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:

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

Showing 1-25 of 56 citing articles:

Recurrent forest fires, emission of atmospheric pollutants (GHGs) and degradation of tropical dry deciduous forest ecosystem services
Soumik Saha, Biswajit Bera, Pravat Kumar Shit, et al.
Total Environment Research Themes (2023) Vol. 7, pp. 100057-100057
Open Access | Times Cited: 43
Integrating geospatial, remote sensing, and machine learning for climate-induced forest fire susceptibility mapping in Similipal Tiger Reserve, India
Chiranjit Singha, Kishore Chandra Swain, Armin Moghimi, et al.
Forest Ecology and Management (2024) Vol. 555, pp. 121729-121729
Open Access | Times Cited: 23
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
Forest-Fire-Risk Prediction Based on Random Forest and Backpropagation Neural Network of Heihe Area in Heilongjiang Province, China
Chao Gao, Honglei Lin, Haiqing Hu
Forests (2023) Vol. 14, Iss. 2, pp. 170-170
Open Access | Times Cited: 24
Classification Assessment Tool: A program to measure the uncertainty of classification models in terms of class-level metrics
Szilárd Szabó, I. J. Holb, Vanda Éva Molnár, et al.
Applied Soft Computing (2024) Vol. 155, pp. 111468-111468
Open Access | Times Cited: 10
Machine Learning for Predicting Forest Fire Occurrence in Changsha: An Innovative Investigation into the Introduction of a Forest Fuel Factor
Xin Wu, Gui Zhang, Yang Zhi-gao, et al.
Remote Sensing (2023) Vol. 15, Iss. 17, pp. 4208-4208
Open Access | Times Cited: 19
A Forest Fire Recognition Method Based on Modified Deep CNN Model
Shaoxiong Zheng, Xiangjun Zou, Peng Gao, et al.
Forests (2024) Vol. 15, Iss. 1, pp. 111-111
Open Access | Times Cited: 7
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: 7
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
Forest fire vulnerability in Nepal's Chure region: Investigating the influencing factors using generalized linear model
Khagendra Prasad Joshi, Gunjan Adhikari, Divya Bhattarai, et al.
Heliyon (2024) Vol. 10, Iss. 7, pp. e28525-e28525
Open Access | Times Cited: 5
Identifying Influential Spatial Drivers of Forest Fires through Geographically and Temporally Weighted Regression Coupled with a Continuous Invasive Weed Optimization Algorithm
Parham Pahlavani, Amin Raei, Behnaz Bigdeli, et al.
Fire (2024) Vol. 7, Iss. 1, pp. 33-33
Open Access | Times Cited: 4
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
Fire Risk Mapping Using Machine Learning Method and Remote Sensing in the Mediterranean Region
Fatih Sivrikaya, Döndü Demirel
Advances in Space Research (2025)
Closed Access
Modeling of Forest Fire Risk Areas of Amazonas Department, Peru: Comparative Evaluation of Three Machine Learning Methods
Alex J. Vergara, Sivmny V. Valqui-Reina, Dennis Cieza-Tarrillo, et al.
Forests (2025) Vol. 16, Iss. 2, pp. 273-273
Open Access
A Synergistic Approach Using Machine Learning and Deep Learning for Forest Fire Susceptibility in Himalayan Forests
Parthiva Shome, A. Jaya Prakash, Mukunda Dev Behera, et al.
Journal of the Indian Society of Remote Sensing (2025)
Closed Access
Remote sensing scene classification with relation-aware dynamic graph neural networks
Qionghao Huang, Fan Jiang, Changqin Huang
Engineering Applications of Artificial Intelligence (2025) Vol. 150, pp. 110513-110513
Closed Access
Harnessing Artificial Intelligence, Machine Learning and Deep Learning for Sustainable Forestry Management and Conservation: Transformative Potential and Future Perspectives
T. J. Wang, Y. Zuo, Teja Manda, et al.
Plants (2025) Vol. 14, Iss. 7, pp. 998-998
Open 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
Investigating Landfill Leachate and Groundwater Quality Prediction Using a Robust Integrated Artificial Intelligence Model: Grey Wolf Metaheuristic Optimization Algorithm and Extreme Learning Machine
Meysam Alizamir, Zahra Kazemi, Zohre Kazemi, et al.
Water (2023) Vol. 15, Iss. 13, pp. 2453-2453
Open Access | Times Cited: 11
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: 11
Predicting the RUL of Li-Ion Batteries in UAVs Using Machine Learning Techniques
Dragoș Andrioaia, Vasile Gheorghiță Găitan, George Culea, et al.
Computers (2024) Vol. 13, Iss. 3, pp. 64-64
Open Access | Times Cited: 3
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
Geospatial forest fire risk assessment and zoning by integrating MaxEnt in Gorkha District, Nepal
Gayatri Paudel, Kabita Pandey, Puspa Lamsal, et al.
Heliyon (2024) Vol. 10, Iss. 11, pp. e31305-e31305
Open Access | Times Cited: 3
Deep learning approaches for estimating forest vegetation cover and exploring influential ecosystem factors
Hendaf N. Habeeb, Yaseen T. Mustafa
Earth Science Informatics (2024)
Closed Access | Times Cited: 3
Page 1 - Next Page

Scroll to top