Evaluating the influence of COVID-19 pandemic on socioeconomic development in Wumeng Mountain area based on multi-source remote sensing data

被引:0
作者
Hu, Ting [1 ,2 ,3 ,4 ]
Li, Niantan [1 ]
Yang, Qiquan [5 ,6 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing, Peoples R China
[2] Hubei Luojia Lab, Wuhan, Peoples R China
[3] Minist Nat Resources, Technol Innovat Ctr Integrat Applicat Remote Sensi, Nanjing, Peoples R China
[4] Jiangsu Engn Ctr Collaborat Nav Positioning & Smar, Nanjing, Peoples R China
[5] Macau Univ Sci & Technol, State Key Lab Lunar & Planetary Sci, Macau 999078, Peoples R China
[6] Tongji Univ, Coll Surveying & Geoinformat, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Socioeconomic development; Wumeng Mountain area; COVID-19; pandemic; trend analysis; land use/land cover; POVERTY ALLEVIATION; CHINA; DYNAMICS;
D O I
10.1080/17538947.2024.2391031
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Assessing the socioeconomic development of rural areas is important for the targeted implementation of rural revitalization in China, especially after three years of COVID-19 pandemic restrictions. However, the influence of COVID-19 on socioeconomic development in rural areas remains unclear. Therefore, this paper constructed a comprehensive socioeconomic development index (SEDI) by considering county-level statistics on natural environment, social resources, and economy as proxies for assessing local socioeconomic development, and analyzed the influence of COVID-19 from the changing pattern of SEDI before and after COVID-19, with Wumeng Mountain (WM) area as the study case. In response to the absence and untimeliness of statistics, we employed both nighttime light (NTL) and land use/land cover (LULC) features to fill in these missing SEDIs from 2013 to 2022, using random forest regression. With the assistance of LULC, the overall R2 increased from 0.7763 to 0.9056, and the estimation accuracy improved in 36 out of 38 counties. All counties in WM experienced an increase in SEDI, and the growth rate did not slow down, proving the effective implementation of rural revitalization strategy. Also, the spatial clustering pattern remained relatively stable. These findings provide scientific foundations for the local government to assess comprehensive development and formulate policies.
引用
收藏
页数:22
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