Deciphering China’s Socio-Economic Disparities: A Comprehensive Study Using Nighttime Light Data

Tianyu Chen, Yuke Zhou*, Dan Zou, Jingtao Wu, Yang Chen, Jiapei Wu, Jia Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Achieving equitable and harmonized socio-economic development is a vital gauge of national progress, particularly in geographically extensive nations such as China. This study, employing nighttime lights as a socio-economic development indicator and remote sensing vegetation indices, investigates spatial variations in wealth distribution across China’s eastern and western regions, delineated by the Hu Huanyong Line. It uncovers the balance between economic growth and green space preservation and discrepancies in development and green space allocation. A thorough county-level analysis using this nighttime light (NTL) and vegetation index exposes the dynamic shifts in socio-economic focal points. The Gini coefficient, assessing inequality and spatial autocorrelation within the index ratio, enriches our regional development understanding. The findings depict a heterogeneous yet rapid economic expansion, primarily within a 30 km coastal buffer zone. Despite a decrease in Gini coefficients in both eastern and western regions, the potential for inland development escalates as coastal illumination approaches saturation. This study unveils enduring, yet lessening, economic disparities between eastern and western China, underscoring the necessity for green preservation in eastern development plans. Moreover, inland regions emerge as potential areas for accelerated development. This study offers crucial insights for formulating balanced, sustainable regional development strategies in China.

Original languageEnglish
Article number4581
JournalRemote Sensing
Volume15
Issue number18
DOIs
Publication statusPublished - Sept 2023

Keywords

  • Hu Huanyong line
  • big data mining
  • nighttime light data
  • socio-economic disparities
  • spatial autocorrelation
  • urbanization
  • vegetation index

Fingerprint

Dive into the research topics of 'Deciphering China’s Socio-Economic Disparities: A Comprehensive Study Using Nighttime Light Data'. Together they form a unique fingerprint.

Cite this