基于AHP-熵权法的瑞丽市边境线新冠疫情风险及防控部署研究
Risks and the prevention and control deployment of COVID-19 infection along the border of Ruili City based on the AHP-entropy weight method
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摘要: 目前中国的新冠疫情已经得到了控制,但国际上新冠病毒传播形势依然严峻,中国边境地区仍面临较高风险,瑞丽市作为中缅边境重要口岸城市,其国境线疫情防控难度较大。研究运用地理信息系统技术、遥感技术和AHP-熵权法,选取地形因子、交通因子、基础因子分析瑞丽市边境线上风险较高的空间位置部署防控点,提高防控的科学性。结果表明,瑞丽市需要重点防控的高风险地区位于靠近边境的西南地带及南部地带,这些地区具有以下特征: ①地形平缓,植被覆盖度较高; ②交通便利、靠近水系; ③居民点密度较高。同时,基于集合覆盖模型并结合ArcGIS视域分析,部署了35个防控点,以达到完整观测边境线的目的,根据防控重要性从高到低将这些防控点分为22个一级防控点、8个二级防控点和5个三级防控点。研究可为边境地区提高疫情防控能力提供参考。Abstract: Although the COVID-19 pandemic has been contained in China presently, it remains a major threat to the international environment. The border areas of China remain at high risk of COVID-19 infection, including Ruili, an important port city on the border between China and Myanmar, which still faces great challenges in pandemic prevention and control along the border. This study analyzed the topographic, traffic, and basic factors of Ruili using the GIS technology, the remote sensing technology, and the AHP-entropy weight method and identified locations with high risks of the pandemic along the border, aiming to achieve more scientific the pandemic prevention and control. The results showed that the high-risk areas in Ruili that need major pandemic prevention and control were in the southwestern and southern zones near the border and had the following characteristics: ① gentle terrain with high fractional vegetation cover; ② convenient transportation and proximity to water systems; ③ high settlement density. To achieve a complete observation of the border, a total of 35 prevention and control points were deployed based on the set covering location model combined with the ArcGIS viewshed analysis. They were divided into 22 primary, 8 secondary, and 5 tertiary prevention and control points, of which the importance of pandemic prevention and control increased gradually. This study can provide references for improving the pandemic prevention and control capacity of border areas.
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