001     1049207
005     20251217202227.0
024 7 _ |a 10.1364/AO.547144
|2 doi
024 7 _ |a 1559-128X
|2 ISSN
024 7 _ |a 0003-6935
|2 ISSN
024 7 _ |a 1539-4522
|2 ISSN
024 7 _ |a 1540-8981
|2 ISSN
024 7 _ |a 2155-3165
|2 ISSN
024 7 _ |a 10.34734/FZJ-2025-05289
|2 datacite_doi
037 _ _ |a FZJ-2025-05289
082 _ _ |a 530
100 1 _ |a Trim, Simon A.
|0 0000-0002-6009-9888
|b 0
|e Corresponding author
245 _ _ |a Simulation of a simultaneous traceable spectroradiometric calibration of an imaging spectrometer
260 _ _ |a Washington, DC
|c 2025
|b Optical Soc. of America
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1765994171_6046
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Spectroradiometric calibration aims to determine the instrumental spectral response function (ISRF) parameters and radiometric coefficients of an instrument’s spectral bands across all spatial pixels. Typically, this is done by making separate spectral and radiometric calibration measurements. We present a method for the simultaneous traceable spectroradiometric calibration of an imaging spectrometer, using the Spectroscopically Tunable Absolute Radiometric, calibration and characterisation, Optical Ground Support Equipment (STAR-cc-OGSE) facility. We performed the forward simulation of calibration data acquisition by convolving input spectra with the sensor model’s response and simulated a slit scattering function (SSF)-based calibration, allowing for both ISRF coefficients and the absolute spectral responsivities to be accurately retrieved from a single series of measurements. We show how the SSF method minimizes uncertainties compared to the traditional spectroradiometric calibration approach.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5112
|c POF4-511
|f POF IV
|x 0
536 _ _ |a 2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)
|0 G:(DE-HGF)POF4-2173
|c POF4-217
|f POF IV
|x 1
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Buffat, Jim
|0 P:(DE-Juel1)188104
|b 1
700 1 _ |a Hueni, Andreas
|0 P:(DE-HGF)0
|b 2
773 _ _ |a 10.1364/AO.547144
|g Vol. 64, no. 4, p. 782 -
|0 PERI:(DE-600)1474462-4
|n 4
|p 782 -
|t Applied optics
|v 64
|y 2025
|x 1559-128X
856 4 _ |u https://juser.fz-juelich.de/record/1049207/files/Trim%20et%20al_2025_Simulation%20of%20a%20simultaneous%20traceable%20spectroradiometric%20calibration%20of%20an.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1049207
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)188104
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5112
|x 0
913 1 _ |a DE-HGF
|b Forschungsbereich Erde und Umwelt
|l Erde im Wandel – Unsere Zukunft nachhaltig gestalten
|1 G:(DE-HGF)POF4-210
|0 G:(DE-HGF)POF4-217
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-200
|4 G:(DE-HGF)POF
|v Für eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten
|9 G:(DE-HGF)POF4-2173
|x 1
914 1 _ |y 2025
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2024-12-11
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b APPL OPTICS : 2022
|d 2024-12-11
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-11
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2024-12-11
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2024-12-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1230
|2 StatID
|b Current Contents - Electronics and Telecommunications Collection
|d 2024-12-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-11
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IAS-8-20210421
|k IAS-8
|l Datenanalyse und Maschinenlernen
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IAS-8-20210421
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21