A simple self-adjusting model for correcting the blooming effects in DMSP-OLS nighttime light images

REMOTE SENSING OF ENVIRONMENT

卷:224

Article

Cao, Xin¹  Hu, Yang¹  Zhu, Xiaolin²  Shi, Feng³  Zhuo, Li^4,5  Chen, Jin¹ 

[1] Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China

[2] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China

[3] Qilu Univ Technol, Inst Sci & Technol Dev Shandong, Shandong Acad Sci, Jinan 250014, Shandong, Peoples R China

[4] Sun Yat Sen Univ, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R China

[5] Sun Yat Sen Univ, Sch Geog & Planning, Ctr Integrated Geog Informat Anal, Guangzhou 510275, Guangdong, Peoples R China

关键词: DMSP-OLS;    Nighttime light;    Blooming;    Spatial response function;    Self-adjusting model;   

DOI  :  10.1016/j.rse.2019.02.019

来源: Elsevier

【 摘 要 】

Night-time light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operation Linescan System (OLS) provide important observations of human activities; however, DMSP-OLS NTL data suffer from problems such as saturation and blooming. This research developed a self-adjusting model (SEAM) to correct blooming effects in DMSP-OLS NTL data based on a spatial response function and without using any ancillary data. By assuming that the pixels adjacent to the background contain no lights (i.e., pseudo light pixels, PLPs), the blooming effect intensity, a parameter in the SEAM model, can be estimated by pixel-based regression using PLPs and their neighboring light sources. SEAM was applied to all of China, and its performance was assessed for twelve cities with different population sizes. The results show that SEAM can largely reduce the blooming effect in the original DMSP-OLS dataset and enhance its quality. The images after blooming effect correction have higher spatial similarity with Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) images and higher spatial variability than the original DMSP-OLS data. We also found that the average effective blooming distance is approximately 3.5 km in China, which may be amplified if the city is surrounded by water surfaces, and that the blooming effect intensity is positively correlated to atmospheric quality. The effectiveness of the proposed model will improve the capacity of DMSP-OLS images for mapping the urban extent and modeling socioeconomic parameters.

【 授权许可】

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