基于千米格网的地震应急灾情预评估数据开发

doi:10.3969/j.issn.0253-4967.2016.03.020

地震地质 ›› 2016, Vol. 38 ›› Issue (3): 760-772.DOI: 10.3969/j.issn.0253-4967.2016.03.020

基于千米格网的地震应急灾情预评估数据开发

徐敬海¹, 安基文², 聂高众²

1 南京工业大学测绘学院, 空间信息综合减灾研究所, 南京 211816;
2 中国地震局地质研究所, 北京 100029

收稿日期:2015-03-23 修回日期:2016-07-07 出版日期:2016-09-20 发布日期:2016-10-15
作者简介:徐敬海,男,1977年生,2006年于武汉大学获摄影测量与遥感专业博士学位,副教授,主要从事地震应急、空间技术减灾集成与工程应用研究,电话:025-58139462,E-mail:xu_jing_hai@163.com。
基金资助:
中国地震局地质研究所基本科研业务专项（IGCEA1506）、国家科技支撑计划项目（2012BAK15B06）、空间信息智能感知与服务深圳市重点实验室（深圳大学）开放基金资助项目（201404）、江苏省测绘地理信息科研项目（JSCHKY201506）与中国地震局工程力学研究所基本科业务费专项（2016QJGJ16）共同资助

DEVELOPMENT OF EARTHQUAKE EMERGENCY DISASTER INFORMATION PRE-EVALUATION DATA BASED ON KM GRID

XU Jing-hai¹, AN Ji-wen², NIE Gao-zhong²

1 Institute of Spatial Information and Comprehensive Disaster Reduction, College of Geomatics Engineering, Nanjing University of Technology, Nanjing 211816, China;
2 Institute of Geology, China Earthquake Administration, Beijing 100029, China

Received:2015-03-23 Revised:2016-07-07 Online:2016-09-20 Published:2016-10-15

摘要/Abstract

摘要：

震后地震应急灾情的准确、快速评估（盲估）是有效地震应急决策的关键之一。为提高应急灾情评估的速度与准确性，文中提出开发基于千米格网技术的地震应急灾情预评估数据。阐述了预评估数据计算模型，包括承灾体数据、灾情计算用致灾因子和计算公式。介绍了千米格网地震应急灾情预评估数据计算的算法，该算法通过对计算参数的空间化和地图代数的应用实现。最后论述了预评估数据在地震应急灾情评估与应急救援中的应用，并以近期中国大陆发生的2次实际破坏性地震为实验案例，展示和检验了其应用。实验结果表明，千米格网地震应急灾情预评估数据能较好地提升灾情评估速度和准确度，还能精细地展示灾情的空间分布，为地震应急指挥和救援提供参考。

关键词: 地震应急, 千米格网, 地震应急灾情, 灾情评估, 空间化

Abstract:

After an earthquake, earthquake emergency response and rescue is one of the effective ways to reduce casualties from the earthquake. Earthquake emergency disaster information is one of crucial factors to effectively guide the rescue work. However, there is a "black box effect" on the emergency disaster information acquisition after an earthquake, which means real-time earthquake disaster information is insufficient. Hazard estimates are usually used as a substitute for the real-time disaster information in the "black box" period. However, it is subject to the accuracy and speed of the estimation.
The development of the km grid technology provides good prospect to solve this problem. The paper suggests to develop earthquake disaster information pre-estimation data with the support of the km grid technology. The definition and source of the pre-estimation data are introduced and its possibility in improving the estimation speed and accuracy are analyzed theoretically.
Then, we elaborate the calculation model of the pre-estimation data. The framework of the model includes disaster-bearing body data, disaster-causing factors used in calculation and calculation formula. The disaster-bearing body data in km grid format are introduced, including population data in km grid format and building data in km grid format. Then the four elements of the earthquake(earthquake occurrence time, earthquake location, earthquake magnitude and focal depth)are selected as disaster-causing factors for calculation. Map algebra method is used to realize the calculation model in which calculation parameters are associated with base map in the km grid format. So the pre-estimation data are developed by python and ArcGIS, which includes building damage dataset(100 layers), death toll dataset(10 layers)and direct economic loss dataset(5 layers).
Finally, the pre-estimation data based method for earthquake emergency disaster information estimation is presented. With the support of this method, two real earthquake cases are used to validate the effect of the pre-estimation data. The validation results show the pre-estimation data can not only significantly improve the speed of the estimation but also greatly improve the accuracy of the estimation. Another good result is found in the validation process that with the support of the pre-estimation data, the estimated result can display the spatial distribution of the disaster information, which will effectively aid earthquake emergency response and rescues.

Key words: earthquake emergency, kilometer (km) grid, earthquake emergency disaster information, disaster information estimation, spatialization

中图分类号:

P315.9

徐敬海, 安基文, 聂高众. 基于千米格网的地震应急灾情预评估数据开发[J]. 地震地质, 2016, 38(3): 760-772.

XU Jing-hai, AN Ji-wen, NIE Gao-zhong. DEVELOPMENT OF EARTHQUAKE EMERGENCY DISASTER INFORMATION PRE-EVALUATION DATA BASED ON KM GRID[J]. SEISMOLOGY AND GEOLOGY, 2016, 38(3): 760-772.

参考文献

陈颙, 刘杰. 1999. 地震危险性分析和震害预测［M］. 北京:地震出版社.
CHEN Yong, LIU Jie. 1999. Earthquake Risk Analysis and Hazard Prediction［M］. Seismological Press, Beijing(in Chinese).
高庆华. 2011. 论地震风险［M］. 北京:气象出版社.
GAO Qing-hua. 2011. On Earthquake Disaster Risk［M］. Meteorological Press, Beijing(in Chinese).
韩贞辉, 李志强, 陈振拓, 等. 2013. 人口、房屋数据空间化及其在震灾快速评估中的应用:以彝良地震为例［J］. 地震地质, 35(4):894-906. doi:10.3969/j.issn.0253-4967.2013.04.018.
HAN Zhen-hui, LI Zhi-qiang, CHEN Zhen-tuo, et al. 2013. Population, housing statistics data spatialization research in the application of rapid earthquake loss assessment-A case of Yiliang earthquake［J］. Seismology and Geology, 35(4):894-906(in Chinese).
江东. 2007. 人文要素空间化研究进展［J］. 甘肃科学学报, 19(2):91-94.
JIANG Dong. 2007. Study on the progress of spatialization of anthrop factors［J］. Journal of Gansu Sciences, 19(2):91-94(in Chinese).
刘红辉, 江东, 杨小唤, 等. 2005. 基于遥感的全国GDP 1km格网的空间化表达［J］. 地球信息科学, 7(2):120-123.
LIU Hong-hui, JIANG Dong, YANG Xiao-huan, et al. 2005. Spatialization approach to 1km grid GDP supported by remote sensing［J］. Geo-information Science, 7(2):120-123(in Chinese).
马玉宏, 谢礼立. 2000. 地震人员伤亡估算方法研究［J］. 地震工程与工程振动, 20(4):140-147.
MA Yu-hong, XIE Li-li. 2000. Methodologies for assessment of earthquake causality［J］. Earthquake Engineering and Engineering Vibration, 20(4):140-147(in Chinese).
苗崇刚, 聂高众. 2004. 地震应急指挥模式探讨［J］. 自然灾害学报, 13(5):48-54.
MIAO Chong-gang, NIE Gao-zhong. 2004. Exploration on mode of earthquake emergency command［J］. Journal of Natural Disasters, 13(5):48-54(in Chinese).
聂高众, 安基文, 邓砚. 2012. 地震应急灾情服务进展［J］. 地震地质, 34(4):782-791. doi:10.3969/j.issn.0253-4967.2012.04.020.
NIE Gao-zhong, AN Ji-wen, DENG Yan. 2012. Advances in earthquake emergency disaster service［J］. Seismology and Geology, 34(4):782-791(in Chinese).
聂高众, 陈建英, 李志强, 等. 2002. 地震应急基础数据库建设［J］. 地震, 22(3):105-112.
NIE Gao-zhong, CHEN Jian-ying, LI Zhi-qiang, et al. 2002. The construction of basic database for earthquake emergency response［J］. Earthquake, 22(3):105-112(in Chinese).
王晓青, 丁香, 王龙, 等. 2009. 四川汶川8 级大地震灾害损失快速评估研究［J］. 地震学报, 31(2):205-211.
WANG Xiao-qing, DING Xiang, WANG Long, et al. 2009. A study on fast earthquake loss assessment and its application to 2008 Wenchuan M8 earthquake［J］. Acta Seismologica Sinica, 31(2):205-211(in Chinese).
熊俊楠, 韦方强, 苏鹏程, 等. 2013. 基于多源数据的四川省GDP千米格网化研究［J］. 应用基础与工程科学学报, 21(2):317-326. doi:10.3969/j.issn.1005-0930.2013.02.013.
XIONG Jun-nan, WEI Fang-qiang, SU Peng-cheng, et al. 2013. Research on GDP spatialization approach of Sichuan Province supported by multi-source data［J］. Journal of Basic Science and Engineering, 21(2):317-326(in Chinese).
尹之潜. 1995. 地震灾害及损失预测方法［M］. 北京:地震出版社.
YIN Zhi-qian. 1995. Earthquake Disaster and Loss Prediction Method［M］. Seismological Press, Beijing(in Chinese).
中国地震局震灾应急救援司. 2004. 地震应急［M］. 北京:地震出版社.
Earthquake Emergency Rescue Department, China Earthquake Administration. 2004. Earthquake Emergency Response［M］. Seismological Press, Beijing(in Chinese).
Bhaduri B, Bright E, Coleman P, et al. 2007. LandScan USA:A high-resolution geospatial and temporal modeling approach for population distribution and dynamics［J］. GeoJournal, 69:103-117.
Cai Q, Rushton G, Bhaduri B L, et al. 2006. Estimating small-area populations by age and sex using spatial interpolation and statistical inference methods［J］. Transactions in GIS, 10:577-598.
Dobson J E, Bright E A, Coleman P R, et al. 2000. Landscan:A global population database for estimating populations at risk［J］. Photogrammetric Engineering & Remote Sensing, 66:849-857.
Goodchild M F, Anselin L, Deichmann U. 1993. A framework for the areal interpolation of socioeconomic data［J］. Environment and Planning A, 25:383-397.

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基于千米格网的地震应急灾情预评估数据开发

DEVELOPMENT OF EARTHQUAKE EMERGENCY DISASTER INFORMATION PRE-EVALUATION DATA BASED ON KM GRID

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