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Liu, JJ, Li, Z, Qiao, YL, Liu, YJ, Zhang, YX (2004). A new method for cross-calibration of two satellite sensors. INTERNATIONAL JOURNAL OF REMOTE SENSING, 25(23), 5267-5281.

Abstract
Given that many operational satellite sensors are not calibrated, while a handful of research sensors are, cross-calibration between the two types of sensor is a cost-effective means of calibration. A new method of sensor cross-calibration is demonstrated here using the Chinese Multi-channel Visible Infrared Scanning radiometer (MVIRS) and the US Moderate Resolution Imaging Spectrometer (MODIS). MVIRS has six channels, equivalent to the current National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and four additional ones for remote sensing of ocean colour and moisture. The MVIRS on-board China's polar-orbiting meteorological satellite (FY-1D) was launched on 15 May 2002 with an earlier overpass time than Terra. The sensor has no on-board calibration assembly. This study attempts to calibrate MVIRS against the well-calibrated MOMS, by taking a series of measures to account for their differences. Clear-sky measurements made from the two sensors in July-October 2002 were first collocated. Using the 6S radiative transfer model, MODIS reflectances measured at the top-of-the atmosphere were converted into surface reflectances. They were corrected to the viewing geometry of the MVIRS using the bidirectional reflectance distribution function (BRDF) measured on the ground. The spectral response functions of the two sensors were employed to account for spectral discrepancies. After these corrections, very close linear correlations were found between radiances estimated from the MODIS and the digital readings from the MVIRS, from which the calibration gains were derived. The gains differ considerably from the pre-launch values and are subject to degradation over time. The calibration accuracy is estimated to be less than 5%, which is compatible to that obtained by the more expensive vicarious calibration approach.

DOI:
10.1080/01431160412331269779

ISSN:
0143-1161

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