Climate Change Data Portal
| DOI | 10.3390/f15010170 |
| Wildfire Susceptibility Mapping in Baikal Natural Territory Using Random Forest | |
| 发表日期 | 2024 |
| EISSN | 1999-4907 |
| 起始页码 | 15 |
| 结束页码 | 1 |
| 卷号 | 15期号:1 |
| 英文摘要 | Wildfires are a significant problem in Irkutsk Oblast. They are caused by climate change, thunderstorms, and human factors. In this study, we use the Random Forest machine learning method to map the wildfire susceptibility of Irkutsk Oblast based on data from remote sensing, meteorology, government forestry authorities, and emergency situations. The main contributions of the paper are the following: an improved domain model that describes information about weather conditions, vegetation type, and infrastructure of the region in the context of the possible risk of wildfires; a database of wildfires in Irkutsk Oblast from 2017 to 2020; the results of an analysis of factors that cause wildfires and risk assessment based on Random Forest in the form of fire hazard mapping. In this paper, we collected and visualized data on wildfires and factors influencing their occurrence: meteorological, topographic, characteristics of vegetation, and human activity (social factors). Data sets describing two classes, '' fire '' and '' no fire '', were generated. We introduced a classification according to which the probability of a wildfire in each specific cell of the territory can be determined and a wildfire risk map built. The use of the Random Forest method allowed us to achieve the following risk assessment accuracy indicators: accuracy-0.89, F1-score-0.88, and AUC-0.96. The comparison of the results with earlier ones obtained using case-based reasoning revealed that the application of the case-based approach can be considered the initial stage for deeper investigations with the use of Random Forest for more accurate forecasting. |
| 英文关键词 | hazard of wildfires; wildfire; forest quarters; wildfire susceptibility mapping; random forest; data analysis; Baikal natural territory; Irkutsk oblast |
| 语种 | 英语 |
| WOS研究方向 | Forestry |
| WOS类目 | Forestry |
| WOS记录号 | WOS:001149281700001 |
| 来源期刊 | FORESTS
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/300385 |
| 作者单位 | Irkutsk Science Centre of the Russian Academy of Sciences; Russian Academy of Sciences; Matrosov Institute for System Dynamics & Control Theory SB RAS |
| 推荐引用方式 GB/T 7714 | . Wildfire Susceptibility Mapping in Baikal Natural Territory Using Random Forest[J],2024,15(1). |
| APA | (2024).Wildfire Susceptibility Mapping in Baikal Natural Territory Using Random Forest.FORESTS,15(1). |
| MLA | "Wildfire Susceptibility Mapping in Baikal Natural Territory Using Random Forest".FORESTS 15.1(2024). |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
