基于人口/GDP数据空间化的雷电灾害风险评价

Risk Assessment of Lightning Disasters Based on Spatial Population/GDP Data

为满足雷电灾害风险决策的精准化需求,突破人口、GDP等社会经济数据受行政区域的限制。本文基于多源遥感资料及统计年鉴数据,反演贵州省人口、GDP空间精细化分布情况,实现受灾对象在空间上的连续性分布;同时结合闪电定位监测资料、土壤电导率(HWSD)数据、地理信息数据,从致灾因子、孕灾环境、承灾体3个方面选取评价因子,构建雷电灾害风险评价模型,实现精细化风险评价研究。结果表明:(1)通过融入坡度分布修正人居指数、土地利用数据和夜间灯光数据反演不同产业经济数据实现的人口、GDP数据空间化分布,在总体趋势和局部特征上与贵州省实际情况相符,可为雷电灾害及其他自然灾害风险评价中承灾体的精细化分布提供参考。(2)雷电灾害风险主要受致灾因子、承灾体的影响,与雷电活动频繁程度以及社会经济发展水平有关。贵州省高风险区域主要集中在六盘水、毕节东南部、黔西南东北部、安顺南部及北部、贵阳东南部,黔南西南及东北部、遵义西北部、铜仁中部及东南部等区域。

In order to meet the precise needs of the lightning disaster risk decision-making and lift the limits of the administrative region for the social and economic data such as population and GDP,the refined spatial distribution of population and GDP in Guizhou Province is analyzed,which is based on the multisource remote sensing data and the statistical yearbooks,so as to achieve the continuous spatial distribution of the victims.The lightning disaster risk assessment model is constructed,and the evaluation factors are selected from the three aspects of disaster factors,disaster environment,and disaster bearing body,combining with lightning location monitoring data,HWSD（Harmonized World Soil Database）data and geographic information data.The results show：（1）The spatial distribution of population and GDP data is gained by modifying the habitat index by integrating slope distribution and retrieving various industrial economic data by integrating land use data and DMSP/OLS night light data.The overall trend and local characteristics are in agreement with the actual situation in Guizhou Province,which can provide a reference for the fine distribution of hazard bodies in the risk assessment of lightning disasters and other natural disasters.（2）The risk of lightning disasters is mainly affected by hazard factors and hazard bearing bodies,which is related to the frequency of lightning activities and the level of social and economic development.The high risk areas in Guizhou Province are mainly in Liupanshui,southeastern Bijie,northeastern Qianxinan,southern and northern Anshun,southeastern Guiyang,southwestern and northeastern Qiannan,northwestern Zunyi,central and southeastern Tongren.