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基于ArcGIS点抽稀的河南省灾情速报骨干网建设
引用本文:王斐斐,韩贞辉,钟敏,苏莉华,谢恒义.基于ArcGIS点抽稀的河南省灾情速报骨干网建设[J].华南地震,2019,39(1):59-65.
作者姓名:王斐斐  韩贞辉  钟敏  苏莉华  谢恒义
作者单位:河南省地震局,郑州,450016;河南省地震局,郑州,450016;河南省地震局,郑州,450016;河南省地震局,郑州,450016;河南省地震局,郑州,450016
摘    要:河南省地震局灾情速报员队伍经过多年建设,目前在册灾情速报员多达3万余人,数量位居全国前列,但也存在灾情速报员数量过多、管理不易等问题,为确保河南省地震灾情速报员队伍发挥作用,以河南省现有行政村点为基础,根据空间均匀分布的原则,以5×6 km为格网单元,对ArcGIS的三种不同的点抽稀方法进行对比分析,最终选择SubsetFeatures和SubPoints相结合的方法,提取出6000多个行政村点,依此为依据报送人员名单,以保证每个乡(镇、街道办事处)有3~5名灾情速报人员组成河南省骨干灾情速报员队伍,从而强化灾情速报工作管理。

关 键 词:点抽稀  数据提取  灾情速报管理

Construction of Backbone Network for Disaster Quick Reporting in Henan Province Based on ArcGIS Point Thinning
WANG Feifei,HAN Zhenhui,ZHONG Min,SU Lihua,XIE Hengyi.Construction of Backbone Network for Disaster Quick Reporting in Henan Province Based on ArcGIS Point Thinning[J].South China Journal of Seismology,2019,39(1):59-65.
Authors:WANG Feifei  HAN Zhenhui  ZHONG Min  SU Lihua  XIE Hengyi
Institution:(Henan Earthquake Agency,Zhengzhou 450016,China)
Abstract:After many years of construction,the disaster quick reporting team of Henan Earthquake Agency has more than 30 000 people,and the number is among the highest in the country. However, there are also problems such as excessive number of disaster quick reporters and poor management. To ensure that the earthquake disaster quick reporting team in Henan Province play a role,this paper takes the existing administrative village in Henan Province as a point according to the principle of uniform spatial distribution, three different point extraction methods of ArcGIS are compared and analyzed with 5×6 km as the grid unit. Finally,the method of combing Subset features with SubPoints was selected to extract more than 6 000 administrative village points, and based on this, submit a list of personnel to ensure that each township (town, street office) has 3 to 5 disasters reporting staff. Thus the disaster quick reporting backbone network of Henan Province has constructed,so as to strengthen the management of disaster quick reporting work.
Keywords:Point Thinning  Data extraction  Disaster quick report management
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