Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China-Mongolia-Russia Cross-Border Area
文献类型：期刊论文
| 作者 | Li, Yuheng1,4; Xu, Shuxing1,2; Fan, Zhaofei3; Zhang, Xiao1,4; Yang, Xiaohui1,4; Wen, Shuo1,4; Shi, Zhongjie1,4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023 |
| 卷号 | 15期号:1页码:15 |
| 关键词 | ANFIS wildfire China-Mongolia-Russia cross-border area genetic algorithm (GA) particle swarm optimization (PSO) random forest |
| DOI | 10.3390/rs15010042 |
| 通讯作者 | Shi, Zhongjie(shizj@caf.ac.cn) |
| 英文摘要 | Wildfire is essential in altering land ecosystems' structures, processes, and functions. As a critical disturbance in the China-Mongolia-Russia cross-border area, it is vital to understand the potential drivers of wildfires and predict where wildfires are more likely to occur. This study assessed factors affecting wildfire using the Random Forest (RF) model. No single factor played a decisive role in the incidence of wildfires. However, the climatic variables were most critical, dominating the occurrence of wildfires. The probability of wildfire occurrence was simulated and predicted using the Adaptive Network-based Fuzzy Inference System (ANFIS). The particle swarm optimization (PSO) model and genetic algorithm (GA) were used to optimize the ANFIS model. The hybrid ANFIS models performed better than single ANFIS for the training and validation datasets. The hybrid ANFIS models, such as PSO-ANFIS and GA-ANFIS, overcome the over-fitting problem of the single ANFIS model at the learning stage of the wildfire pattern. The high classification accuracy and good model performance suggest that PSO-ANFIS can be used to predict the probability of wildfire occurrence. The probability map illustrates that high-risk areas are mainly distributed in the northeast part of the study area, especially the grassland and forest area of Dornod Province of Mongolia, Buryatia, and Chita state of Russia, and the northeast part of Inner Mongolia, China. The findings can be used as reliable estimates of the relative likelihood of wildfire hazards for wildfire management in the region covered or vicinity. |
| WOS关键词 | FUZZY INFERENCE SYSTEM ; ARTIFICIAL-INTELLIGENCE APPROACH ; PARTICLE SWARM OPTIMIZATION ; FOREST-FIRE ; GENETIC ALGORITHM ; NEURAL-NETWORKS ; SUSCEPTIBILITY ASSESSMENT ; LOGISTIC-REGRESSION ; SPATIAL-PATTERNS ; CLIMATE-CHANGE |
| 资助项目 | National Natural Science Foundation of China[32071558] ; National Natural Science Foundation of China[41701249] ; National Natural Science Foundation of China[32061123005] ; National Natural Science Foundation of China[31670715] ; Special Project on Basic Resources of Science and Technology[2017FY101301] ; Fundamental Research Funds of CAF-Overseas Outstanding Innovative Scientists Exchange Program[CAFYBB2020GD001] ; Re-project of Surplus Funds of Research Institute of Desertification Studies, CAF[IDS2021JY-5] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000910199500001 |
| 资助机构 | National Natural Science Foundation of China ; Special Project on Basic Resources of Science and Technology ; Fundamental Research Funds of CAF-Overseas Outstanding Innovative Scientists Exchange Program ; Re-project of Surplus Funds of Research Institute of Desertification Studies, CAF |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/189026]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Shi, Zhongjie |
| 作者单位 | 1.Chinese Acad Forestry, Res Inst Desertificat Studies, Beijing 100091, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Auburn Univ, Sch Forestry & Wildlife Sci, Auburn, AL 36830 USA 4.Chinese Acad Forestry, Res Inst Ecol Conservat & Restorat, Beijing 100091, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Yuheng,Xu, Shuxing,Fan, Zhaofei,et al. Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China-Mongolia-Russia Cross-Border Area[J]. REMOTE SENSING,2023,15(1):15. |
| APA | Li, Yuheng.,Xu, Shuxing.,Fan, Zhaofei.,Zhang, Xiao.,Yang, Xiaohui.,...&Shi, Zhongjie.(2023).Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China-Mongolia-Russia Cross-Border Area.REMOTE SENSING,15(1),15. |
| MLA | Li, Yuheng,et al."Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China-Mongolia-Russia Cross-Border Area".REMOTE SENSING 15.1(2023):15. |
入库方式： OAI收割
来源：地理科学与资源研究所
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