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:

How far spatial resolution affects the ensemble machine learning based flood susceptibility prediction in data sparse region
Tamal Kanti Saha, Swades Pal, Swapan Talukdar, et al.
Journal of Environmental Management (2021) Vol. 297, pp. 113344-113344
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Flood susceptible prediction through the use of geospatial variables and machine learning methods
Navid Mahdizadeh Gharakhanlou, Liliana Pérez
Journal of Hydrology (2023) Vol. 617, pp. 129121-129121
Closed Access | Times Cited: 51
Improving National Forest Mapping in Romania Using Machine Learning and Sentinel-2 Multispectral Imagery
Mohamed Islam Keskes, Aya Hamed Mohamed, Stelian Alexandru Borz, et al.
Remote Sensing (2025) Vol. 17, Iss. 4, pp. 715-715
Open Access | Times Cited: 2
Modelling flood susceptibility based on deep learning coupling with ensemble learning models
Yuting Li, Haoyuan Hong
Journal of Environmental Management (2022) Vol. 325, pp. 116450-116450
Closed Access | Times Cited: 48
A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction
Mohammed Sarfaraz Gani Adnan, Zakaria Shams Siam, Irfat Kabir, et al.
Journal of Environmental Management (2022) Vol. 326, pp. 116813-116813
Open Access | Times Cited: 43
Living with Floods Using State-of-the-Art and Geospatial Techniques: Flood Mitigation Alternatives, Management Measures, and Policy Recommendations
Rabin Chakrabortty, Subodh Chandra Pal, Dipankar Ruidas, et al.
Water (2023) Vol. 15, Iss. 3, pp. 558-558
Open Access | Times Cited: 29
Solving the spatial extrapolation problem in flood susceptibility using hybrid machine learning, remote sensing, and GIS
Huu Duy Nguyen, Quoc‐Huy Nguyen, Quang‐Thanh Bui
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 12, pp. 18701-18722
Closed Access | Times Cited: 9
Flood Susceptibility Mapping: Integrating Machine Learning and GIS for Enhanced Risk Assessment
Zelalem Demissie, Prashant Rimal, Wondwosen M. Seyoum, et al.
Applied Computing and Geosciences (2024) Vol. 23, pp. 100183-100183
Open Access | Times Cited: 8
Flood susceptibility mapping in the Yom River Basin, Thailand: stacking ensemble learning using multi-year flood inventory data
Gen Long, Sarintip Tantanee, Korakod Nusit, et al.
Geocarto International (2025) Vol. 40, Iss. 1
Open Access | Times Cited: 1
Spatial analysis of flood susceptibility in Coastal area of Pakistan using machine learning models and SAR imagery
Muhammad Afaq Hussain, Zhanlong Chen, Yulong Zhou, et al.
Environmental Earth Sciences (2025) Vol. 84, Iss. 5
Closed Access | Times Cited: 1
Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms
Farhana Parvin, Sk Ajim Ali, Beata Całka, et al.
Theoretical and Applied Climatology (2022) Vol. 149, Iss. 1-2, pp. 639-659
Closed Access | Times Cited: 35
Novel hybrid models to enhance the efficiency of groundwater potentiality model
Swapan Talukdar, Javed Mallick, Showmitra Kumar Sarkar, et al.
Applied Water Science (2022) Vol. 12, Iss. 4
Open Access | Times Cited: 34
Developing Robust Flood Susceptibility Model with Small Numbers of Parameters in Highly Fertile Regions of Northwest Bangladesh for Sustainable Flood and Agriculture Management
Showmitra Kumar Sarkar, Saifullah Bin Ansar, Khondaker Mohammed Mohiuddin Ekram, et al.
Sustainability (2022) Vol. 14, Iss. 7, pp. 3982-3982
Open Access | Times Cited: 29
GIS-based hybrid machine learning for flood susceptibility prediction in the Nhat Le–Kien Giang watershed, Vietnam
Huu Duy Nguyen
Earth Science Informatics (2022) Vol. 15, Iss. 4, pp. 2369-2386
Closed Access | Times Cited: 28
Framework for global sensitivity analysis in a complex 1D-2D coupled hydrodynamic model: Highlighting its importance on flood management over large data-scarce regions
Kaustav Mondal, Soumya Bandyopadhyay, Subhankar Karmakar
Journal of Environmental Management (2023) Vol. 332, pp. 117312-117312
Closed Access | Times Cited: 21
Application of hybrid model-based deep learning and swarm‐based optimizers for flood susceptibility prediction in Binh Dinh province, Vietnam
Huu Duy Nguyen, Chien Pham Van, Anh Duc
Earth Science Informatics (2023)
Closed Access | Times Cited: 18
Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR
Sackdavong Mangkhaseum, Yogesh Bhattarai, Sunil Duwal, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Groundwater potentiality mapping using ensemble machine learning algorithms for sustainable groundwater management
Showmitra Kumar Sarkar, Swapan Talukdar, Atiqur Rahman, et al.
Frontiers in Engineering and Built Environment (2021) Vol. 2, Iss. 1, pp. 43-54
Open Access | Times Cited: 35
Spatial modeling of flood hazard using machine learning and GIS in Ha Tinh province, Vietnam
Huu Duy Nguyen
Journal of Water and Climate Change (2022) Vol. 14, Iss. 1, pp. 200-222
Open Access | Times Cited: 28
Spatial Prediction of Current and Future Flood Susceptibility: Examining the Implications of Changing Climates on Flood Susceptibility Using Machine Learning Models
Navid Mahdizadeh Gharakhanlou, Liliana Pérez
Entropy (2022) Vol. 24, Iss. 11, pp. 1630-1630
Open Access | Times Cited: 26
Assessing landscape ecological vulnerability to riverbank erosion in the Middle Brahmaputra floodplains of Assam, India using machine learning algorithms
Nirsobha Bhuyan, Haroon Sajjad, Tamal Kanti Saha, et al.
CATENA (2023) Vol. 234, pp. 107581-107581
Open Access | Times Cited: 15
Improving the Accuracy of Flood Susceptibility Prediction by Combining Machine Learning Models and the Expanded Flood Inventory Data
Han Yu, Zengliang Luo, Lunche Wang, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3601-3601
Open Access | Times Cited: 14
Integration of machine learning and hydrodynamic modeling to solve the extrapolation problem in flood depth estimation
Huu Duy Nguyen, Dinh Kha Dang, Nhu Y Nguyen, et al.
Journal of Water and Climate Change (2023) Vol. 15, Iss. 1, pp. 284-304
Open Access | Times Cited: 13
Interpreting optimised data-driven solution with explainable artificial intelligence (XAI) for water quality assessment for better decision-making in pollution management
Javed Mallick, Saeed Alqadhi, Hoang Thi Hang, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 30, pp. 42948-42969
Closed Access | Times Cited: 5
Integration of fuzzy AHP and explainable AI for effective coastal risk management: A micro-scale risk analysis of tropical cyclones
Tanmoy Das, Swapan Talukdar, Shahfahad, et al.
Progress in Disaster Science (2024) Vol. 23, pp. 100357-100357
Open Access | Times Cited: 5
Flood risk assessment using machine learning, hydrodynamic modelling, and the analytic hierarchy process
Nguyen Huu Duy, Le T. Pham, Nguyen Xuan Linh, et al.
Journal of Hydroinformatics (2024) Vol. 26, Iss. 8, pp. 1852-1882
Open Access | Times Cited: 5
Page 1 - Next Page

Scroll to top