Capability assessment of DMSP-OLS and NPP-VIIRS nighttime light data estimating statistical indicators: a case of county-level GDP, population and energy consumption in Beijing-Tianjin-Hebei region

doi:10.13474/j.cnki.11-2246.2020.0290

Abstract

Abstract: Nighttime light data, which records the intensity of artificial light on the earth's surface, is one of the effective means to estimate social statistical indicators. To assess the simulation potential of DMSP-OLS, NPP-VIIRS nighttime light data for social statistical indicators, four common light correction methods are respectively used for saturation correction of two nighttime light data. Three linear regression models are respectively applied to construct between GDP, population, energy consumption data and the corrected nighttime light data from Beijing-Tianjin-Hebei. Then, the correlation coefficient of model fitting, statistical value of F and probability value of p are employed to analyze and evaluate the ability of two kinds of night light data in terms of measuring GDP, population and energy consumption. The results show that EANTLI method is the best correction method for two kinds of night light data, while HSI method is not suitable for fitting the linear relationship between nighttime light data and county-level social statistical index. The two kinds of night light data both have a good fitting effect on GDP. The fitting ability of social statistical indicators of NPP-VIIRS data is better than that of DMSP-OLS data.

Key words: DMSP-OLS, NPP-VIIRS, nighttime light, statistical index measurement, GDP, population, energy consumption

CLC Number:

P237

LI Feng, ZHANG Xiaobo, LIAO Shunbao, QIAN An. Capability assessment of DMSP-OLS and NPP-VIIRS nighttime light data estimating statistical indicators: a case of county-level GDP, population and energy consumption in Beijing-Tianjin-Hebei region[J]. Bulletin of Surveying and Mapping, 2020, 0(9): 89-93,118.

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