
Proceedings Paper
On-orbit radiometric calibration of Earth-observing sensors using the Radiometric Calibration Test Site (RadCaTS)Format | Member Price | Non-Member Price |
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Paper Abstract
Vicarious techniques are used to provide supplemental radiometric calibration data for sensors with onboard calibration
systems, and are increasingly important for sensors without onboard calibration systems. The Radiometric Calibration
Test Site (RadCaTS) is located at Railroad Valley, Nevada. It is a facility that was developed with the goal of increasing
the amount of ground-based radiometric calibration data that are collected annually while maintaining the current level
of radiometric accuracy produced by traditional manned field campaigns. RadCaTS is based on the reflectance-based
approach, and currently consists of a Cimel sun photometer to measure the atmosphere, a weather station to monitor
meteorological conditions, and ground-viewing radiometers (GVRs) that are used the determine the surface reflectance
throughout the 1 × 1-km area. The data from these instruments are used in MODTRAN5 to determine the at-sensor
spectral radiance at the time of overpass.
This work describes the RadCaTS concept, the instruments used to obtain the data, and the processing method used to
determine the surface reflectance and top-of-atmosphere spectral radiance. A discussion on the design and calibration of
three new eight-channel GVRs is introduced, and the surface reflectance retrievals are compared to in situ
measurements. Radiometric calibration results determined using RadCaTS are compared to Landsat 7 ETM+, MODIS,
and MISR.
Paper Details
Date Published: 24 May 2012
PDF: 9 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83902B (24 May 2012); doi: 10.1117/12.918614
Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)
PDF: 9 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83902B (24 May 2012); doi: 10.1117/12.918614
Show Author Affiliations
Jeffrey S. Czapla-Myers, College of Optical Sciences, The Univ. of Arizona (United States)
Nathan P. Leisso, College of Optical Sciences, The Univ. of Arizona (United States)
Nathan P. Leisso, College of Optical Sciences, The Univ. of Arizona (United States)
Nikolaus J. Anderson, College of Optical Sciences, The Univ. of Arizona (United States)
Stuart F. Biggar, College of Optical Sciences, The Univ. of Arizona (United States)
Stuart F. Biggar, College of Optical Sciences, The Univ. of Arizona (United States)
Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)
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