ji, L., Zhao, Z., Huo, W., Zhao, J., and Gao, R. (2022) · 2022
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A convnet for the 2020s
Liu, Z., Mao, H., Wu, C.-Y., Feichtenhofer, C., Darrell, T., and Xie, S. (2022) · 2022
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Examining flood vulnerability mapping approaches in developing countries: A scoping review
Membele, G. M., Naidu, M., and Mutanga, O. (2022) · 2022
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Mmflood: A multimodal dataset for flood delineation from satellite imagery
Montello, F., Arnaudo, E., and Rossi, C. (2022) · 2022
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Flood exposure and poverty in 188 countries
Rentschler, J., Salhab, M., and Jafino, B. A. (2022) · 2022
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Bevacqua, E., Vousdoukas, M. I., Zappa, G., Hodges, K., Shepherd, T. G., Maraun, D., Mentaschi, L., and Feyen, L. (2020) · 2020
Cited alongside, same era.
Sen1floods11: A georeferenced dataset to train and test deep learning flood algorithms for sentinel-1
Bonafilia, D., Tellman, B., Anderson, T., and Issenberg, E. (2020) · 2020
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MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark
Contributors, M. (2020) · 2020
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Hazard and vulnerability in urban flood risk mapping: Machine learning techniques and considering the role of urban districts
Eini, M., Kaboli, H. S., Rashidian, M., and Hedayat, H. (2020) · 2020
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Flood detection using multi-modal and multi-temporal images: A comparative study
Islam, K. A., Uddin, M. S., Kwan, C., and Li, J. (2020) · 2020
Cited alongside, same era.
Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery
Nemni, E., Bullock, J., Belabbes, S., and Bromley, L. (2020) · 2020
Cited alongside, same era.
A review of the current status of flood modelling for urban flood risk management in the developing countries
Nkwunonwo, U., Whitworth, M., and Baily, B. (2020) · 2020
Cited alongside, same era.
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A sentinel-2 multiyear, multicountry benchmark dataset for crop classification and segmentation with deep learning
Sykas, D., Sdraka, M., Zografakis, D., and Papoutsis, I. (2022) · 2022
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Regional index insurance using satellite-based fractional flooded area
Tellman, B., Lall, U., Islam, A. S., and Bhuyan, M. A. (2022) · 2022
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Flood detection in dual-polarization sar images based on multi-scale deeplab model
Wu, H., Song, H., Huang, J., Zhong, H., Zhan, R., Teng, X., Qiu, Z., He, M., and Cao, J. (2022) · 2022
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Unsupervised Flood Detection on SAR Time Series
Yadav, R., Nascetti, A., Azizpour, H., and Ban, Y. (2022) · 2022
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Complex-valued end-to-end deep network with coherency preservation for complex-valued sar data reconstruction and classification
Asiyabi, R. M., Datcu, M., Anghel, A., and Nies, H. (2023) · 2023
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Attentive decoder network for flood analysis using sentinel 1 images
Chouhan, A., Chutia, D., and Aggarwal, S. P. (2023) · 2023
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Mapping inundation extents in Poyang Lake area using Sentinel-1 data and transformer-based change detection method
Dong, Z., Liang, Z., Wang, G., Amankwah, S. O. Y., Feng, D., Wei, X., and Duan, Z. (2023) · 2023
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Cross-modal distillation for flood extent mapping
Garg, S., Feinstein, B., Timnat, S., Batchu, V., Dror, G., Rosenthal, A. G., and Gulshan, V. (2023) · 2023
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Auckland floods: city begins clean-up after ‘biggest climate event’ in New Zealand’s history
Graham-McLay, C. (2023) · 2023
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Cross-modal change detection flood extraction based on convolutional neural network
He, X., Zhang, S., Xue, B., Zhao, T., and Wu, T. (2023) · 2023
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Segment anything
Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al. (2023) · 2023
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Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the mediterranean
Kondylatos, S., Prapas, I., Camps-Valls, G., and Papoutsis, I. (2023) · 2023
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Domain adaptive cross-reconstruction for change detection of heterogeneous remote sensing images via a feedback guidance mechanism
Liu, Q., Ren, K., Meng, X., and Shao, F. (2023) · 2023
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Regionally high risk increase for precipitation extreme events under global warming
Martinez-Villalobos, C. and Neelin, J. D. (2023) · 2023
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Benchmarking and scaling of deep learning models for land cover image classification
Papoutsis, I., Bountos, N. I., Zavras, A., Michail, D., and Tryfonopoulos, C. (2023) · 2023
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Changing intensity of hydroclimatic extreme events revealed by grace and grace-fo
Rodell, M. and Li, B. (2023) · 2023
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A framework to assess remote sensing algorithms for satellite-based flood index insurance
Thomas, M., Tellman, E., Osgood, D. E., DeVries, B., Islam, A. S., Steckler, M. S., Goodman, M., and Billah, M. (2023) · 2023
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Devastating floods in Pakistan
Unicef (2022) · 2023
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Floods in pakistan: A state-of-the-art review
Waseem, H. B. and Rana, I. A. (2023) · 2023
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Pakistan: Flood Damages and Economic Losses Over USD 30 billion and Reconstruction Needs Over USD 16 billion - New Assessment
World-Bank (2022) · 2023
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Siam-DWENet: Flood inundation detection for SAR imagery using a cross-task transfer siamese network
Zhao, B., Sui, H., and Liu, J. (2023) · 2023
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ETCI 2021 Competition on Flood Detection
NASA-IMPACT (2021) · 2024
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Dam-net: Flood detection from sar imagery using differential attention metric-based vision transformers
Saleh, T., Weng, X., Holail, S., Hao, C., and Xia, G.-S. (2024) · 2024
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A Near-Real-Time Flood Detection Method Based on Deep Learning and SAR Images
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