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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery
Edoardo Nemni, Joseph Aylett-Bullock, Samir Belabbès, et al.
Remote Sensing (2020) Vol. 12, Iss. 16, pp. 2532-2532
Open Access | Times Cited: 149

Showing 1-25 of 149 citing articles:

Deep learning methods for flood mapping: a review of existing applications and future research directions
Roberto Bentivoglio, Elvin Isufi, Sebastiaan N. Jonkman, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 16, pp. 4345-4378
Open Access | Times Cited: 203
Towards global flood mapping onboard low cost satellites with machine learning
Gonzalo Mateo‐García, Joshua Veitch-Michaelis, Lewis Smith, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 147
Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning
Goutam Konapala, Sujay V. Kumar, S. Ahmad
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 180, pp. 163-173
Open Access | Times Cited: 112
Flood Detection with SAR: A Review of Techniques and Datasets
Donato Amitrano, Gerardo Di Martino, Alessio Di Simone, et al.
Remote Sensing (2024) Vol. 16, Iss. 4, pp. 656-656
Open Access | Times Cited: 29
Rapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning
Xin Jiang, Shijing Liang, Xinyue He, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 178, pp. 36-50
Closed Access | Times Cited: 82
Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine
Timothy Mayer, Ate Poortinga, Biplov Bhandari, et al.
ISPRS Open Journal of Photogrammetry and Remote Sensing (2021) Vol. 2, pp. 100005-100005
Open Access | Times Cited: 71
Flood Modeling and Prediction Using Earth Observation Data
Guy Schumann, Laura Giustarini, Angelica Tarpanelli, et al.
Surveys in Geophysics (2022) Vol. 44, Iss. 5, pp. 1553-1578
Open Access | Times Cited: 47
FWENet: a deep convolutional neural network for flood water body extraction based on SAR images
Jingming Wang, Shixin Wang, Futao Wang, et al.
International Journal of Digital Earth (2022) Vol. 15, Iss. 1, pp. 345-361
Open Access | Times Cited: 45
Sentinel-1-Based Water and Flood Mapping: Benchmarking Convolutional Neural Networks Against an Operational Rule-Based Processing Chain
Max Bereczky, Marc Wieland, Christian Krullikowski, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022) Vol. 15, pp. 2023-2036
Open Access | Times Cited: 40
AI for climate impacts: applications in flood risk
Anne Jones, Julian Kuehnert, Paolo Fraccaro, et al.
npj Climate and Atmospheric Science (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 37
Fast high-fidelity flood inundation map generation by super-resolution techniques
Zeda Yin, Yasaman Saadati, Beichao Hu, et al.
Journal of Hydroinformatics (2024) Vol. 26, Iss. 1, pp. 319-336
Open Access | Times Cited: 11
Integrating deep learning, satellite image processing, and spatial-temporal analysis for urban flood prediction
Nasim Mohamadiazar, Ali Ebrahimian, Hossein Hosseiny
Journal of Hydrology (2024) Vol. 639, pp. 131508-131508
Closed Access | Times Cited: 11
An Overview of Flood Risk Analysis Methods
Daniel Constantin Diaconu, Romulus Costache, Mihnea Cristian Popa
Water (2021) Vol. 13, Iss. 4, pp. 474-474
Open Access | Times Cited: 51
Floodwater detection in urban areas using Sentinel-1 and WorldDEM data
David C. Mason, Sarah L. Dance, Hannah Cloke
Journal of Applied Remote Sensing (2021) Vol. 15, Iss. 03
Open Access | Times Cited: 42
Estimation of flood-exposed population in data-scarce regions combining satellite imagery and high resolution hydrological-hydraulic modelling: A case study in the Licungo basin (Mozambique)
Luís Cea, Manuel Álvarez, Jerónimo Puertas
Journal of Hydrology Regional Studies (2022) Vol. 44, pp. 101247-101247
Open Access | Times Cited: 31
Dual-Tasks Siamese Transformer Framework for Building Damage Assessment
Hongruixuan Chen, Edoardo Nemni, S. Vallecorsa, et al.
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (2022)
Open Access | Times Cited: 31
Probabilistic SAR-based water segmentation with adapted Bayesian convolutional neural network
Victor Hertel, Candace Chow, Omar Wani, et al.
Remote Sensing of Environment (2022) Vol. 285, pp. 113388-113388
Closed Access | Times Cited: 29
Harvesting the Landsat archive for land cover land use classification using deep neural networks: Comparison with traditional classifiers and multi-sensor benefits
Giorgos Mountrakis, Shahriar S. Heydari
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 200, pp. 106-119
Open Access | Times Cited: 21
The quantitative assessment of impact of pumping capacity and LID on urban flood susceptibility based on machine learning
Yingying Wu, Dunxian She, Jun Xia, et al.
Journal of Hydrology (2023) Vol. 617, pp. 129116-129116
Closed Access | Times Cited: 20
Monitoring and Mapping Floods and Floodable Areas in the Mekong Delta (Vietnam) Using Time-Series Sentinel-1 Images, Convolutional Neural Network, Multi-Layer Perceptron, and Random Forest
Chi-Nguyen Lam, Simona Niculescu, Soumia Bengoufa
Remote Sensing (2023) Vol. 15, Iss. 8, pp. 2001-2001
Open Access | Times Cited: 20
In-orbit demonstration of a re-trainable machine learning payload for processing optical imagery
Gonzalo Mateo‐García, Josh Veitch-Michaelis, Cormac Purcell, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17
Leveraging machine learning algorithms for improved disaster preparedness and response through accurate weather pattern and natural disaster prediction
Harshita Jain, Renu Dhupper, Anamika Shrivastava, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 17
S1S2-Water: A Global Dataset for Semantic Segmentation of Water Bodies From Sentinel- 1 and Sentinel-2 Satellite Images
Marc Wieland, Florian Fichtner, Sandro Martinis, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 17, pp. 1084-1099
Open Access | Times Cited: 17
Using integrated hydrological–hydraulic modelling and global data sources to analyse the February 2023 floods in the Umbeluzi Catchment (Mozambique)
Luís Cea, Manuel Álvarez, Jerónimo Puertas
Natural hazards and earth system sciences (2024) Vol. 24, Iss. 1, pp. 225-243
Open Access | Times Cited: 8
Automatic Flood Detection from Sentinel-1 Data Using a Nested UNet Model and a NASA Benchmark Dataset
Binayak Ghosh, Shagun Garg, Mahdi Motagh, et al.
PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science (2024) Vol. 92, Iss. 1, pp. 1-18
Open Access | Times Cited: 8
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