危险化学品泄漏灾害链的构建及其时空推导

IF 1.8 Q3 REMOTE SENSING

International Journal of Image and Data Fusion Pub Date : 2021-07-25 DOI:10.1080/19479832.2021.1958929

Xinxin Zheng, Fei Wang, Wenyu Jiang, Xiaocui Zheng, Zuhe Wu, Xiaohui Qiao, Q. Meng, Q. Chen

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引用次数: 4

摘要

摘要危险化学品是现代工业发展不可或缺的物质。然而，危险化学品的储存、运输或处理不当会引发泄漏、爆炸等连锁灾害，严重威胁人民生命、社会、经济和自然环境的安全。本研究基于灾害系统理论，分析了危险化学品泄漏引发的各种灾害事件的发生和演化过程，从灾害发生因素、灾害孕育环境、灾害影响主体、灾后损失等方面构建了危险化学品泄露灾害链。以一起甲烷泄漏事故为例，在三维地理场景中对危险化学品泄漏灾害链进行了数值模拟和时空动态推导。该研究可以为处理危险化学品泄漏灾害提供支持，并协助知情决策，包括监测、预警、灾害预测和预防、应急准备和灾后应对，进一步提高应急响应和城市安全管理的效率。

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Construction and spatio-temporal derivation of hazardous chemical leakage disaster chain

ABSTRACT Hazardous chemicals are indispensable substances for the development of modern industries. However, improper storage, transportation, or handling of hazardous chemicals can cause chain disasters such as leakage and explosion, seriously threatening the safety of people’s lives, society, economy, and natural environment. In this study, we analysed the occurrence and evolution process of various disaster events caused by hazardous chemical leakage based on the disaster system theory, and constructed a hazardous chemical leakage disaster chain from the aspects of disaster-causing factors, disaster-pregnant environment, hazard-affected bodies, and post-disaster losses. Taking a methane leakage accident as a case study, we conducted numerical simulation and spatio-temporal dynamic derivation on the hazardous chemical leakage disaster chain in a three-dimensional (3-D) geographic scene. This study can provide support on handling hazardous chemical leakage disasters and assist informed decision-making, including monitoring, pre-warning, disaster forecast and prevention, emergency preparedness, and post-disaster response, further improving the efficiency of emergency response and urban safety management.

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来源期刊

International Journal of Image and Data Fusion REMOTE SENSING-

CiteScore

5.00

自引率

0.00%

发文量

期刊介绍： International Journal of Image and Data Fusion provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications. Image and data fusion techniques are important for combining the many sources of satellite, airborne and ground based imaging systems, and integrating these with other related data sets for enhanced information extraction and decision making. Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in-situ, and other statistical data sets for improved information extraction, as well as to increase the reliability of the information. This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence based management. The journal welcomes original research papers, review papers, shorter letters, technical articles, book reviews and conference reports in all areas of image and data fusion including, but not limited to, the following aspects and topics: • Automatic registration/geometric aspects of fusing images with different spatial, spectral, temporal resolutions; phase information; or acquired in different modes • Pixel, feature and decision level fusion algorithms and methodologies • Data Assimilation: fusing data with models • Multi-source classification and information extraction • Integration of satellite, airborne and terrestrial sensor systems • Fusing temporal data sets for change detection studies (e.g. for Land Cover/Land Use Change studies) • Image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets (e.g. geometric information, topological information, statistical information, etc.).