Linking the Random Forests Model and GIS to Assess Geo-Hazards Risk: A Case Study in Shifang County, China
文献类型：期刊论文
| 作者 | Huang Pei1,2; Peng Li1,2 ; Pan Hongyi1
|
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2020 |
| 卷号 | 8页码:28033-28042 |
| 关键词 | Geo-hazards random forests model risk assessment Shifang county support vector machine model. |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2020.2972005 |
| 产权排序 | 3 |
| 通讯作者 | Peng, Li(pengli@imde.ac.cn) |
| 文献子类 | Article |
| 英文摘要 | This study proposes an objective and accurate geo-hazards risk assessment method to address the challenge of increasingly severe hazards around the world. Previous studies mostly began from the perspectives of hazard and vulnerability, ignoring the role of survey data at disaster sites during risk assessments. The random forests (RF) model was applied in this study. Combined with detailed data from hazard sites, a geo-hazards risk assessment model was constructed, with the two dimensions of disaster hazard and vulnerability, was constructed. We analyzed the spatial pattern characteristics and the internal patterns of disaster risk and discussed the risk controlling factors and their contributions. The results showed the following. (1) The RF model, when combined with hazard, vulnerability conditions, and detailed data from disaster sites, can be used to zone and verify regional geo-hazards risks, providing a method for point-to-surface disaster risk mapping. (2) The RF-based geo-hazards risk assessment results were relatively consistent with the evaluation results from the support vector machine (SVM) model, but the accuracy and stability of the RF model were higher. (3) This method can be used to avoid the subjectivity in determining the weights and threshold values for indexes and can calculate the contribution of each index to geo-hazards risks. |
| WOS关键词 | LANDSLIDE HAZARD ; GEOLOGICAL DISASTERS ; CLASSIFICATION ; PREDICTION ; MANAGEMENT ; REGION ; TREE |
| 资助项目 | Science and Technology Service Network Initiative[KFJ-STS-QYZD-060] ; Sichuan Philosophy and Social Science 397 Planning Project[SC18B095] ; Sichuan Normal University[CSY201903-28] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000525472700020 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Science and Technology Service Network Initiative ; Sichuan Philosophy and Social Science 397 Planning Project ; Sichuan Normal University |
| 源URL | [http://ir.imde.ac.cn/handle/131551/34264]  |
| 专题 | 成都山地灾害与环境研究所_山区发展研究中心 |
| 通讯作者 | Peng Li |
| 作者单位 | 1.Sichuan Normal Univ, Coll Geog & Resources, Chengdu 610101, Peoples R China; 2.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang Pei,Peng Li,Pan Hongyi. Linking the Random Forests Model and GIS to Assess Geo-Hazards Risk: A Case Study in Shifang County, China[J]. IEEE ACCESS,2020,8:28033-28042. |
| APA | Huang Pei,Peng Li,&Pan Hongyi.(2020).Linking the Random Forests Model and GIS to Assess Geo-Hazards Risk: A Case Study in Shifang County, China.IEEE ACCESS,8,28033-28042. |
| MLA | Huang Pei,et al."Linking the Random Forests Model and GIS to Assess Geo-Hazards Risk: A Case Study in Shifang County, China".IEEE ACCESS 8(2020):28033-28042. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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