The regulation of the National Significant Seismic Monitoring and Protection Regions(NSSMPR for short) is defined by the Law of the Peoples Republic of China on Protecting Against and Mitigating Earthquake Disasters.T...The regulation of the National Significant Seismic Monitoring and Protection Regions(NSSMPR for short) is defined by the Law of the Peoples Republic of China on Protecting Against and Mitigating Earthquake Disasters.The first stage of implementation of the regulation of NSSMPR in the Chinese mainland was finished from 1996 to 2005.The second stage is being carried on from 2006 to 2020.With the support of the National Social Science Foundation,this paper follows up and evaluates the implementation of the regulation of NSSMPR from 1996 to 2012 in the Chinese mainland.Based on analysis of earthquake examples and investigation data,we find that the effect of disaster mitigation is good,and on this basis,some suggestions are proposed to improve the regulation of NSSMPR.展开更多
The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new d...The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies.However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that:(1)Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors,including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts;(2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster;and(3)Descriptions of rainfall intensity by females are closer to the meteorological observation data.展开更多
基金sponsored by the National Social Science Foundation of China"Research on the Status,Efficiencies and the Policy on the National Significant Seismic Monitoring and Protection Regions"(11&ZD054)
文摘The regulation of the National Significant Seismic Monitoring and Protection Regions(NSSMPR for short) is defined by the Law of the Peoples Republic of China on Protecting Against and Mitigating Earthquake Disasters.The first stage of implementation of the regulation of NSSMPR in the Chinese mainland was finished from 1996 to 2005.The second stage is being carried on from 2006 to 2020.With the support of the National Social Science Foundation,this paper follows up and evaluates the implementation of the regulation of NSSMPR from 1996 to 2012 in the Chinese mainland.Based on analysis of earthquake examples and investigation data,we find that the effect of disaster mitigation is good,and on this basis,some suggestions are proposed to improve the regulation of NSSMPR.
基金supported by the National Key Research and Development Program of China(No.2018YFC1508903)the Science Technology Department of Zhejiang Province(No.2022C03107)the International Center for Collaborative Research on Disaster Risk Reduction。
文摘The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies.However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that:(1)Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors,including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts;(2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster;and(3)Descriptions of rainfall intensity by females are closer to the meteorological observation data.
