Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

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Ancin-Murguzur, Francisco Javier; Brown, Antony G.; Clarke, Charlotte; Sjøgren, Per; Svendsen, John Inge; Alsos, Inger Greve, 2020, "Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?", https://doi.org/10.18710/OJC4TH, DataverseNO, V1

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Description	This dataset contains the reference data and script to develop a predictive NIRS model to measure LOI in lacustrine sediments, as described in the article: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? (2019-12-27)
Subject	Earth and Environmental Sciences
Keyword	Holocene, Lacustrine, Paleolimnology, Partial least squares (PLS), Sediment organic matter
Related Publication	Ancin-Murguzur, F.J., Brown, A.G., Clarke, C. et al. How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?. J Paleolimnol 64, 59–69 (2020). https://doi.org/10.1007/s10933-020-00121-5 doi: 10.1007/s10933-020-00121-5
License/Data Use Agreement	CC0 1.0

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	00_ReadMe_file_LOI.txt Plain Text - 1.6 KB Published Mar 9, 2020 26 Downloads MD5: 2e7d26cc64217682a47be9689c048baa README file	Preview "00_ReadMe_file_LOI.txt" Access File File Access Public Download Options Plain Text Download Metadata Data File Citation EndNote XML RIS BibTeX
	LOI_Modeling_Script.R R Syntax - 3.2 KB Published Mar 9, 2020 24 Downloads MD5: 22498b95800e905b07643382b720afeb Script to develop the LOI predictive model based on lacustrine samples scanned by means of near infra-red reflectance spectroscopy	Preview "LOI_Modeling_Script.R" Access File File Access Public Download Options R Syntax Download Metadata Data File Citation EndNote XML RIS BibTeX
	LOI_Reference_Dataset.txt Plain Text - 13.1 MB Published Mar 9, 2020 41 Downloads MD5: 5875ab1e2b7614cb30e0b23be2e4439b Reference dataset containing the spectral values, LOI values and lake ID	Preview "LOI_Reference_Dataset.txt" Access File File Access Public Download Options Plain Text Download Metadata Data File Citation EndNote XML RIS BibTeX

Citation Metadata

Persistent Identifier	doi:10.18710/OJC4TH
Publication Date	2020-03-09
Title	Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
Author	Ancin-Murguzur, Francisco Javier (UiT The Arctic University of Norway) - ORCID: 0000-0002-1435-5190 Brown, Antony G. (Palaeoenvironmental Laboratory University of Southampton (PLUS)) Clarke, Charlotte (Palaeoenvironmental Laboratory University of Southampton (PLUS)) - ORCID: 0000-0002-1296-2229 Sjøgren, Per (UiT The Arctic University of Norway) - ORCID: 0000-0001-7319-4748 Svendsen, John Inge (University of Bergen) - ORCID: 0000-0002-0570-466X Alsos, Inger Greve (UiT The Arctic University of Norway) - ORCID: 0000-0002-8610-1085
Point of Contact	Use email button above to contact. Ancin-Murguzur, Francisco Javier (UiT The Arctic University of Norway)
Description	This dataset contains the reference data and script to develop a predictive NIRS model to measure LOI in lacustrine sediments, as described in the article: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? (2019-12-27)
Subject	Earth and Environmental Sciences
Keyword	Holocene Lacustrine Paleolimnology Partial least squares (PLS) Sediment organic matter
Related Publication	Ancin-Murguzur, F.J., Brown, A.G., Clarke, C. et al. How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?. J Paleolimnol 64, 59–69 (2020). https://doi.org/10.1007/s10933-020-00121-5 doi: 10.1007/s10933-020-00121-5 https://doi.org/10.1007/s10933-020-00121-5
Language	English
Producer	UiT The Arctic University of Norway (UiT) https://en.uit.no/
Distributor	UiT The Arctic University of Norway (UiT The Arctic University of Norway) https://dataverse.no/dataverse/uit
Depositor	Ancin Murguzur, Francisco Javier
Deposit Date	2019-12-27
Date of Collection	Start Date: 2016-02-01 ; End Date: 2017-06-01
Data Type	Experimental data

Geospatial Metadata

Geographic Coverage	Norway, Troms og Finnmark Norway, Svalbard, Skartjørna lake Russian Federation, Priuralsky district

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