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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:

Forest fire susceptibility prediction using machine learning models with resampling algorithms, Northern part of Eastern Ghat Mountain range (India)
Biswajit Bera, Pravat Kumar Shit, Nairita Sengupta, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 11756-11781
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Prediction of forest fire susceptibility applying machine and deep learning algorithms for conservation priorities of forest resources
Soumik Saha, Biswajit Bera, Pravat Kumar Shit, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 29, pp. 100917-100917
Closed Access | Times Cited: 56
Spatial analysis and machine learning prediction of forest fire susceptibility: a comprehensive approach for effective management and mitigation
Manoranjan Mishra, Rajkumar Guria, Biswaranjan Baraj, et al.
The Science of The Total Environment (2024) Vol. 926, pp. 171713-171713
Closed Access | Times Cited: 22
Ensembling machine learning models to identify forest fire-susceptible zones in Northeast India
Mriganka Shekhar Sarkar, Bishal Kumar Majhi, Bhawna Pathak, et al.
Ecological Informatics (2024) Vol. 81, pp. 102598-102598
Open Access | Times Cited: 15
Environmental drivers and spatial prediction of forest fires in the Western Ghats biodiversity hotspot, India: An ensemble machine learning approach
Kanda Naveen Babu, Rahul Gour, Kurian Ayushi, et al.
Forest Ecology and Management (2023) Vol. 540, pp. 121057-121057
Open Access | Times Cited: 28
Lightning-Induced Wildfires: An Overview
Song Yang, Cangsu Xu, Xiaolu Li, et al.
Fire (2024) Vol. 7, Iss. 3, pp. 79-79
Open Access | Times Cited: 10
Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine
Tianwu Ma, Gang Wang, Rui Guo, et al.
Journal of Environmental Management (2024) Vol. 359, pp. 120966-120966
Closed Access | Times Cited: 5
Using ensemble machine learning algorithm to predict forest fire occurrence probability in Madhya Pradesh and Chhattisgarh, India
Sumedha Surbhi Singh, C. Jeganathan
Advances in Space Research (2023) Vol. 73, Iss. 6, pp. 2969-2987
Closed Access | Times Cited: 15
Predicting forest fire probability in Similipal Biosphere Reserve (India) using Sentinel-2 MSI data and machine learning
Rajkumar Guria, Manoranjan Mishra, Richarde Marques da Silva, et al.
Remote Sensing Applications Society and Environment (2024) Vol. 36, pp. 101311-101311
Closed Access | Times Cited: 5
Identification of potential dam sites for severe water crisis management in semi-arid fluoride contaminated region, India
Arijit Ghosh, Biswajit Bera
Cleaner Water (2024) Vol. 1, pp. 100011-100011
Open Access | Times Cited: 4
Enhancing forest fire susceptibility mapping in Xichang City, China using DBSCAN-based non-fire point selection integrated with deep neural network
Lingxiao Xie, Rui Zhang, Jichao Lv, et al.
Geomatics Natural Hazards and Risk (2025) Vol. 16, Iss. 1
Open Access
Assessing Wildfire Susceptibility and Spatial Patterns in Diverse Forest Ecosystems Across China: An Integrated Geospatial Analysis
Yuping Tian, Zechuan Wu, Shuai Cui, et al.
Journal of Cleaner Production (2025), pp. 144800-144800
Closed Access
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
Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility
Saeid Janizadeh, Sayed M. Bateni, Changhyun Jun, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 11
Forest fire susceptibility mapping based on precipitation-constrained cumulative dryness status information in Southeast China: A novel machine learning modeling approach
Longlong Zhao, Yuankai Ge, Shanxin Guo, et al.
Forest Ecology and Management (2024) Vol. 558, pp. 121771-121771
Closed Access | Times Cited: 3
Data driven forest fire susceptibility mapping in Bangladesh
Mafrid Haydar, Al Hossain Rafi, Halima Sadia, et al.
Ecological Indicators (2024) Vol. 166, pp. 112264-112264
Open Access | Times Cited: 3
Forest Fire Detection using Deep Learning Techniques
Ishaan Dawar, S. Gupta, Rashika Singh, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 7
Comparing Machine Learning and Time Series Approaches in Predictive Modeling of Urban Fire Incidents: A Case Study of Austin, Texas
Yihong Yuan, Andrew Grayson Wylie
ISPRS International Journal of Geo-Information (2024) Vol. 13, Iss. 5, pp. 149-149
Open Access | Times Cited: 2
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: 2
Ormancılıkta makine öğrenmesi kullanımı
Remzi Eker, Kamber Can Alkiş, Zennure Uçar, et al.
Turkish Journal of Forestry | Türkiye Ormancılık Dergisi (2023), pp. 150-177
Open Access | Times Cited: 6
Machine learning application to assess deforestation and wildfire levels in protected areas with tourism management
Felipe Roberto da Silva, Samuel Façanha Câmara, Francisco Roberto Pinto, et al.
Journal for Nature Conservation (2023) Vol. 74, pp. 126435-126435
Open Access | Times Cited: 5
Potentialities and development of groundwater resources applying machine learning models in the extended section of Manbhum-Singhbhum Plateau, India
Arijit Ghosh, Biswajit Bera
HydroResearch (2023) Vol. 7, pp. 1-14
Open Access | Times Cited: 5
Modeling forest-shrubland fire susceptibility based on machine learning and geospatial approaches in mountains of Kurdistan Region, Iraq
Nabaz R. Khwarahm
Arabian Journal of Geosciences (2022) Vol. 15, Iss. 13
Closed Access | Times Cited: 6
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
Distributed Random Forest for Predicting Forest Wildfires Based on Weather Data
Robertas Damaŝeviŝius, Rytis Maskeliūnas
Communications in computer and information science (2024), pp. 305-320
Closed Access
Addressing the Impacts of Annual Wildfires on Biodiversity and Ecosystem Services
Saurabh Chandra, Bhumika Muchan
Advances in environmental engineering and green technologies book series (2024), pp. 1-24
Closed Access
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