Acta Optica Sinica, Volume. 39, Issue 7, 0728004(2019)

A Method for Hyperspectral Reflectance Reconstruction from Automatic Observation with Multispectral Radiometer

Zhihong Ma1,2, Lingling Ma1、*, Yaokai Liu1, Yongguang Zhao1, Ning Wang1, Chuanrong Li1, and Lingli Tang1
Author Affiliations
  • 1 Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China
  • 2 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
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    A method for hyperspectral reflectance reconstruction from observed data with an automatic multispectral radiometer is presented. The surface bidirectional reflectance distribution function effect is considered in our method in order to meet the on-orbit calibration requirement of sensors with different spectral characteristics and viewing angles. The satellite-ground synchronous observation data from the National Calibration and Validation Site for High Resolution Remote Sensors are used to validate the proposed method. The results show that the average relative difference between the reconstructed hyperspectral reflectance and the measured reflectance by a field spectrometer is about 2.67%. Compared with observation values of Sentinel-2A/B, the difference is less than 10% for each band. Furthermore, the results of uncertainty analysis show that uncertainty of hyperspectral reflectance obtained by the proposed method is about 3.34%. The overall uncertainty of radiometric calibration at blue, green, red, and near-infrared bands of Sentinel-2A/B is about 3.35%, 3.77%, 4.10%, and 4.29%, respectively.

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    Zhihong Ma, Lingling Ma, Yaokai Liu, Yongguang Zhao, Ning Wang, Chuanrong Li, Lingli Tang. A Method for Hyperspectral Reflectance Reconstruction from Automatic Observation with Multispectral Radiometer[J]. Acta Optica Sinica, 2019, 39(7): 0728004

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Feb. 1, 2019

    Accepted: Mar. 21, 2019

    Published Online: Jul. 16, 2019

    The Author Email: Ma Lingling (llma@aoe.ac.cn)

    DOI:10.3788/AOS201939.0728004

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