|
|||||
|
|
A time-dependent stochastic grassland fire ignition probability model for Hulun Buir Grassland of China |
|
| Authors: | Zhixing Guo Weihua Fang Jun Tan Xianwu Shi |
| Institution: | 1. Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing, 100875, China 2. National Marine Hazard Mitigation Service, State Oceanic Administration, Beijing, 100194, China 3. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing, 100875, China 4. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing, 100875, China |
| Abstract: | Grassland fire is one of the most important disturbance factors in the natural ecosystems. This paper focuses on the spatial distribution of long-term grassland fire patterns in the Hulun Buir Grassland located in the northeast of Inner Mongolia Autonomous Region in China. The density or ratio of ignition can reflect the relationship between grassland fire and different ignition factors. Based on the relationship between the density or ratio of ignition in different range of each ignition factor and grassland fire events, an ignition probability model was developed by using binary logistic regression function and its overall accuracy averaged up to 81.7%. Meanwhile it was found that daily relative humidity, daily temperature, elevation, vegetation type, distance to county-level road, distance to town are more important determinants of spatial distribution of fire ignitions. Using Monte Carlo method, we developed a time-dependent stochastic ignition probability model based on the distribution of inter-annual daily relative humidity and daily temperature. Through this model, it is possible to estimate the spatial patterns of ignition probability for grassland fire, which will be helpful to the quantitative evaluation of grassland fire risk and its management in the future. |
| Keywords: | grassland fire binary logistic regression GIS spatial analysis ignition probability Monte Carlo method |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ | |