Abstract：Nighttime light imagery removes most natural disturbances, so nighttime images can be used to reflect human activity, especially for research on spatialization of socio-economic development. This study utilized night-light data collected by the Suomi-NPP satellite in a spatial correlation model with GDP data to analyze both the spatial distribution and factors influencing development. The model extracted the lighting information and calculated night-light indexes to select the best night-light index for each Chinese mainland province. Tests show that the normalized total radiance index relates well to the GDP, so this index is related to the GDP using linear and nonlinear spatial models to develop a model to predict the GDP. The fitting results for the linear, power law and logistic models are all greater than 0.8. The power law model predicts the GDP of each mainland provincial-level region in 2014 with an average relative error of only 26.0%.
郭永德, 高金环, 马洪兵. Suomi-NPP夜间灯光数据与GDP的空间关系分析[J]. 清华大学学报（自然科学版）, 2016, 56(10): 1122-1130.
GUO Yongde, GAO Jinhuan, MA Hongbing. Spatial correlation analysis of Suomi-NPP nighttime light data and GDP data. Journal of Tsinghua University(Science and Technology), 2016, 56(10): 1122-1130.
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2016, Vol. 56 
