枯黄期草原火灾精细化风险预测研究

为增强对草原火灾风险评估和应急管理能力,利用“智能网格”精细化气象要素预报数据、DGI指数、NDSI指数、DEM数据和社会经济数据,依据自然灾害风险理论,构建枯黄期草原火灾精细化风险预测模型。使用ANUSPLIN插值软件把所有因子插值为相同空间尺度数据,GIS栅格计算未来草原火灾风险预报,结果分为高风险、次高风险、中风险、次低风险、低风险区域,并统计出面积及人口等信息,开发出具有业务应用能力的草原火灾风险预测产品。随着气象行业供给侧改革深入开展,精细化气象服务水平不断提高,专业气象应用多样化发展,本研究为新型火险预测产品开发思路提供理论借鉴。

Grassland Fire Disaster: Refined Risk Prediction in EOS

The paper aims to enhance the risk assessment and emergency management of grassland fire. The author built the risk prediction model of grassland fire in EOS based on the natural disaster risking theory by using the“smart grid” meteorological element forecast data, DGI index, NDSI index, DEM data and socioeconomic data. Then, the author interpolated all the factors into the same spatial scale data by ANUSPLIN interpolation software, calculated the grassland fire disaster risk index by GIS raster tool, divided the region into high risk, sub- high risk, medium risk, sub- low risk and low risk areas, did statistics of area and population, and developed a product of grassland fire risk prediction with business application capability. With the deepening of the supply- side reform of the meteorological industry, the improvement of refined meteorological services is enhanced continuously, and the diversification of professional meteorological application is developed, this study could provide a reference for the development of new fire insurance forecasting products.