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An image layer difference index method to extract light area from NPP/VIIRS nighttime light monthly data

Jiang, Shuai, Li, Jia, Duan, Ping, Wei, Yadong
International journal of remote sensing 2019 v.40 no.12 pp. 4839-4855
image analysis, light intensity, regression analysis, remote sensing, satellites, China
Nighttime light data have been proven to perform well for economic measurements and built-up area extractions. However, the new generation of monthly NPP/VIIRS data series products, which collected from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite contains background values, which relatively restrict the potential application of nighttime images. Therefore, the image layer difference index (LDI) was constructed to obtain high-intensity pixels that have radiance mainly caused by urban light glow. In addition, an empirical threshold was used to extract low-intensity pixels. Thirty-eight counties in Chongqing Province in China were used as an example for this experimental research. To verify the accuracy of the proposed method, a linear regression model, which was based on the quantitative statistics of the pixels, exhibited the coefficient of determination R² values of 0.980 and 0.947. Considering the interrelation between the light intensity and economic level, statistical data of the county-level economy was also used for further confirmation; the R² values of the linear regression between the computed indexes were 0.924 and 0.909.