Potential for using remote sensing to estimate carbon fluxes across northern peatlands – A review

Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use chang...

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Vydáno v:The Science of the total environment Ročník 615; s. 857 - 874
Hlavní autoři: Lees, K.J., Quaife, T., Artz, R.R.E., Khomik, M., Clark, J.M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Netherlands Elsevier B.V 15.02.2018
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ISSN:0048-9697, 1879-1026, 1879-1026
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Abstract Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration. [Display omitted] •Optical data can be used to drive models of peatland carbon flux.•Water, temperature and vegetation indices are important model factors.•Challenges from peatland heterogeneity and vegetation composition•Remote sensing driven models have the potential to fill gaps in current research
AbstractList Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration.
Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration.Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration.
Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration. [Display omitted] •Optical data can be used to drive models of peatland carbon flux.•Water, temperature and vegetation indices are important model factors.•Challenges from peatland heterogeneity and vegetation composition•Remote sensing driven models have the potential to fill gaps in current research
Author Artz, R.R.E.
Lees, K.J.
Khomik, M.
Quaife, T.
Clark, J.M.
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  surname: Quaife
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  givenname: R.R.E.
  surname: Artz
  fullname: Artz, R.R.E.
  organization: The James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, UK
– sequence: 4
  givenname: M.
  surname: Khomik
  fullname: Khomik, M.
  organization: The James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, UK
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  surname: Clark
  fullname: Clark, J.M.
  organization: Department of Geography and Environmental Science, University of Reading, Whiteknights, PO box 227, Reading RG6 6AB, UK
BackLink https://www.ncbi.nlm.nih.gov/pubmed/29017128$$D View this record in MEDLINE/PubMed
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HZ~
R2-
SEN
SEW
WUQ
XPP
ZXP
ZY4
~HD
NPM
7X8
7S9
L.6
ID FETCH-LOGICAL-c453t-36668b48e9b109146f4745c103dd9d373d91e049e191dda9c21c09b7d6b3bb043
ISICitedReferencesCount 145
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ISSN 0048-9697
1879-1026
IngestDate Sun Sep 28 11:10:38 EDT 2025
Sat Sep 27 19:06:09 EDT 2025
Wed Feb 19 02:41:34 EST 2025
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Tue Nov 18 19:56:06 EST 2025
Fri Feb 23 02:12:31 EST 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords PAR
GPP
PRI
WTD
GHG
OLI
AVHRR
DOC
EC
EF
TANSO
H2O
SPOT
POC
IR
CAI
EO
SWIR
LST
NDWI
SLSTR
USGS
μm
SIF
Satellites
VI
GMAO
MIR
EVI
MERIS
LSWI
APAR
nm
Suomi-NPP
EUMETSAT
fBWI
RS
JAXA
O2
FTS
SAR
Vegetation indices
CO2
VPD
GLO-PEM
NDVI
Ra
ESA
VPM
WI
GOSAT
Rg
RSPB
Rh
Reco
Rm
LUE
DIC
IRGA
EOM
MSI
NASA
LiDAR
InSAR
MTCI
VIIRS
CH4
FIR
MODIS
NEE
SOM
Restored peatlands
LAI
DoD
OCO
REP
TIR
Respiration
ETM
Language English
License This is an open access article under the CC BY license.
Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c453t-36668b48e9b109146f4745c103dd9d373d91e049e191dda9c21c09b7d6b3bb043
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
OpenAccessLink https://dx.doi.org/10.1016/j.scitotenv.2017.09.103
PMID 29017128
PQID 1950162899
PQPubID 23479
PageCount 18
ParticipantIDs proquest_miscellaneous_2000558764
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pubmed_primary_29017128
crossref_primary_10_1016_j_scitotenv_2017_09_103
crossref_citationtrail_10_1016_j_scitotenv_2017_09_103
elsevier_sciencedirect_doi_10_1016_j_scitotenv_2017_09_103
PublicationCentury 2000
PublicationDate 2018-02-15
PublicationDateYYYYMMDD 2018-02-15
PublicationDate_xml – month: 02
  year: 2018
  text: 2018-02-15
  day: 15
PublicationDecade 2010
PublicationPlace Netherlands
PublicationPlace_xml – name: Netherlands
PublicationTitle The Science of the total environment
PublicationTitleAlternate Sci Total Environ
PublicationYear 2018
Publisher Elsevier B.V
Publisher_xml – name: Elsevier B.V
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Snippet Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of...
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SubjectTerms carbon
carbon cycle
climate
Earth atmosphere
ecosystems
eddy covariance
GPP
greenhouse gases
land use change
landscapes
NEE
peatlands
remote sensing
Respiration
Restored peatlands
Satellites
spatial data
uncertainty
Vegetation indices
Title Potential for using remote sensing to estimate carbon fluxes across northern peatlands – A review
URI https://dx.doi.org/10.1016/j.scitotenv.2017.09.103
https://www.ncbi.nlm.nih.gov/pubmed/29017128
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