Share Email Print
cover

Proceedings Paper

Ground-based automated radiometric calibration system in Baotou site, China
Author(s): Ning Wang; Chuanrong Li; Lingling Ma; Yaokai Liu; Fanrong Meng; Yongguang Zhao; Bo Pang; Yonggang Qian; Wei Li; Lingli Tang; Dongjin Wang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Post-launch vicarious calibration method, as an important post launch method, not only can be used to evaluate the onboard calibrators but also can be allowed for a traceable knowledge of the absolute accuracy, although it has the drawbacks of low frequency data collections due expensive on personal and cost. To overcome the problems, CEOS Working Group on Calibration and Validation (WGCV) Infrared Visible Optical Sensors (IVOS) subgroup has proposed an Automated Radiative Calibration Network (RadCalNet) project. Baotou site is one of the four demonstration sites of RadCalNet. The superiority characteristics of Baotou site is the combination of various natural scenes and artificial targets. In each artificial target and desert, an automated spectrum measurement instrument is developed to obtain the surface reflected radiance spectra every 2 minutes with a spectrum resolution of 2nm. The aerosol optical thickness and column water vapour content are measured by an automatic sun photometer. To meet the requirement of RadCalNet, a surface reflectance spectrum retrieval method is used to generate the standard input files, with the support of surface and atmospheric measurements. Then the top of atmospheric reflectance spectra are derived from the input files. The results of the demonstration satellites, including Landsat 8, Sentinal-2A, show that there is a good agreement between observed and calculated results.

Paper Details

Date Published: 10 October 2017
PDF: 8 pages
Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, 104271J (10 October 2017); doi: 10.1117/12.2278072
Show Author Affiliations
Ning Wang, Academy of Opto-Electronics (China)
Chuanrong Li, Academy of Opto-Electronics (China)
Lingling Ma, Academy of Opto-Electronics (China)
Yaokai Liu, Academy of Opto-Electronics (China)
Fanrong Meng, Academy of Opto-Electronics (China)
Yongguang Zhao, Academy of Opto-Electronics (China)
Bo Pang, Academy of Opto-Electronics (China)
Univ. of Chinese Academy of Science (China)
Yonggang Qian, Academy of Opto-Electronics (China)
Wei Li, Academy of Opto-Electronics (China)
Lingli Tang, Academy of Opto-Electronics (China)
Dongjin Wang, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 10427:
Image and Signal Processing for Remote Sensing XXIII
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top