Journal of Atmospheric and Environmental Optics ›› 2024, Vol. ›› Issue (2): 125-141.doi: 10.3969/j.issn.1673-6141.2024.02.001

Previous Articles    

Research progress of atmospheric remote sensing based on satellite nighttime low-light data

MA Yu 1,2,3, ZHANG Wenhao 1,2,3*, ZHANG Lili 4,5, WU Yu 6, TANG Jianxiong 1,2,3, FU Yashuai 1,2,3   

  1. 1 School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China; 2 Heibei Space Remote Sensing Information Processing and Application of Collaborative Innovation Center, Langfang 065000, China; 3 Institute of Remote Sensing Applications North China Institute of Aerospace Engineering, Langfang 065000, China; 4 Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; 5 Zhongke Langfang Institute of Spatial Information Applications, Langfang 065001, China; 6 School of Earth System Science, Tianjin University, Tianjin 300072, China
  • Received:2022-07-20 Revised:2022-09-22 Online:2024-03-28 Published:2024-04-18

Abstract: With the launch of a series of nighttime low-light remote sensing satellites, such as Defense Meteology Satellite Program (DMSP) and Suomi National Polar-orbiting Partnership (Suomi NPP), the application of low-light data in quantitative remote sensing has received increasing attention from researcher. However, there is still a lack of research summaries in the field of atmospheric remote sensing based on night-light data. Therefore, a comprehensive review of atmospheric remote sensing research based on nighttime low-light data in the past 20 years is presented. The progress of nighttime low-light atmospheric remote sensing research is summarized from three aspects: radiometric calibration low-light imager of low-light radiation transfer model and atmospheric parameters research based on low-light data. The application status and characteristics of low light data in atmospheric remote sensing research are also reviewed in this paper, which will provide a valuable reference for future in-depth application of night lowlight data in atmospheric remote sensing.

Key words: nighttime low-light remote sensing, quantitative remote sensing, radiometric calibration; radiative transfer model, atmospheric remote sensing

CLC Number: