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自然资源遥感  2022, Vol. 34 Issue (3): 218-226    DOI: 10.6046/zrzyyg.2021299
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
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
李益敏1,2(), 吴博闻1, 刘师旖1, 李盈盈1, 袁静1
1.云南大学地球科学学院,昆明 650500
2.云南省高校国产高分卫星遥感地质工程研究中心,昆明 650500
Risks and the prevention and control deployment of COVID-19 infection along the border of Ruili City based on the AHP-entropy weight method
LI Yimin1,2(), WU Bowen1, LIU Shiyi1, LI Yingying1, YUAN Jing1
1. School of Earth Sciences, Yunnan University, Kunming 650500, China
2. Remote Sensing Geological Engineering Research Center for Domestic Gaofen Satellite of Yunnan Universities, Kunming 650500, China
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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。

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李益敏
吴博闻
刘师旖
李盈盈
袁静
关键词 边境防控瑞丽市新冠疫情    
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.

Key wordsprevention and control along the border    Ruili City    COVID-19 pandemic
收稿日期: 2021-09-18      出版日期: 2022-09-21
ZTFLH:  TP79  
基金资助:云南省科技厅-云南大学联合基金重点项目“‘天空地’协同的高山峡谷区重大地质灾害隐患识别监测预警研究”(2019FY003017);中国地质调查局地质调查项目“中印边境东段和中缅边境地区遥感地质解译项目”(DD20190545)
作者简介: 李益敏(1965-),女,研究员,主要从事3S技术在山地资源环境和地质灾害中的应用研究。Email: 648119611@qq.com
引用本文:   
李益敏, 吴博闻, 刘师旖, 李盈盈, 袁静. 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[J]. 自然资源遥感, 2022, 34(3): 218-226.
LI Yimin, WU Bowen, LIU Shiyi, LI Yingying, YUAN Jing. Risks and the prevention and control deployment of COVID-19 infection along the border of Ruili City based on the AHP-entropy weight method. Remote Sensing for Natural Resources, 2022, 34(3): 218-226.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2021299      或      https://www.gtzyyg.com/CN/Y2022/V34/I3/218
Fig.1  瑞丽市区位图
因子类型 指标 选取依据



地形因子
植被覆盖度(B1) 植被覆盖指数越高的地区防控风险越高
海拔(B2) 海拔较高的地方难以入境
坡度(B3) 坡度较小、地势越平坦越容易入境



交通因子
水系距离(B4) 距离水系距离越近的点越容易作为偷渡者的登陆点
交通密度(B5) 交通密度越大的地区防控风险越大


基础因子
人口密度(B6) 人口密度越高的地区防控风险越大
管控基础设施(B7) 越靠近管控基础设施的地区防控风险越低
Tab.1  瑞丽市边境防控风险评估指标体系
Fig.2  瑞丽市坡度分级
Fig.3  瑞丽市植被覆盖指数图
Fig.4  瑞丽市交通密度图
Fig.5  瑞丽市人口密度图
防控指标因子 熵权法权重 AHP法权重 综合权重
植被覆盖度(B1) 0.011 3 0.165 8 0.071 4
海拔(B2) 0.004 3 0.091 3 0.038 1
坡度(B3) 0.003 4 0.301 3 0.119 3
水系距离(B4) 0.036 2 0.030 5 0.034 0
交通密度(B5) 0.244 0 0.091 5 0.184 6
人口密度(B6) 0.365 7 0.255 7 0.322 9
管控基础设施(B7) 0.338 0 0.063 9 0.231 4
Tab.2  瑞丽市疫情防控指标综合权重
Fig.6  瑞丽市境内地区防疫风险评价
Fig.7  瑞丽市边境线疫情防控风险评价
Fig.8  边境线防控点选址部署
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