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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:

Wildfire Susceptibility Mapping Using Five Boosting Machine Learning Algorithms: The Case Study of the Mediterranean Region of Turkey
Sohaib K. M. Abujayyab, Moustafa Moufid Kassem, Ashfaq Ahmad Khan, et al.
Advances in Civil Engineering (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 23

Showing 23 citing articles:

A novel flood risk management approach based on future climate and land use change scenarios
Huu Duy Nguyen, Quoc‐Huy Nguyen, Dinh Kha Dang, et al.
The Science of The Total Environment (2024) Vol. 921, pp. 171204-171204
Closed Access | Times Cited: 26
Forest fire probability zonation using dNBR and machine learning models: a case study at the Similipal Biosphere Reserve (SBR), Odisha, India
Rajkumar Guria, Manoranjan Mishra, Samiksha Mohanta, et al.
Environmental Science and Pollution Research (2025)
Closed Access | Times Cited: 2
Assessment of Wildfire Susceptibility and Wildfire Threats to Ecological Environment and Urban Development Based on GIS and Multi-Source Data: A Case Study of Guilin, China
Weiting Yue, Chao Ren, Yueji Liang, et al.
Remote Sensing (2023) Vol. 15, Iss. 10, pp. 2659-2659
Open Access | Times Cited: 27
Comparison of diverse machine learning algorithms for forest fire susceptibility mapping in Antalya, Türkiye
Hazan Alkan Akıncı, Halil Akıncı, Mustafa Zeybek
Advances in Space Research (2024) Vol. 74, Iss. 2, pp. 647-667
Closed Access | Times Cited: 10
Integrated Spatial Analysis of Forest Fire Susceptibility in the Indian Western Himalayas (IWH) Using Remote Sensing and GIS-Based Fuzzy AHP Approach
Pragya, Manish Kumar, Akash Tiwari, et al.
Remote Sensing (2023) Vol. 15, Iss. 19, pp. 4701-4701
Open Access | Times Cited: 21
Improving the prediction of wildfire susceptibility on Hawaiʻi Island, Hawaiʻi, using explainable hybrid machine learning models
Trang Thi Kieu Tran, Saeid Janizadeh, Sayed M. Bateni, et al.
Journal of Environmental Management (2023) Vol. 351, pp. 119724-119724
Closed Access | Times Cited: 18
Wildfire susceptibility mapping by incorporating damage proxy maps, differenced normalized burn Ratio, and deep learning algorithms based on sentinel-1/2 data: a case study on Maui Island, Hawaii
Suci Ramayanti, Bong-Chan Kim, Sungjae Park, et al.
GIScience & Remote Sensing (2024) Vol. 61, Iss. 1
Open Access | Times Cited: 8
Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii
Saeid Janizadeh, Trang Thi Kieu Tran, Sayed M. Bateni, et al.
Expert Systems with Applications (2024) Vol. 258, pp. 124963-124963
Closed Access | Times Cited: 4
Machine Learning-Based Wildfire Susceptibility Mapping: A Gis-Integrated Predictive Framework
Yehya Bouzeraa, Nardjes Bouchemal, Salim Djaaboub
(2025)
Closed Access
Integrating ensemble machine learning and explainable AI for enhanced forest fire susceptibility analysis and risk assessment in Türkiye’s Mediterranean region
Hasan Tonbul
Earth Science Informatics (2024)
Closed Access | Times Cited: 3
Method of Wildfire Risk Assessment in Consideration of Land-Use Types: A Case Study in Central China
Weiting Yue, Chao Ren, Yueji Liang, et al.
Forests (2023) Vol. 14, Iss. 7, pp. 1393-1393
Open Access | Times Cited: 8
Integrating object-based and pixel-based segmentation for building footprint extraction from satellite images
Sohaib K. M. Abujayyab, Rania Almajalid, Raniyah Wazirali, et al.
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 10, pp. 101802-101802
Open Access | Times Cited: 8
Developing a hybrid deep learning model with explainable artificial intelligence (XAI) for enhanced landslide susceptibility modeling and management
Saeed Alqadhi, Javed Mallick, Meshel Q. Alkahtani, et al.
Natural Hazards (2023) Vol. 120, Iss. 4, pp. 3719-3747
Closed Access | Times Cited: 8
Visibility Evaluation and Suitability Analysis of Fire Lookout Towers in Mediterranean Region, Southwest Anatolia/Türkiye
Ufuk Coşgun, Mücahit COŞKUN, Ferhat TOPRAK, et al.
Fire (2023) Vol. 6, Iss. 8, pp. 305-305
Open Access | Times Cited: 6
A framework for flood depth using hydrodynamic modeling and machine learning in the coastal province of Vietnam
Huu Duy Nguyen, Dinh Kha Dang, Y. Nhu Nguyen, et al.
VIETNAM JOURNAL OF EARTH SCIENCES (2023)
Closed Access | Times Cited: 5
Modeling and Mapping of Flood Susceptibility at Que Son District, Quang Nam Province, Vietnam using CatBoost
Tran Van Phong, Duc Dam Nguyen, Binh Thai Pham
IOP Conference Series Materials Science and Engineering (2023) Vol. 1289, Iss. 1, pp. 012019-012019
Open Access | Times Cited: 4
Machine Learning for Modeling Vegetation Restoration of Forests Using Satellite Images
Saeideh Karimi, Mehdi Heidari, Amir Mosavi
(2024), pp. 000531-000538
Closed Access | Times Cited: 1
Predicting daily firefighting personnel deployment trends in the western United States
Kevin A. Young, Erin J. Belval, Karin L. Riley, et al.
Journal of Environmental Management (2024) Vol. 370, pp. 122705-122705
Closed Access | Times Cited: 1
Wildfire Risk Assessment Considering Seasonal Differences: A Case Study of Nanning, China
Weiting Yue, Chao Ren, Yueji Liang, et al.
Forests (2023) Vol. 14, Iss. 8, pp. 1616-1616
Open Access | Times Cited: 3
Suitable area identification for mulberry plantation using query-based prescriptive analytics and microclimatic parameters
M. Navamuniyammal, R. Vidhya, Muttucumaru Sivakumar, et al.
International Journal of Agricultural Sustainability (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 1
Four hybrid machine learning algorithms to predict forest fire susceptibility
Huayu Zhang, Xiao Yu Huang, Yi Ouyang, et al.
(2024), pp. 56-56
Closed Access
Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Kullanılarak Yangın Hasarının ve Yangına Duyarlı Alanların Belirlenmesi: Aydıncık (Mersin) İlçesi Örneği, Türkiye
Fatih Ocak, Feride Cesur, Amira Ismail, et al.
Doğal Afetler ve Çevre Dergisi (2024) Vol. 10, Iss. 2, pp. 344-364
Open Access
Forest Fire Susceptibility Zonation using dNBR and Machine Learning models: A case study at the Similipal Biosphere Reserve, Odisha, India
Rajkumar Guria, Manoranjan Mishra, Samiksha Mohanta, et al.
(2024)
Closed Access
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