Analyzing multidimensional rural poverty alleviation at the county level in Guangxi based on remote sensing data of nighttime light
LU Yanling1,2(), HUANG Yaqi1, ZHOU Junfen3, WANG Jie1, WEI Jingshan4()
1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China 2. College of Earth Sciences, Guilin University of Technology, Guilin 541004, China 3. The Academy of Digital China, Fuzhou University, Fuzhou 350001, China 4. Department of Civil and Surveying Engineering, Guilin University of Technology at Nanning, Nanning 530001, China
A vital task for the current economic construction of China is to consolidate poverty alleviation achievements, implement rural revitalization strategies, and prevent poverty relapse. The 2022 Central Rural Work Conference emphasized that China must firmly prevent any large-scale relapse into poverty. The multidimensional poverty theory underlines the significant role of the dynamic and objective monitoring of the spatio-temporal evolution of rural poverty at the county level in China’s poverty-returning prevention. Rapid progress in remote sensing satellites has enabled the gradual enrichment and extensive application of high-quality remote sensing images that contain massive information. Compared to traditional statistical data, the remote sensing data of nighttime light exhibit a high correlation with socio-economic factors, pronounced objectivity, and a relatively long time span. This study constructed a model to describe the relationship between the nighttime light intensity index extracted from the DMSP/OLS and NPP/VIIRS remote sensing data, as well as the multidimensional poverty alleviation index. Using this model, this study explored the spatio-temporal evolution of rural poverty at the county level in Guangxi from 2010 to 2020 and analyzed the existing poverty-returning causes, providing a scientific reference and preventive measures for rural revitalization and poverty alleviation.
陆妍玲, 黄娅琦, 周俊芬, 王杰, 韦晶闪. 基于夜光遥感数据的广西县域农村多维脱贫分析[J]. 自然资源遥感, 2024, 36(1): 169-178.
LU Yanling, HUANG Yaqi, ZHOU Junfen, WANG Jie, WEI Jingshan. Analyzing multidimensional rural poverty alleviation at the county level in Guangxi based on remote sensing data of nighttime light. Remote Sensing for Natural Resources, 2024, 36(1): 169-178.
The Editorial Department of This Journal. Poverty alleviation:The first secretary,“the first”responsibility——“comprehensive well-off·poverty alleviation ”excellent first secretary in the village special report album complied preamble[J]. China Development Observation, 2020 (s2):1.
[2]
习近平. 在决战决胜脱贫攻坚座谈会上的讲话[N]. 人民日报,2020-03-07(2).
Xi J P. Speech at a Symposium on fighting a decisive battle to poverty alleviation[N]. People’s Daily,2020-03-07(2).
Li D R, Li X. Application of night light remote sensing technology in assessing economic and social development ——Also on its guarantee for the construction quality of “the Belt and Road”[J]. Journal of Macro-quality Research, 2015, 3 (4):1-8.
Yu B l, Wang C X, Gong W K, et al. Nighttime light remote sensing and urban studies:Data,methods,applications,and prospects[J]. National Remote Sensing Bulletin, 2021, 25(1):342-364.
doi: 10.11834/jrs.20211018
Zhang B J. Analysis of the inter-annual variation of nighttime lights in the most affected area of Wenchuan earthquake from 2003 to 2013[J]. Journal of Catastrophology, 2018, 33 (1):12-18,22.
Ruan O, Liu S H, Chen F, et al. Analysis on the spatial and temporal changes of county rural poverty in Guizhou Province[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2022, 43(5):156-168.
[7]
Sabina A, James F. Counting and multidimensional poverty measurement[J]. Journal of Public Economics, 2010, 95(7):476-487.
doi: 10.1016/j.jpubeco.2010.11.006
[8]
Wang Y H, Wang B X. Multidimensional poverty measure and analysis:A case study from Hechi City,China[J]. SpringerPlus, 2016, 5(1):1-25.
doi: 10.1186/s40064-015-1659-2
Liu Y H, Xu Y. Geographical identification and classification of multi-dimensional Poverty in rural China[J]. Acta Geographica Sinica, 2015, 70 (6):993-1007.
doi: 10.11821/dlxb201506012
[10]
方迎风, 张芬. 多维贫困测度的稳定性分析[J]. 统计与决策, 2017(24):84-89.
Fang Y F, Zhang F. Stability study on analysis of multidimensional poverty measurement[J]. Statistics & Decision, 2017 (24):84-89.
Wang Z, Cheng J H, Cui M J. Prediction of regional poverty degree prediction based on night time light remote sensing data[J]. Mine Surveying, 2018, 46 (6):27-33.
[12]
胡艳兴. 基于夜间灯光数据的中国贫困空间识别研究[D]. 兰州: 西北师范大学, 2016.
Hu Y X. Research on spatial identification of poverty in China based on night time light data[D]. Lanzhou: Northwest Normal University, 2016.
2024, Vol. 36 
), 黄娅琦1, 周俊芬3, 王杰1, 韦晶闪4(
