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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:

A novel optimized repeatedly random undersampling for selecting negative samples: A case study in an SVM-based forest fire susceptibility assessment
Xianzhe Tang, Takashi Machimura, Jiufeng Li, et al.
Journal of Environmental Management (2020) Vol. 271, pp. 111014-111014
Open Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Machine learning based wildfire susceptibility mapping using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey
Muzaffer Can İban, Aliihsan Şekertekin
Ecological Informatics (2022) Vol. 69, pp. 101647-101647
Closed Access | Times Cited: 112
Detection of forest fire using deep convolutional neural networks with transfer learning approach
Hatice Çatal Reis, Veysel Turk
Applied Soft Computing (2023) Vol. 143, pp. 110362-110362
Closed Access | Times Cited: 45
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: 27
A Systematic Review of Applications of Machine Learning Techniques for Wildfire Management Decision Support
Karol Bot, José G. Borges
Inventions (2022) Vol. 7, Iss. 1, pp. 15-15
Open Access | Times Cited: 69
A Small-Target Forest Fire Smoke Detection Model Based on Deformable Transformer for End-to-End Object Detection
Jingwen Huang, Jiashun Zhou, Huizhou Yang, et al.
Forests (2023) Vol. 14, Iss. 1, pp. 162-162
Open Access | Times Cited: 34
Preferred vector machine for forest fire detection
Xubing Yang, Zhichun Hua, Li Zhang, et al.
Pattern Recognition (2023) Vol. 143, pp. 109722-109722
Closed Access | Times Cited: 32
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
Forest fire risk mapping with Landsat 8 OLI images: Evaluation of the potential use of vegetation indices
Fatih Sivrikaya, Alkan Günlü, Ömer Küçük, et al.
Ecological Informatics (2024) Vol. 79, pp. 102461-102461
Open Access | Times Cited: 16
SHAP-Driven Explainable Artificial Intelligence Framework for Wildfire Susceptibility Mapping Using MODIS Active Fire Pixels: An In-Depth Interpretation of Contributing Factors in Izmir, Türkiye
Muzaffer Can İban, Oktay Aksu
Remote Sensing (2024) Vol. 16, Iss. 15, pp. 2842-2842
Open Access | Times Cited: 10
Safe Evacuation Framework with Intelligent Dynamic Exit Sign System and Demonstration in Tunnel Fire
Ho Yin Wong, Meng Wang, Xiaoning Zhang, et al.
Journal of Safety Science and Resilience (2025)
Open Access | Times Cited: 1
Assessment of forest fire vulnerability prediction in Indonesia: Seasonal variability analysis using machine learning techniques
Wulan Salle Karurung, Kangjae Lee, W. K. Lee
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 138, pp. 104435-104435
Closed Access | Times Cited: 1
A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN
Jin Pan, Xiaoming Ou, Xu Liang
Forests (2021) Vol. 12, Iss. 6, pp. 768-768
Open Access | Times Cited: 52
Application of a two-step sampling strategy based on deep neural network for landslide susceptibility mapping
Jingyu Yao, Shengwu Qin, Shuangshuang Qiao, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 4
Closed Access | Times Cited: 35
GIS-based evolution and comparisons of landslide susceptibility mapping of the East Sikkim Himalaya
Neha Gupta, Sanjit Kumar Pal, Josodhir Das
Annals of GIS (2022) Vol. 28, Iss. 3, pp. 359-384
Open Access | Times Cited: 29
Evaluation of forest fire risk based on multicriteria decision analysis techniques for Changzhou, China
Weiyi Ju, Zhixiang Xing, Jie Wu, et al.
International Journal of Disaster Risk Reduction (2023) Vol. 98, pp. 104082-104082
Closed Access | Times Cited: 19
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
Regional landslide susceptibility assessment based on improved semi-supervised clustering and deep learning
Yuhang Jiang, Wei Wang, Lifang Zou, et al.
Acta Geotechnica (2023) Vol. 19, Iss. 1, pp. 509-529
Closed Access | Times Cited: 17
A novel index to evaluate discretization methods: A case study of flood susceptibility assessment based on random forest
Xianzhe Tang, Takashi Machimura, Wei Liu, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 6, pp. 101253-101253
Open Access | Times Cited: 33
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: 14
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: 6
A novel hybrid approach to flood susceptibility assessment based on machine learning and land use change. Case study: a river watershed in Vietnam
Huu Duy Nguyen, Bui Quang-Thanh, Quoc‐Huy Nguyen, et al.
Hydrological Sciences Journal (2022) Vol. 67, Iss. 7, pp. 1065-1083
Closed Access | Times Cited: 21
Exploring effective ways to increase reliable positive samples for machine learning-based urban waterlogging susceptibility assessments
Xianzhe Tang, Zhanyu Wu, Wei Liu, et al.
Journal of Environmental Management (2023) Vol. 344, pp. 118682-118682
Closed Access | Times Cited: 12
Data adjusting strategy and optimized XGBoost algorithm for novel insider threat detection model
Xiu Kan, Yixuan Fan, Jinjie Zheng, et al.
Journal of the Franklin Institute (2023) Vol. 360, Iss. 16, pp. 11414-11443
Closed Access | Times Cited: 12
Hybrid models based on deep learning neural network and optimization algorithms for the spatial prediction of tropical forest fire susceptibility in Nghe An province, Vietnam
Huu Duy Nguyen
Geocarto International (2022) Vol. 37, Iss. 26, pp. 11281-11305
Closed Access | Times Cited: 19
Evaluating Seasonal Wildfire Susceptibility and Wildfire Threats to Local Ecosystems in the Largest Forested Area of China
Xianzhe Tang, Takashi Machimura, Jiufeng Li, et al.
Earth s Future (2022) Vol. 10, Iss. 5
Open Access | Times Cited: 18
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