@inproceedings{a9819b95e8144f6bb295f91e7903957b,
title = "Ground comparisons at RadCalNet sites to determine the equivalence of sites within the network",
abstract = "The Radiometric Calibration Network (RadCalNet, www.radcalnet.org) routinely brings together data from several instrumented ground sites to provide users with top-of-atmosphere (TOA) reflectance data. These data are provided on cloud free days between 09:00 and 15:00 for the spectral range 400 to 1000 nm (and up to 2500 nm depending on available instrumentation) at a 10 nm spectral resolution. The data represents the nadir view of the ground. A key aspect to RadCalNet is a strict adherence to SI-traceability leading to well-understood and defensible uncertainty analysis to ensure that the different sites operating within RadCalNet are consistent with one another. This process includes the requirement to validate uncertainty analyses. One way in which this can be achieved is through field-based comparisons between independently measured reflectance of the ground and the RadCalNet data product for that date/time. To test the potential of such comparisons for uncertainty validation, a comparison campaign has been undertaken by the UK's National Physical Laboratory (NPL) with the University of Arizona (UA) in March 2017 at the Railroad Valley radiometric test site in Nevada, USA using instruments developed for the purpose by UA and the Czech Metrology Institute (CMI). The measurements taken at the site with a new instrument, the Multispectral Transfer Radiometer (MuSTR) have been compared against the RadCalNet bottom-of-atmosphere (BOA) dataset to determine the equivalence of the reflectance. Radiances from MuSTR have also been compared against radiance measurements from the in-situ instrumentation at the site using a 48 % reflectance tarpaulin as a target. The comparisons presented here have demonstrated the utility of field-based comparisons for RadCalNet. In addition, a potential methodology for these comparisons has been developed and potential areas for improvement, including the systematic development of field-based uncertainty analyses, have been identified.",
keywords = "Comparisons, MuSTR, RadCalNet, Railroad Valley, SI Traceability",
author = "Tracy Scanlon and Claire Greenwell and Jeffrey Czapla-Myers and Nikolaus Anderson and Teresa Goodman and Kurt Thome and Emma Wolliams and Geiland Porrovecchio and Petr Lindu{\v s}ka and Marek {\v S}m{\'i}d and Fox, {Nigel P.}",
note = "Funding Information: This work has been funded under the MetEOC-2 project which is an EMRP funded project. The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union. Publisher Copyright: {\textcopyright} Copyright 2017 SPIE.; Sensors, Systems, and Next-Generation Satellites XXI 2017 ; Conference date: 11-09-2017 Through 14-09-2017",
year = "2017",
doi = "10.1117/12.2278649",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Haruhisa Shimoda and Neeck, {Steven P.} and Toshiyoshi Kimura and Jean-Loup Bezy and Roland Meynart",
booktitle = "Sensors, Systems, and Next-Generation Satellites XXI",
}