A Wide-Angle Hyperspectral Top-of-Atmosphere Reflectance Model for the Libyan Desert

Author:

Guo Fuxiang12ORCID,Zheng Xiaobing1ORCID,Zhang Yanna3,Wei Wei1,Zhang Zejie4,Zhang Quan1,Li Xin1

Affiliation:

1. Key Laboratory of Optical Calibration and Characterization, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

2. Graduate School, University of Science and Technology of China, Hefei 230026, China

3. School of Electrical Engineering, Anhui Polytechnic University, Wuhu 241000, China

4. Department of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, UK

Abstract

Reference targets with stability, uniformity, and known reflectance on the Earth’s surface, such as deserts, can be used for the absolute radiometric calibration of satellite sensors. A wide-angle hyperspectral reflectance model at the top of atmosphere (TOA) over such a reference target will expand the applicability of on-orbit calibration to different spectral bands and angles. To achieve the long-term, continuous, and high-precision absolute radiometric calibration of remote sensors, a wide-angle hyperspectral TOA reflectance model of the Libyan Desert was constructed based on spectral reflectance data, satellite overpass parameters, and atmospheric parameters from the Terra/Aqua and Earth Observation-1 (EO-1) satellites between 2003 and 2012. By means of angle fitting, viewing angle grouping, and spectral extension, the model is applicable for absolute radiometric calibration of the visible to short-wave infrared (SWIR) bands for sensors within viewing zenith angles of 65 degrees. To validate the accuracy and precision of the model, a total of 3120 long-term validations of model accuracy and 949 cross-validations with the Landsat 8 Operational Land Imager (OLI) and Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors between 2013 and 2020 were conducted. The results show that the TOA reflectance calculated by the model had a standard deviation (SD) of relative differences below 1.9% and a root-mean-square error (RMSE) below 0.8% when compared with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 OLI. The SD of the relative differences and the RMSE were within 2.7% when predicting VIIRS data.

Funder

National Natural Science Foundation of China

HFIPS Director’s Fund

Publisher

MDPI AG

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