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Articles | Volume XLII-3/W10
https://doi.org/10.5194/isprs-archives-XLII-3-W10-783-2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-783-2020
08 Feb 2020
 | 08 Feb 2020

GDP SPATIALIZATION AND DYNAMIC ANALYSIS BASED ON DMSP/OLS IMAGES: A CASE OF HENAN PROVINCE

R. X. Ma, B. L. Fu, H. C. He, and D. L. Fan

Keywords: DMSP/OLS Night-time Light images, GDP, Correlation Analysis, Regression Modeling, Spatial Visualization

Abstract. Gross Domestic Product (GDP) is an important statistical indicator for quantitatively studying of economic development and space distribution characteristics. However, GDP has been often calculated based on administrative units without fine describing the difference of space distribution in the administrative unit. This paper calculated night-light indexes of Henan province using DMSP/OLS remote sensing data in 2006 and 2013. Those correlation between different light indexes and GDP was analyzed, and the best regression model of GDP was constructed. The accuracy of statistical data in 2006 and 2013 was used to verify the accuracy. The spatial visualization and dynamic analysis of GDP in Henan province were realized. Finally, this paper realized the spatial visualization and dynamic analysis of GDP in Henan province and produced 1 km × 1 km distribution map of GDP density.The results showed that the Total Night-time Light (TNL) index had the highest correlation with GDP in 2010 with the coefficient of 0.928, R2 was 0.861. The TNL indicator and GDP in 2013 achieved the correlation coefficient of 0.930, R2 was 0.865. the average relative error between GDP simulation value and statistical value in 2006 and 2013 is 8.19%, 8.08%, respectively.The GDP density map of 18 prefecture-level cities in Henan province showed an obvious expansion trend from 2006 to 2013.This research demonstrated that the Night-time light data could be used as an important index of analyzing economic status of Henan province. The model between light indicators and GDP could better simulate the spatial distribution of regional economic development.