Application note: evaluation of the Gini coefficient at the county level in mainland China based on Luojia 1-01 nighttime light images - Banshao Hu; Weixin Zhai; Dong Li; Junqing Tang (Computational Urban Science, 2024)
Abstract The Luojia 1–01 (LJ1-01) night lighting satellite's superior spatial information capture capability provides conditions for accurate assessment of regional wealth distribution inequality (RWDI) at a small scale. This paper evaluated the wealth Gini coefficient (WGC) of 2,853 counties and 31 provinces in mainland China to establish a comprehensive picture of inequalities at county-level regions in China as a whole, using data from LJ1-01 and the Suomi National Polar Orbiter Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The WGC values (LJ-Gini) calculated by the LJ1-01 data are always higher than those (NPP-Gini) based on NPP-VIIRS, and the mean of the ratio between them is 1.7. Compared with NPP-Gini, LJ-Gini showed sensitivity to low RWDI areas. The average county and provincial LJ-Gini are statistically consistent, 0.77 and 0.78; County LJ-Gini’s volatility is significantly higher than that of the provincial LJ-Gini, with standard deviations (SD) 0.13 and 0.096. The differences of RWDI in the regions within some provinces are more significant than in other provinces. For example, the SD of Tibet is 0.31, while all provinces' average SD is 0.13. In addition, this paper establishes a grading criterion based on the normal distribution abstracted from provincial LJ-Gini to reflect the corresponding relationship between the LJ-Gini value and the five inequality ranks. Totally, RWDI demonstrates heterogeneity at various spatial scales and regions, and it correlates negatively with economic development. The superior performance of LJ1-01 data in evaluating county-level RWDI demonstrates its potential to evaluate RWDI on a smaller scale, such as communities and streets.