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An Investigation of a Novel Cross-Calibration Method of FY-3C/VIRR against NPP/VIIRS in the Dunhuang Test Site
- Source :
- Remote Sensing, Vol 8, Iss 1, p 77 (2016)
- Publication Year :
- 2016
- Publisher :
- MDPI AG, 2016.
-
Abstract
- Radiometric cross-calibration of Earth observation sensors is an effective approach to evaluate instrument calibration performance, identify and diagnose calibration anomalies, and quantify the consistency of measurements from different sensors. In this study a novel cross-calibration method is proposed, taking into account the spectral and viewing angle differences adequately; the method is applied to the FY-3C/Visible Infrared Radiometer (VIRR), taking the Suomi National Polar-Orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) as a reference. The results show that the relative difference between the two sets increases from January to May 2014, and becomes lower for the data on 24 July, 11 September, and 16 September, within approximately 10%. This phenomenon is caused by the updating of the calibration coefficients in the VIRR datasets with results from a vicarious method on June 2014. After performing an approximate estimation of the uncertainty, it is demonstrated that this calibration has a total uncertainty of 5.5%–6.0%, which is mainly from the uncertainty of the Bidirectional Reflectance Distribution Function model.
- Subjects :
- Visible Infrared Imaging Radiometer Suite
Earth observation
FY-3C/VIRR
Radiometer
NPP/VIIRS
010504 meteorology & atmospheric sciences
Meteorology
Calibration (statistics)
Science
0211 other engineering and technologies
bidirectional reflectance distribution function model
02 engineering and technology
Viewing angle
01 natural sciences
Cross Calibration
cross-calibration
Consistency (statistics)
General Earth and Planetary Sciences
Environmental science
Bidirectional reflectance distribution function
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
spectral adjustment
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 8
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....243084db9b72dcdf7a3c0dd3af8f6257