使用全局细分网格的紧急机场选址

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2021-11-28 DOI:10.1080/20964471.2021.1996866
Bing Han, Tengteng Qu, Zili Huang, Qiangyu Wang, Xinlong Pan
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引用次数: 7

摘要

摘要大震级灾害的发生已引起公众对应急设施选址多样化的关注。尤其是应急机场选址问题,其复杂性较大,相关研究较少。机场应急选址是一个时空范围广、数据量大、环境信息复杂的场景,传统的设施选址方法可能不适用于大尺度时变的机场环境。本文提出了一个基于GeoSOT-3D全球细分网格模型的应急机场选址应用程序,证明了离散全球网格系统作为选址空间数据结构的良好适用性。本文提出了一个增加惩罚因子的目标函数来解决机场建设中覆盖和环境的约束。通过模拟退火算法的多次迭代,可以从多个预选点中选择出最优的机场建设位置。经过实验验证,本研究可以有效合理地解决不同情况下的应急机场选址问题。
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Emergency airport site selection using global subdivision grids
ABSTRACT The occurrence of large-magnitude disasters has significantly aroused public attention regarding diversified site selection of emergency facilities. In particular, emergency airport site selection (EASS) is highly complicated, and relevant research is rarely conducted. Emergency airport site selection is a scenario with a wide spatiotemporal range, massive data, and complex environmental information, while traditional facility site selection methods may not be applicable to a large-scale time-varying airport environment. In this work, an emergency airport site selection application is presented based on the GeoSOT-3D global subdivision grid model, which has demonstrated good suitability of the discrete global grid system as a spatial data structure for site selection. This paper proposes an objective function that adds a penalty factor to solve the constraints of coverage and the environment in airport construction. Through multiple iterations of the simulated annealing algorithm, the optimal airport construction location can be selected from multiple preselected points. With experimental verifications, this research may effectively and reasonably solve the emergency airport site selection issue under different circumstances.
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来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
期刊最新文献
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