Forest fire risk mapping based on spatial logistic model of northeastern China forest zone
文献类型：会议论文
| 作者 | Deng Ou ; Su Guofeng ; Huang Quanyi ; Li Yiqiu |
| 出版日期 | 2013 |
| 会议名称 | 2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013, November 8, 2013 - November 10, 2013 |
| 会议地点 | Wuhan, China |
| 关键词 | Fires Budget control Deforestation Ecosystems Human resource management Mapping Mathematical models Natural resources management Regression analysis Resource allocation Risk perception |
| 页码 | 181-192 |
| 英文摘要 | Forest fire risk and danger mapping is about forest fire potential estimating. Spatial differentiation of forest fire risk and danger is obvious in the Northeastern China Forest Zone, and it is of crucial importance in setting up management objectives in this region. Based on RS and GIS technology and spatial logistic regression analysis, the relations between the burn scar and its influencing factors were evaluated using Wald step forward logistic regression. Using logistic regression model, forest fire risk probability of each pixel was calculated and five-class forest fire risk and danger zones were identified. The result shows that spatial differentiation of forest fire risk and danger is obvious in the region. Different forest fire management can be applied in different fire risk zone. To eradicate forest fire from the beginning, budgets, personnel, technology, equipment, early warning and monitoring systems need to be adjusted in fire management systems. Springer-Verlag Berlin Heidelberg 2013. |
| 收录类别 | EI |
| 会议录出版者 | Springer Verlag |
| 语种 | 英语 |
| ISSN号 | 18650929 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/31068]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Deng Ou,Su Guofeng,Huang Quanyi,et al. Forest fire risk mapping based on spatial logistic model of northeastern China forest zone[C]. 见:2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013, November 8, 2013 - November 10, 2013. Wuhan, China. |
入库方式： OAI收割
来源：地理科学与资源研究所
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