The desaturation method of DMSP/OLS nighttime light data based on vector data: taking the rapidly urbanized China as an example

ABSTRACT

The saturation of night light data caused by sensor defects conceals the differences and details of light luminance in the urban area, which greatly limits the application of Nighttime Light (NTL) in the study of urbanization. Although some methods have been proposed to mitigate the saturation of NTL data, the research of desaturation is worth further advancing due to its shortcomings in highlighting light differences and spatial resolution. Therefore, we propose a new spectral index, the Vector Data Adjusted NTL Index (VDANTLI) after analyzing the influence of different auxiliary parameters on saturation elimination. Then, we select the three most developed urban agglomerations in China and make a series of qualitative and quantitative analysis. The results of various assessments confirm that VDANTLI can effectively alleviate NTL saturation and enhance urban lighting differences. Moreover, by dynamically adjusting the length of the grid and single-phase vector data modified time-series NTL data, we further achieve the resolution-series and time-series VDANTLI. Therefore, compared with previous desaturation models, the VDANTLI can be used as an effective indicator and even an indispensable basic data for urbanization research and socio-economic spatial analysis because of its unique advantages in spatial resolution and the capability in time-series native NTL desaturation.

KEYWORDS:

• VDANTLI
• urbanization
• DMSP/OLS
• saturation
• China

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was jointly supported by Natural Science Foundation of Guangdong Province, China (Grant No. 2016A030313551) and National Natural Science Foundation of China (Grant No. 41671430).

Notes on contributors

Zihao Zheng

Zihao Zheng is a Ph. D. student at University of Padova and works in the area of urban remote sensing and nighttime light data analysis.

Yingbiao Chen

Yingbiao Chen is a professor with Guangzhou University and works in the area of GIS spatial analysis and urbanization research.

Zhifeng Wu

Zhifeng Wu is a professor with Guangzhou University and works in the area of urban remote sensing and urbanization complex surface process.

Xinyue Ye

Xinyue Ye is an associate professor at Department of Informatics, New Jersey Institute of Technology and works in the area of space-time analysis, regional science, and new economic geography.

Guanhua Guo

Guanhua Guo receives the Ph.D. degree in University of Chinese Academy of Sciences. He is currently a lecturer with Guangzhou University and works in the area of urban thermal environment and heat island effect.

Qinglan Qian

Qinglan Qian is a professor with Guangzhou University and works in the area of regional economy and planning.