Articles citing this paper
Assessing the predictive efficacy of six machine learning algorithms for the susceptibility of Indian forests to fire
Laxmi Kant Sharma
A , Rajit Gupta A * and Naureen Fatima A
+ Author Affiliations
- Author Affiliations
A Remote Sensing & GIS Lab, Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, N.H.-8, Bandarsindri-305817, Ajmer, Rajasthan, India.
* Correspondence to: 2017phdes03@curaj.ac.in
International Journal of Wildland Fire 31(8) 735-758 https://doi.org/10.1071/WF22016
Submitted: 21 February 2022 Accepted: 30 May 2022 Published: 20 July 2022
19 articles found in Crossref database.
GeoAI for Disaster Mitigation: Fire Severity Prediction Models using Sentinel-2 and ANN Regression
2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES) (2022)
Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine
Ma Tianwu,
Wang Gang,
Guo Rui,
Chen Liang, Ma Junfei
Journal of Environmental Management. 2024 359 p.120966
Predicting habitat suitability of Litsea glutinosa: a declining tree species, under the current and future climate change scenarios in India
Gupta Rajit,
Sharma Laxmi Kant,
Rajkumar Muthu,
Mohammad Naseer, Khan Mohammed Latif
Landscape and Ecological Engineering. 2023 19(2). p.211
LEF-YOLO: a lightweight method for intelligent detection of four extreme wildfires based on the YOLO framework
Li Jianwei,
Tang Huan,
Li Xingdong,
Dou Hongqiang, Li Ru
International Journal of Wildland Fire. 2023 33(1).
Integrating geospatial, remote sensing, and machine learning for climate-induced forest fire susceptibility mapping in Similipal Tiger Reserve, India
Singha Chiranjit,
Swain Kishore Chandra,
Moghimi Armin,
Foroughnia Fatemeh, Swain Sanjay Kumar
Forest Ecology and Management. 2024 555 p.121729
Spatial model of wildfire susceptibility using Machine Learning approaches on Rawa Aopa Watumohai National Park, Indonesia
Aldiansyah Septianto, Madani Ilyas
GeoScape. 2024 18(1). p.1
Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China–Mongolia–Russia Cross-Border Area
Li Yuheng,
Xu Shuxing,
Fan Zhaofei,
Zhang Xiao,
Yang Xiaohui,
Wen Shuo, Shi Zhongjie
Remote Sensing. 2022 15(1). p.42
Research Trends in Wildland Fire Prediction Amidst Climate Change: A Comprehensive Bibliometric Analysis
Bao Mingwei,
Liu Jiahao,
Ren Hong,
Liu Suting,
Ren Caixia,
Chen Chen, Liu Jianxiang
Forests. 2024 15(7). p.1197
An Integrated Grassland Fire-Danger-Assessment System for a Mountainous National Park Using Geospatial Modelling Techniques
Mofokeng Olga D.,
Adelabu Samuel A., Jackson Colbert M.
Fire. 2024 7(2). p.61
Forest fire susceptibility mapping with sensitivity and uncertainty analysis using machine learning and deep learning algorithms
Rihan Mohd,
Ali Bindajam Ahmed,
Talukdar Swapan,
Shahfahad ,
Waseem Naikoo Mohd,
Mallick Javed, Rahman Atiqur
Advances in Space Research. 2023 72(2). p.426
Spatial Prediction of Wildfire Susceptibility Using Hybrid Machine Learning Models Based on Support Vector Regression in Sydney, Australia
Nur Arip,
Kim Yong,
Lee Joon, Lee Chang-Wook
Remote Sensing. 2023 15(3). p.760
Forest Fire Detection using Deep Learning Techniques
2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) (2023)
Deep learning modeling of human activity affected wildfire risk by incorporating structural features: A case study in eastern China
He Zhonghua,
Fan Gaofeng,
Li Zhengquan,
Li Shaohong,
Gao Ling,
Li Xiang, Zeng Zhao-Cheng
Ecological Indicators. 2024 160 p.111946
An efficient, multi-scale neighbourhood index to quantify wildfire likelihood
Radford Douglas A. G.,
Maier Holger R.,
van Delden Hedwig,
Zecchin Aaron C., Jeanneau Amelie
International Journal of Wildland Fire. 2024 33(5).
Method of Wildfire Risk Assessment in Consideration of Land-Use Types: A Case Study in Central China
Yue Weiting,
Ren Chao,
Liang Yueji,
Lin Xiaoqi, Liang Jieyu
Forests. 2023 14(7). p.1393
Exploring forest fire susceptibility and management strategies in Western Himalaya: Integrating ensemble machine learning and explainable AI for accurate prediction and comprehensive analysis
Thi Hang Hoang,
Mallick Javed,
Alqadhi Saeed,
Bindajam Ahmed Ali, Abdo Hazem Ghassan
Environmental Technology & Innovation. 2024 35 p.103655
Prediction and driving factors of forest fire occurrence in Jilin Province, China
Gao Bo,
Shan Yanlong,
Liu Xiangyu,
Yin Sainan,
Yu Bo,
Cui Chenxi, Cao Lili
Journal of Forestry Research. 2024 35(1).
Spatial analysis and machine learning prediction of forest fire susceptibility: a comprehensive approach for effective management and mitigation
Mishra Manoranjan,
Guria Rajkumar,
Baraj Biswaranjan,
Nanda Ambika Prasad,
Santos Celso Augusto Guimarães,
Silva Richarde Marques da, Laksono FX Anjar Tri
Science of The Total Environment. 2024 926 p.171713
An artificial intelligence framework for predicting fire spread sustainability in semiarid shrublands
Khanmohammadi Sadegh,
Arashpour Mehrdad,
Golafshani Emadaldin Mohammadi,
Cruz Miguel G., Rajabifard Abbas
International Journal of Wildland Fire. 2023 32(4). p.636
