Analyzing multidimensional rural poverty alleviation at the county level in Guangxi based on remote sensing data of nighttime light

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.