Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Flood susceptibility mapping using a novel integration of multi-temporal sentinel-1 data and eXtreme deep learning model
Rami Al‐Ruzouq, Abdallah Shanableh, Ratiranjan Jena, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 3, pp. 101780-101780
Open Access | Times Cited: 14

Showing 14 citing articles:

Improving flood hazard susceptibility assessment by integrating hydrodynamic modeling with remote sensing and ensemble machine learning
Izhar Ahmad, Rashid Farooq, Muhammad Ashraf, et al.
Natural Hazards (2025)
Open Access | Times Cited: 1
Integrating machine learning and geospatial data analysis for comprehensive flood hazard assessment
Chiranjit Singha, Vikas Kumar Rana, Quoc Bao Pham, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 35, pp. 48497-48522
Open Access | Times Cited: 5
Metaheuristic-driven enhancement of categorical boosting algorithm for flood-prone areas mapping
Seyed Vahid Razavi-Termeh, Ali Pourzangbar, Abolghasem Sadeghi‐Niaraki, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 136, pp. 104357-104357
Closed Access
The ensemble learning combined with the pruning model reveals the spectral response mechanism of tidal flat mapping in China
Jiapeng Dong, Kai Jia, Chongyang Wang, et al.
Ecological Informatics (2025), pp. 103104-103104
Open Access
Interpretable flash flood susceptibility mapping in Yarlung Tsangpo River Basin using H2O Auto-ML
Fei He, Suxia Liu, Xingguo Mo, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Advancing flood risk assessment: Multitemporal SAR-based flood inventory generation using transfer learning and hybrid fuzzy-AHP-machine learning for flood susceptibility mapping in the Mahananda River Basin
Chiranjit Singha, Satiprasad Sahoo, Alireza Bahrami Mahtaj, et al.
Journal of Environmental Management (2025) Vol. 380, pp. 124972-124972
Open Access
Integrating Satellite Images and Machine Learning for Flood Prediction and Susceptibility Mapping for the Case of Amibara, Awash Basin, Ethiopia
Gizachew Kabite Wedajo, Tsegaye Demisis Lemma, Tesfaye Fufa Gedefa, et al.
Remote Sensing (2024) Vol. 16, Iss. 12, pp. 2163-2163
Open Access | Times Cited: 3
A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios
Kezhen Yao, Saini Yang, Zhihao Wang, et al.
Remote Sensing (2024) Vol. 16, Iss. 8, pp. 1413-1413
Open Access | Times Cited: 2
Threshold-based inventory for flood susceptibility assessment of the world’s largest river island using multi-temporal SAR data and ensemble machine learning algorithms
Pankaj Prasad, Dipjyoti Gogoi, Debashish Gogoi, et al.
Stochastic Environmental Research and Risk Assessment (2024)
Closed Access | Times Cited: 2
Monitoring the effects of climate, land cover and land use changes on multi-hazards in the Gianh River watershed, Vietnam
Huu Duy Nguyen, Dinh Kha Dang, Quoc‐Huy Nguyen, et al.
Environmental Research Letters (2024) Vol. 19, Iss. 10, pp. 104033-104033
Open Access | Times Cited: 1
A novel flood conditioning factor based on topography for flood susceptibility modeling
Jun Liu, Xueqiang Zhao, Yangbo Chen, et al.
Geoscience Frontiers (2024) Vol. 16, Iss. 1, pp. 101960-101960
Open Access | Times Cited: 1
Mapping flood risk using a workflow including deep learning and MCDM– Application to southern Iran
Hamid Gholami, Aliakbar Mohammadifar, Shahram Golzari, et al.
Urban Climate (2024) Vol. 59, pp. 102272-102272
Closed Access | Times Cited: 1
Flood susceptibility mapping using machine learning and remote sensing data in the Southern Karun Basin, Iran
Mohamad Kazemi, Fariborz Mohammadi, Mohammad Hassanzadeh Nafooti, et al.
Applied Geomatics (2024) Vol. 16, Iss. 3, pp. 731-750
Closed Access
Assessing the environmental impacts of flooding in Brazil using the flood area segmentation network deep learning model
Abdullah ŞENER, Burhan Ergen
Natural Hazards (2024)
Closed Access
Spatio-Temporal Analysis of Susceptibility Hazardous and Risk Mapping in Post-2023 Simangulampe Devastating Flood
Togi Tampubolon, Jeddah Yanti, Juniar Hutahaean, et al.
Journal of Physics Conference Series (2024) Vol. 2908, Iss. 1, pp. 012005-012005
Open Access
Page 1

Scroll to top